Category Archives: Lit Review

Phil 8.16.17

7:00 – 8:00 Research

  • Added takeaway thoughts to my C&C writeup.
  • Working out how to add capability to the sim for P&RCH paper. My thoughts from vacation:
    • The agents contribution is the heading and speed
    • The UI is what the agent’s can ‘see’
    • The IR is what is available to be seen
    • An additional part might be to add the ability to store data in the space. Then the behavior of the IR (e.g. empty areas) would b more apparent, as would the effects of UI (only certain data is visible, or maybe only nearby data is visible) Data could be a vector field in Hilbert space, and visualized as color.
  • Updated IntelliJ
  • Working out how to to have a voxel space for the agents to move through that can also be drawn. It’s any number of dimensions, but it has to project to 2D. In the case of the agents, I just choose the first two axis. Each agent has an array of statements that are assembled into a belief vector. The space can be an array of beliefs. Are these just constructed so that they fill a space according to a set of rules? Then the xDimensionName and yDimensionName axis would go from (0, 1), which would scale to stage size? IR would still be a matter of comparing the space to the agent’s vector. Hmm.
  • This looks really good from an information horizon perspective: The Role of the Information Environment in Partisan Voting
    • Voters are often highly dependent on partisanship to structure their preferences toward political candidates and policy proposals. What conditions enable partisan cues to “dominate” public opinion? Here I theorize that variation in voters’ reliance on partisanship results, in part, from the opportunities their environment provides to learn about politics. A conjoint experiment and an observational study of voting in congressional elections both support the expectation that more detailed information environments reduce the role of partisanship in candidate choice

9:00 – 5:00 BRI

  • Good lord, the BoA corporate card comes with SIX seperate documents to read.
  • Onward to Chapter Three and Spring database interaction
  • Well that’s pretty clean. I do like the JdbcTemplate behaviors. Not sure I like the way you specify the values passed to the query, but I can’t think of anything better if you have more than one argument:
    @Repository
    public class EmployeeDaoImpl implements EmployeeDao {
        @Autowired
        private DataSource dataSource;
    
        @Autowired
        private JdbcTemplate jdbcTemplate;
    
        private RowMapper<Employee> employeeRowMapper = new RowMapper<Employee>() {
            @Override
            public Employee mapRow(ResultSet rs, int i) throws SQLException {
                Employee employee = new EmployeeImpl();
                employee.setEmployeeAge(rs.getInt("Age"));
                employee.setEmployeeId(rs.getInt("ID"));
                employee.setEmployeeName(rs.getString("FirstName") + " " + rs.getString("LastName"));
                return employee;
            }
        };
    
        @Override
        public Employee getEmployeeById(int id) {
            Employee employee = null;
    
            employee = jdbcTemplate.queryForObject(
                    "select * from Employee where id = ?",
                    new Object[]{id},
                    employeeRowMapper
            );
            return employee;
        }
    
        public List<Employee> getAllEmployees() {
            List<Employee> eList = jdbcTemplate.query(
                    "select * from Employee",
                    employeeRowMapper
            );
            return eList;
        }
    }
  • Here’s the xml to wire the thing up:
    <context:component-scan base-package="org.springframework.chapter3.dao"/>
    <bean id="employeeDao" class="org.springframework.chapter3.dao.EmployeeDaoImpl"/>
    
    <bean id="dataSource"
          class="org.springframework.jdbc.datasource.DriverManagerDataSource">
        <property name="driverClassName" value="${jdbc.driverClassName}" />
        <property name="url" value="${jdbc.url}" />
        <property name="username" value="xxx"/>
        <property name="password" value="yyy"/>
    </bean>
    
    <bean id="jdbcTemplate" class="org.springframework.jdbc.core.JdbcTemplate">
        <property name="dataSource" ref="dataSource" />
    </bean>
    
    <context:property-placeholder location="jdbc.properties" />
  • And here’s the properties. Note that I had to disable SSL:
    jdbc.driverClassName=com.mysql.jdbc.Driver
    jdbc.url=jdbc:mysql://localhost:3306/sandbox?autoReconnect=true&useSSL=false

