Category Archives: research

Phil 8.23.17

Research

  • Started the ball rolling on 899 approval and getting together waith Wayne for a chat

8:30 – 5:30 ASRC

  • BRI suspended payment on the contract, so much churn. Lots of discussions with many people. Looks like an interview on Friday?
  • Had to reinstall Office. Getting coffee…
  • Connnected to my SVN and got the LabeledTensor code to work on. Need to add the support for more than 32k entries.

Phil 8.18.17

7:00 – 8:00 Research

  • Got indexFromLocation() working. It took some fooling around with Excel. Here’s the method:
    public int[] indexFromLocation(double[] loc){
        int[] index = new int[loc.length];
        for(int i = 0; i < loc.length; ++i){
            double findex = loc[i]/mappingStep;
            double roundDown = Math.floor(findex);
            double roundUp = Math.ceil(findex);
            double lowdiff = findex - roundDown;
            double highdiff = roundUp - findex;
            if(lowdiff < highdiff){
                index[i] = (int)roundDown;
            }else{
                index[i] = (int)roundUp;
            }
        }
        return index;
    }
  • And here are the much cleaner results:
    • [0.00, 0.00] = [0, 0]
      [0.00, 0.10] = [0, 0]
      [0.00, 0.20] = [0, 1]
      [0.00, 0.30] = [0, 1]
      [0.00, 0.40] = [0, 2]
      [0.00, 0.50] = [0, 2]
      [0.00, 0.60] = [0, 2]
      [0.00, 0.70] = [0, 3]
      [0.00, 0.80] = [0, 3]
      [0.00, 0.90] = [0, 4]
      [0.00, 1.00] = [0, 4]

      [1.00, 0.00] = [4, 0]
      [1.00, 0.10] = [4, 0]
      [1.00, 0.20] = [4, 1]
      [1.00, 0.30] = [4, 1]
      [1.00, 0.40] = [4, 2]
      [1.00, 0.50] = [4, 2]
      [1.00, 0.60] = [4, 2]
      [1.00, 0.70] = [4, 3]
      [1.00, 0.80] = [4, 3]
      [1.00, 0.90] = [4, 4]
      [1.00, 1.00] = [4, 4]
  • Another thought that struck me as far as the (int) constraint is that I can have a number of ArrayLists that are embedded in a an object that has the first and last index in it. These would be linked together to provide unconstrained (MAX_VALUE or 2,147,483,647 lists) storage

8:30 – 4:30 BRI

  • I realized yesterday that the Ingest and Query microservices need to access the same GeoMesa Spring service. That keeps all the general store/query GeoMesa access code in one place, simplifies testing and allows for DI to provide the correct (hbase, accumulo, etc) implementation through a facade interface.
  • Got tangled up with getting classpaths right and importing the proper libraries
  • Got the maven files behaving, or at least not complaining on mvn clean and mvn compile!
  • Well that’s a new error: Error: Could not create the Java Virtual Machine. I get that running the new installation with the geomesa-quickstart-hbase
    • Ah, that’s what will happen when you paste your command-line arguments into the VM arguments space just above where it should go…
    • Wednesday’s goal will to verify that HBaseQuickStart is running correctly in its new home and start to turn it into a service.

