Discover the world's scientific knowledge

World Conference on Existential Harmony – 2014-15

The world is facing many a challenge like pollution of air, water and soil. Natural resources are fast depleting. Population growth-rate is outstripping resources worldwide. There is an uneven distribution of sources of livelihood. Multinational corporations are putting undue pressure on governments and twisting their policies. Nuclear weapons pose an imminent threat to the survival of mankind. Confrontationist policies and use of military power to resolve economic and political interests are on the rise. Genocide, racism, fundamentalism and terrorism have wrought havoc worldwide. Issues relating to personal life like rising divorce rate, depression, stress and lifestyle diseases etc., are causing an unbearable tension in the society. Therefore, a holistic approach is needed to grapple with the current unhealthy syndrome.

IASE (D) University and Gandhi Vidya Mandir, Sardarshahar, Rajasthan, India has launched a hydra-headed Interdisciplinary Research Project on peace and harmony. Approximately 100 interdisciplinary and multidisciplinary research projects would be undertaken under the guidance of eminent professors and research scholars. The University has established Six Harmony chairs (Harmony Professors) to co-ordinate these projects namely Chair of Philosophical Harmony, Religious harmony, Harmony through Science & Technology, Social Harmony, Political Harmony & Economical Harmony. This will be followed by a World Conference on Existential Harmony 2014 to explore the philosophy of existential harmony. The Conference will also highlight the scientific aspects of the universal order and examine social, economic and political theories with the objective of drafting a universally acceptable curriculum for college and school students.

Dear colleagues! Each of us may wish to clear up what Innovative Pedagogy is about? Here is what I - as a curator of this topic and Professor of Education - agree with for the time being.

Pedagogy is the study of being a teacher or the process of education. Pedagogy as a science explores the processes by which society deliberately can transmit its accumulated knowledge, skills, and values from one generation to another, from one hand, and activate individual person’s growth – from another. The major pedagogical question is how to educate a humane being? How to enhance students learning and meet the needs of various types of learners?

These tools may include educational goals set by the student and teacher, strategies or styles of instruction, the educator’s own philosophical beliefs, the student’s background knowledge and experience, the curriculum, modern technological devices, monitoring and test system and others.

The term innovation derives from the Latin word innovatus, which is the noun form of innovare "to renew or change". Innovation generally refers to the creation of better or more effective products, processes, technologies, or ideas that are accepted by those in charge of education – teachers, administrators, parents, etc. Innovation differs from invention or renovation in that innovation generally signifies a substantial positive change compared to incremental changes. Not seldom innovations are not accepted by educators or policy makers. So some say true innovations are heretic and belong to future.

In this context Innovative Pedagogy is the study of being an innovative educator or the processes of innovative education/teaching. And the key question of Innovative Pedagogy is - What are the educational, psychological, organizational factors/conditions that have a formative utmost effect on the mind, character, or physical ability of an individual? Here are main steps of thinking on innovative process construction – 1. What is desirable for users (both students and future employers)? 2. What is possible with curriculum and technology? 3. What is viable at educational market? 4. What is beneficial for the community? 5. What is sustainable for our environment?

Thus, Innovative Pedagogy as a science and practice has a responsibility to prepare citizens of the knowledge society who are able to be creative, face changes, manage and analyze information, and work with knowledge. Worldwide schools and teachers are in various states of reform to adapt their instructional practices and educational systems to be more effective. A good example is Sudbury Valley School at http://www.youtube.com/watch?v=91TfXsmW_aA

The role of teachers has shifted from being a subject matter expert who transmits information to acting as a facilitator of student learning in the knowledge society. Current reforms emphasize teachers develop students' capabilities in problem solving, teamwork, and learning to learn, reflective thinking.

Teachers and schools exist within these knowledge societies, which require that they be adept at the same skills they are developing in their students. If teachers do not acquire and display this capacity to redefine their skills for the task of teaching, and if they do not model in their own conduct the very qualities flexibility, networking, creativity, innovative thinking that are now key outcomes for students, then the challenge of schooling in the millennium will not be met. Hopefully, taking part in the discussions under the topic of Innovative Pedagogy we all here contribute to these noble and urgent world tasks. Good luck to all us!

Various current research lines are dedicated to the analysis and study of the technology science and the understanding of the socalled nature of science and technology(NdCyT),specialists in the field recognize today that the nature of science and technology is one of the essential components of literacy in science and technology, whose aim is the understanding of the implications and applications of science and technology in the context of experience and participation personal and social citizens. This is clear, but from th  school and its curriculum in Sciences presently does a debt with them, as it is sure that they should promote strategies to improve scientific education... but there are? and the applicability in their contexts?