Phil 7.18.16

7:00 – 3:30 VTX

  • Writing and reworking Lit Review 2. After that, I need to rework the research plan so that RQs and Hs are interchanged.
  • Meeting with Ned Thursday evening?
  • Meeting with Thom second week of August.
  • If there is time today, try to add color change to the table cells to reflect rank. Failing that, add a column that shows relative motion? Both?
    • Added a Rank and Delta field. That seems to be working fine.
  • Finished lockout task
  • Starting Gateway exposes old APIs task

Phil 6.20.16

7:00 – 7:00 VTX

  • Building chair corpus = Current and Cited
  • Filled MostCited.
  • Rating a few more pages. Still not getting any name hits.
  • Going to advanced search and entering items into each field, I get a different looking query:
    https://www.google.ca/search?as_q=New+York&as_epq=Nader+Golian&as_oq=+license+board+practice+patient+physician+order+health+practitioner+medicine+medical
    • These seem to be the important differences
    • as_q=New+York — This is a ‘normal’ query
    • as_epq=Nader+Golian — This must be in the results
    • as_oq=+license+board+practice+patient+physician+order+health+practitioner+medicine+medical — at least one of these must be in the result
  • Going to add a test to look for the name in the query (and the state?) and at least check the NA box and throw up a dialog. Could also list the number of occurrences by default in the notes

1:00 – Patrick’s proposal

  • Framing of problem and researcher
  • Overview of the problem space
    • Ready to Hand
    • Extension of self
  • Assistive technology abandonment
    • Ease of Acquisition
    • Device Performance
    • Cost and Maintenance
    • Stigma
    • Alignment with lifestyles
  • Prior Work
    • Technology Use
    • Methods Overview
      • Formative User Needs
      • Design Focus Groups
      • Design Evaluation and Configuration Interviews
    • Summary of Findings
    • Priorities
      • Maintain form factor
      • Different controls for different regions
      • Familiarity
      • Robustness to environmental changes
    • Potential of the wheelchair
      • Nice diagram. Shows the mapping from a chair to a smartphone
    • Inputs to wheelchair-mounted devices
    • Force sensitive device, new gestures and insights
    • Summary (This looks like research through design. Why no mention?)
      • Prototypes
      • Gestures
      • Demonstration
  • Proposed Work
    • Passive Haptic Rehabilitation
      • Can it be done
      • How effective
      • User perception
      • Study design!!!
    • Physical Activity and Athletic Performance
      • Completed: Accessibility of fitness trackers. (None of this actually tracks to papers in the presentation)
      • Body location and sensing
      • Misperception
        • Semi-structured interviews
        • Low experience / High interest (Lack of system trust!)
    • Chairable Computing for Basketball
      • Research Methods
        • Observations
        • Semi-structured interviews
        • Prototyping
        • Data presentation – how does one decide what they want from what is available?
  • What is the problem – Helena
    • Assistive technologies are not being designed right. We need to improve the design process.
    • That’s too general – give me a citation that says that technology abandonment WRT wheelchair use has high abandonment
    • Patrick responds with a bad design
    • Helena – isn’t the principal user-centered design. How has the HCI community done this before WRT other areas than wheelchairs to interact with computing systems
    • Helena – Embodied interaction is not a new thing, this is just a new area.Why didn’t you group your work. Is the prior analysis not embodied? Is your prior work not aligned with this perspective
  • How were the design principles used o develop an refine the pressure sensors?

More Reading

  • Creating Friction: Infrastructuring Civic Engagement in Everyday Life
    • This is the confirming information bubble of the ‘ten blue links’: Because infrastructures reflect the standardization of practices, the social work they do is also political: “a number of significant political, ethical and social choices have without doubt been folded into its development” ([67]: 233). The further one is removed from the institutions of standardization, the more drastically one experiences the values embedded into infrastructure—a concept Bowker and Star term ‘torque’ [9]. More powerful actors are not as likely to experience torque as their values more often align with those embodied in the infrastructure. Infrastructures of civic engagement that are designed and maintained by those in power, then, tend to reflect the values and biases held by those in power.
  • Meeting with Wayne. My hypothesis and research questions are backwards but otherwise good.