Phil 8.17.17

BRI – one hour chasing down research hours from Jan – May

7:00 – 6:00 Research

  • Found this on negative flocking influences: The rise of negative partisanship and the nationalization of US elections in the 21st century.  Paper saved to Lit Review
    • One of the most important developments affecting electoral competition in the United States has been the increasingly partisan behavior of the American electorate. Yet more voters than ever claim to be independents. We argue that the explanation for these seemingly contradictory trends is the rise of negative partisanship. Using data from the American National Election Studies, we show that as partisan identities have become more closely aligned with social, cultural and ideological divisions in American society, party supporters including leaning independents have developed increasingly negative feelings about the opposing party and its candidates. This has led to dramatic increases in party loyalty and straight-ticket voting, a steep decline in the advantage of incumbency and growing consistency between the results of presidential elections and the results of House, Senate and even state legislative elections. The rise of negative partisanship has had profound consequences for electoral competition, democratic representation and governance.
  • Working on putting together an indexable high-dimension matrix that can contain objects. Generally, I’d expect it to be doubles, but I can see Strings and Objects as well.
  • Starting off by seeing what’s in the newest Apache Commons Math (v 3.6.1)
  • Found SimpleTensor, which uses the Efficient Java Matrix Library (EJML) and creates a 3D block of rows, columns and slices. THought it was what I wanted, but nope
  • Looks like there isn’t a class that would do what I need to do, or that I can even modify. I’m thinking that the best option is to use org.apache.commons.math3.linear.AbstractRealMatrix as a template.
  • Nope, coudn’t figure out how to do things as nested lists. So I’m doing it C-Style, where you really only have one array that you index into. Here’s a 4x4x4x4 Tensor filled with zeroes:
    Total elements = 256
    0.0:[0, 0, 0, 0], 0.0:[1, 0, 0, 0], 0.0:[2, 0, 0, 0], 0.0:[3, 0, 0, 0],
    0.0:[0, 1, 0, 0], 0.0:[1, 1, 0, 0], 0.0:[2, 1, 0, 0], 0.0:[3, 1, 0, 0],
    0.0:[0, 2, 0, 0], 0.0:[1, 2, 0, 0], 0.0:[2, 2, 0, 0], 0.0:[3, 2, 0, 0],
    0.0:[0, 3, 0, 0], 0.0:[1, 3, 0, 0], 0.0:[2, 3, 0, 0], 0.0:[3, 3, 0, 0],
    0.0:[0, 0, 1, 0], 0.0:[1, 0, 1, 0], 0.0:[2, 0, 1, 0], 0.0:[3, 0, 1, 0],
    ….
    0.0:[0, 2, 3, 3], 0.0:[1, 2, 3, 3], 0.0:[2, 2, 3, 3], 0.0:[3, 2, 3, 3],
    0.0:[0, 3, 3, 3], 0.0:[1, 3, 3, 3], 0.0:[2, 3, 3, 3], 0.0:[3, 3, 3, 3]
  • The only issue that I currently have is that ArrayLists are indexed by int, so the total size is 32k elements. That should be good enough for now, but it will need to be fixed.
  • set() and get() work nicely:
    lt.set(new int[]{0, 1, 0, 0}, 9.9);
    lt.set(new int[]{3, 3, 3, 3}, 3.3);
    
    System.out.println("[0, 1, 0, 0] = " + lt.get(new int[]{0, 1, 0, 0}));
    System.out.println("[3, 3, 3, 3] = " + lt.get(new int[]{3, 3, 3, 3}));
    
    [0, 1, 0, 0] = 9.9
    [3, 3, 3, 3] = 3.3
  • Started the indexFromLocation method, but this is too sloppy:
    index[i] = (int)Math.floor(Math.round(loc[i]/mappingStep));

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

Phil7.25.16

7:00 – 4:00 VTX

  • Rollers
  • Reworking the lit review. Meeting set up with Wayne for tomorrow at 4:00.
  • Still thinking about modelling. I could use sets of strings that would define a CAs worldview and then compare individuals by edit distance.
    • Not sure how to handle weights, a number, or repetitions of the character?
    • Comparing a set of CAs using centrality could see what the most important items are in that (overall and sub) population. how close the individual CA conforms to that distribution is a measure of the ‘belonging’?
    • CAs could adjust their internal model. Big changes should be hard, little changes should be easy. Would the dropping of a low ranked individual item result in a big change in edit distance with a group that doesn’t have the item?
    • Working on infrastructure that builds, collects and maintains Factoids

Phil 7.22.16

7:00 – 1:00 VTX

  • More bubble modelling. Found a nice paper from a financial perspective that looks like a good source for similar models.
  • Split out the calculation and spreadsheet functions to support snapshots and debugging.
    • Set up the base class to be the control. Explorers only look outside their SD, while confirmers and avoiders stay within. Not sure how to tease out the difference between those. I think it will have something to do with the way they look for information, which is beyond the scope of this model for now. Also switched to a random distribution. Here’s an initial result. Much more work to follow

GP

  • I was riding and thinking about something I read on fivethirtyeight.comThis isn’t the most artful way to say it, but it’s like, where do you go when the only people who seem to agree with you on taxes hate black people?” It’s by Ben Howe, a redstate commentator. And it makes me think that rather than basing the sim on only one value, there should be a cluster. Confirmed could look for a match in the cluster while avoiders would clusters if they hit somethings that doesn’t match. And the distance from the value should matter. Adopting a very different concept should take more energy than a similar one. And this makes me think that the CAs have to have a bit more alife in them. They need to budget their energy with reference to their internal and external states.
  • And then mom died. Here’s the OPM web page that matters: https://www.opm.gov/retirement-services/my-annuity-and-benefits/life-events/death/report-of-death/

Phil 6.21.16

7:00 – 5:00 VTX

  • Finished MostRecent.
  • Checked Data directory into SVN
  • Testing rating algorithms. Seems to be working pretty well 🙂
  • Rated all day. Should finish tomorrow.
  • Worked through paragon and fallen angel patterns with Aaron. Pulled out by bayesian spreadsheets and realized I no longer understood them…

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 6.13.16

6:30 – 2:30 VTX