Henry Jenkins

Over the past few years, transmedia storytelling has become a hot buzzword in Hollywood and Madison Avenue alike--"the next big thing" or "the last big thing" depending on whom you ask. Last year, the Producer's Guild announced a new job title, Transmedia Producer, a decision that has more or less established the term as an industry standard. More and more companies are laying claim to expertise in producing transmedia content. But many using the term don't really understand what they are saying. So let's look at what people are getting wrong about transmedia.

Myth 1: Transmedia Storytelling refers to any strategy involving more than one media platform.

The entertainment industry has long developed licensed products, reproducing the same stories across multiple channels (for example, novelizations). Increasingly, broadcast content is also available on line. And many films are adopted from books (or now, comic books). None of these necessarily constitute transmedia storytelling. In transmedia, elements of a story are dispersed systematically across multiple media platforms, each making their own unique contribution to the whole. Each medium does what it does best--comics might provide back-story, games might allow you to explore the world, and the television series offers unfolding episodes.

Myth 2: Transmedia is basically a new promotional strategy.

Yes, many early transmedia experiments were funded through marketing budgets. Transmedia has been closely linked to the industry's new focus on "audience engagement" and sometimes uses "viral" (or "spreadable") media strategies. But, the best transmedia is driven by a creative impulse. Transmedia allows gifted storytellers to expand their canvas and share more of their vision with their most dedicated fans.

Myth 3: Transmedia means games.

The rise of alternate reality games coupled with mass media properties is part of what's generating excitement here. Transmedia properties combine cultural attractors (which draw together a highly invested audience) and cultural activators (which gives that audience something to do). Games are a good way to give your fans something to do, but they are by no means the only model out there.

Myth 4: Transmedia is for geeks.

So far, most of transmedia has been designed for early adapters--folks at home with digital applications, with disposable time and income, and especially the 18-27 year old males who have disappeared from the Nielsen Ratings. So far, much transmedia content has targeted children through cartoons or geeks through science fiction, horror, and fantasy franchises. But, there are plenty of signs that transmedia experiences may appeal more broadly. For example, some believe transmedia strategies may be key to the survival of soap operas.

Myth 5: Transmedia requires a large budget.

Fans now expect transmedia content around blockbuster films and cult television series, but there are also many successes with using transmedia to build audience awareness around low budget and independent media productions--from The Blair Witch Project to District 9 to Paranormal Activity. It's about developing the appropriate mix of media for the genre, the audience, and the budget of a particular production.

Myth 6: Everything should go transmedia.

Many stories are told perfectly well within a single medium, and the audience leaves satisfied, ready for something else. Transmedia represents a strategy for telling stories where there is a particularly diverse set of characters, where the world is richly realized, and where there is a strong back-story or mythology that can extend beyond the specific episodes being depicted in the film or television series. Transmedia represents a creative opportunity, but it should never be a mandate for all entertainment.

Myth 7: Transmedia is "so ten minutes ago."

The first generation series to push transmedia, (Lost, Heroes, Ghost Whisperer, and 24) ended last season, and some of attempts to replace them--from Flash Forward to The Event--failed. But many of the big hits--including Glee, True Blood, and The Walking Dead--model new transmedia strategies to attract and sustain audience engagement. Transmedia storytelling is still about the stories and if the stories do not capture the imagination, no amount of transmedia extension can repair the damage. But, we will see innovative new approaches because transmedia as a strategy responds to a media environment that rewards being everywhere your audience might be and giving your fans a chance to drill deeper into the stories they love.

------

Henry Jenkins is the Provost's Professor of Communications, Journalism, Cinematic Arts, and Education at the University of Southern California. His book, Convergence Culture: Where Old and New Media Collide, has been credited with inspiring much of the buzz on transmedia. On Monday 4/11, he is moderating a session on transmedia at the 2011 NAB Show, the annual media & technology industry conference in Las Vegas, which features a dream team of transmedia experts: Starlight Runner's Jeff Gomez, Red Faction's Danny Bilson, The Ghost Whisperer's Kim Moses, The Walking Dead's Gale Anne Hurd, and Conspiracy for Good's Tim Kring.

https://jobs.colgate.com/colgate/job/Piscataway-Postdoctoral-Research-Scientist-NJ-08854/557566700/

Date: May 9, 2019

Location: Piscataway, NJ, US

Colgate-Palmolive is a leading global consumer products company, tightly focused on Oral Care, Personal Care, Home Care and Pet Nutrition. Colgate sells its products in over 200 countries and territories around the world under such internationally recognized brand names as Colgate, Palmolive, Speed Stick, Lady Speed Stick, Softsoap, Irish Spring, Protex, Sorriso, Kolynos, elmex, Tom’s of Maine, Sanex, Ajax, Axion, Fabuloso, Soupline and Suavitel, as well as Hill’s Science Diet, Hill’s Prescription Diet and Hill’s Ideal Balance.