Phil 6.15.16

7:00 – 10:00, 12:00 – 4:00 VTX

  • Got the official word that I should be charging the project for research. Saved the email this time.
  • Continuing to work on the papers list
  • And in the process of looking at Daniele Quercia‘s work, I found Auralist: introducing serendipity into music recommendation which was cited by
    An investigation on the serendipity problem in recommender systems. Which has the following introduction:

    • In the book ‘‘The Filter Bubble: What the Internet Is Hiding from You’’, Eli Pariser argues that Internet is limiting our horizons (Parisier, 2011). He worries that personalized filters, such as Google search or Facebook delivery of news from our friends, create individual universes of information for each of us, in which we are fed only with information we are familiar with and that confirms our beliefs. These filters are opaque, that is to say, we do not know what is being hidden from us, and may be dangerous because they threaten to deprive us from serendipitous encounters that spark creativity, innovation, and the democratic exchange of ideas. Similar observations have been previously made by Gori and Witten (2005) and extensively developed in their book ‘‘Web Dragons, Inside the Myths of Search Engine Technology’’ (Witten, Gori, & Numerico, 2006), where the metaphor of search engines as modern dragons or gatekeepers of a treasure is justified by the fact that ‘‘the immense treasure they guard is society’s repository of knowledge’’ and all of us accept dragons as mediators when having access to that treasure. But most of us do not know how those dragons work, and all of us (probably the search engines’ creators, either) are not able to explain the reason why a specific web page ranked first when we issued a query. This gives rise to the so called bubble of Web visibility, where people who want to promote visibility of a Web site fight against heuristics adopted by most popular search engines, whose details and biases are closely guarded trade secrets.
    • Added both papers to the corpus. Need to read and code. What I’m doing is different in that I want to add a level of interactivity to the serendipity display that looks for user patterns in how they react to the presented serendipity and incorporate that pattern into a trustworthiness evaluation of the web content. I’m also doing it in Journalism, which is a bit different in its constraints. And I’m trying to tie it back to Group Polarization and opinion drift.
  • Also, Raz Schwartx at Facebook: , Editorial Algorithms: Using Social Media to Discover and Report Local News
  • Working on getting all html and pdf files in one matrix
  • Spent the day chasing down a bug where if the string being annotated is too long (I’ve set the  number of wordes to 60), then we skip. THis leads to a divide by zero issue. Fixed now

Phil 6.7.16

6:00 – 10:00, 12:00 – 5:00 Writing

Phil 6.4.16

7:30 – 1:30 Writing

  • More on libraries and serendipity. Found lots, and then went on to look for metions in electronic retrieval. Found Foster’s A Nonlinear Model of Information-Seeking Behavior, which also has some spiffy citations. Going to take a break from writing and actually read this one. Because, I just realized that interdisciplinary researchers are the rough academic equivalent of the explorer pattern.
  • Investigating Information Seeking BehaviorUsing the Concept of Information Horizons
    • Page 3 – To design and develop a new research method we used Sonnenwald’s (1999) framework for human information behavior as a theoretical foundation. This theoretical framework suggests that within a context and situation is an ‘information horizon’ in which we can act. For a particular individual, a variety of information resources may be encompassed within his/her information horizon. They may include social networks, documents, information retrieval tools, and experimentation and observation in the world. Information horizons, and the resources they encompass, are determined socially and individually. In other words, the opinions that one’s peers hold concerning the value of a particular resource will influence one’s own opinions about the value of that resource and, thus, its position within one’s information horizon. 

Phil 5.31.16

7:00 – 4:30 VTX

  • Writing. Working on describing how maintaining many codes in a network contains more (and more subtle) information than grouping similar codes.
  • Working on the UrlChecker
    • In the process, I discovered that the annotation.xml file is unique only for the account and not for the CSE. All CSEs for one account are contained in one annotation file
    • Created a new annotation called ALL_annotations.xml
    • fixed a few things in Andy’s file
    • Reading in everything. Now to produce the new sets of lists.
    • I think it’s just easier to delete all the lists and start over.
    • Done and verified. You run UrlChecker from the command line, with the input file being a list of domains (one per line) and the ALL_annotations.xml file.
  • https://cwiki.apache.org/confluence/display/CTAKES/cTAKES+3.2
  • Need to add a Delete or Hide button to reduce down a large corpus to a more effective size.
  • Added. Tomorrow I’ll wire up the deletion of a row or cilumn and the recreation of the initialMatrix

Phil 5.30.16

7:00 – 10:00 Thesis/VTX

  • Built a new matrix for the coded lit review. I had coded a couple of more papers
  • Working on copying over the read papers into a new folder that I can run text analytics over
  • After carefully reading through the doc manager list and copying over each paper, I just discovered I could have exported selected.
  • Ooops: Exception in thread “JavaFX Application Thread” java.lang.IllegalArgumentException: Invalid column index (16384).  Allowable column range for EXCEL2007 is (0..16383) or (‘A’..’XFD’)
    • Going to add a limit of
      SpreadsheetVersion.EXCEL2007.getMaxColumns()-8

      columns for now. Clearly that can be cut down.

    • Figuring out where to cut the terms. I’m summing the columns of the LSI calculation, starting at the highest value and then dividing that by the sum of all values. The top 20% of rank weights gives 280 columns. Going to try that first
    • Success! Some initial thoughts
      • The coded version is much more ‘crisp’
      • There are interesting hints in the LSI version
      • Clicking on a term or paper to see the associated items is really nice.
      • I think that document subgroups might be good/better, and it might be possible to use the tool to help build those subgroups. This goes back to the ‘hiding’ concept. (hide item / hide item and associated)

Phil 5.17.16

7:00 -7:00

  • Great discussion with Greg yesterday. Very encouraging.
  • Some thoughts that came up during Fahad’s (Successful!) defense
    • It should be possible to determine the ‘deletable’ codes at the bottom of the ranking by setting the allowable difference between the initial ranking and the trimmed rank.
    • The ‘filter’ box should also be set by clicking on one of the items in the list of associations for the selected items. This way, selection is a two-step process in this context.
    • Suggesting grouping of terms based on connectivity? Maybe second degree? Allows for domain independence?
    • Using a 3D display to show the shared second, third and nth degree as different layer
    • NLP tagged words for TF-IDF to produce a more characterized matrix?
    • 50 samples per iteration, 2,000 iterations? Check! And add info to spreadsheet! Done, and it’s 1,000 iterations
  • Writing
  • Parsing Jeremy’s JSON file
    • Moving the OptionalContent and JsonLoadable over to JavaJtils2
    • Adding javax.persistence-2.1.0
    • Adding json-simple-1.1.1
    • It worked, but it’s junk. It looks like these are un-curated pages
  • Long discussion with Aaron about calculating flag rollups.

Phil 5.6.16

7:00 – 4:00 VTX

  • Today’s shower thought is to compare the variance of the difference of two (unitized) rank matrices. The maximum difference would be (matrix size), so we do have a scale. If we assume a binomial distribution (there are many ways to be slightly different, only two ways to be completely different), then we can use a binomial (one tailed?) distribution centered on zero and ending at (matrix size). That should mean that I can see how far one item is from the other? But it will be withing the context of a larger distribution (all zeros vs all ones)…
  • Before going down that rabbit hole, I decided to use the bootstrap method just to see if the concept works. It looks mostly good.
    • Verified that scaling a low-ranked item (ACLED) by 10 has less impact than scaling the highest ranking item (P61) by 1.28.
    • Set the stats text to red if it’s outside 1 SD and green if it’s within.
    • I think the terms can be played around with more because the top one (Pertinence) gets ranked at .436, while P61 has a rank of 1.
    • There are some weird issues with the way the matrix recalculates. Some states are statistically similar to others. I think I can do something with the thoughts above, but later.
  • There seems to be a bug calculating the current mean when compared to the unit mean. It may be that the values are so small? It’s occasional….
  • Got the ‘top’ button working.
  • And that’s it for the week…

LMT With Data2

Oh yeah – Everything You Ever Wanted To Know About Motorcycle Safety Gear