For more information about Colgate’s global business, visit the Company’s web site at http://www.colgatepalmolive.com. To learn more about Colgate Bright Smiles, Bright Futures® oral health education program, please visit http://www.colgatebsbf.com. To learn more about Hill's and the Hill’s Food, Shelter & Love program please visit hillspet.com. To learn more about Tom’s of Maine  please visit  http://www.tomsofmaine.com.

Location: Piscataway, New Jersey, United States No Relocation Assistance Offered # 73220

Colgate-Palmolive Global Technology Center located in Piscataway, NJ, USA, seeks highly motivated postdoctoral research scientist with an excellent background in research and development of cutting-edge medical diagnostic devices and sensor technologies for next-generation oral and personal care applications.  Candidates with strong background in optical imaging/sensor and mechatronics systems for biomedical applications are preferred. Applicants will work closely with various external collaborators and will spend a significant amount of time to develop and investigate novel sensing and imaging devices and algorithms for next-generation clinical and consumer level applications.

Are you interested in working for Colgate-Palmolive? You can apply to work with us using this online application.  Attach all relevant documents such as a cover letter and resume or CV. Applications received by e-mail are not considered in the selection process.

Become part of our team. We look forward to your application.

Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, ethnicity, age, disability, veteran status, marital status, or any other characteristic protected by law.

I would like to collaborate with other educators/mathematicians/statisticians on an article about different interpretations of and experiences with quantitative reasoning courses across different institutions. I am interested in applications of teaching research (teaching experiments, research cycles, zones of proximal development, etc.) to QR courses. As educators we sometimes forget that we are also teaching researchers, a role that is not always realized but is practiced by default. We design courses and assessment tools, we collect student data, we analyze student feedback and our own designs to adjust our courses to improve the attainment of goals that are set by us, or by our colleagues. More often than not, we might not go the extra few steps to properly formulate our hypotheses, conduct our experiments as scientifically as possible, and organize and publish our work. Most of us have pure mathematics/statistics research interests, and concentrate our research skills and products towards those areas, discounting the research we automatically undertake as educators. I, myself, was only recently made aware of the official framework of teaching research when I took on the role of editor on a soon to be published book on the topic by Bronislaw Czarnocha and Vrunda Prabhu, among other contributors. I have also contributed a chapter in the book describing the Science/Mathematics Interdisciplinary Workshop at Hostos Community College. This workshop was developed jointly by me, Yoel Rodriguez and Francisco Fernandez (also co-authors of the chapter).

The educational philosophy and the institutional structure of Eugenio Maria de Hostos Community College (HCC) is driven by its history, its student population and its overarching mission: Consistent with the mission of The City University of New York (CUNY) to provide access to higher education for all who seek it, Eugenio María de Hostos Community College was established in the South Bronx to meet the higher educational needs of people from this and similar communities who historically have been excluded from higher education. The mission of Eugenio María de Hostos Community College is to offer access to higher education leading to intellectual growth and socio-economic mobility through the development of linguistic, mathematical, technological, and critical thinking proficiencies needed for lifelong learning and for success in a variety of programs including careers, liberal arts, transfer, and those professional programs leading to licensure (Hostos, 2014) The college takes great pride in its historical role in cultivating students from diverse ethnic, racial, cultural and linguistic backgrounds, ― "An integral part of fulfilling its mission is to provide transitional language instruction for all English-as-a-Second-Language learners," as well as a variety of different specialized "education offerings to foster a multicultural environment for all students." (Hostos, 2014) To further advance the college's goal and to foster a rich learning environment, equipping students with necessary tools and affording them accessibility to a wide spectrum of opportunities, HCC, together with some of its senior CUNY college partners, currently offers several joint-degree/dual-admission programs: A.A./B.A in Criminal Justice, jointly with John Jay College, A.S./B.S. in Forensic Science, also jointly with John Jay College, and several A.S./B.E. programs, jointly with City College (CCNY). The latter include degrees in Mechanical, Civil, Chemical, Electrical and Environmental Engineering. Additional joint A.S./B.S. programs, in Chemistry, Earth Science and Biology, are presently being developed in association with Lehman College with the assistance of an NSF grant, and will be available to HCC students soon (Project SEED, 2012). Unlike articulation agreements, the current HCC-CCNY engineering partnerships are jointly registered, dual admission programs designed to meet the licensure guidelines of the Accreditation Board for Engineering and Technology (ABET).

The most common difficulties found among HCC students taking science courses, as is the situation nationwide, are inadequate problem-solving foundations, lack of abstract-analysis skills and a lack of sufficient ability to make connections with previous knowledge, specifically, with concepts in mathematics such as trigonometry, geometric and algebraic operations on vectors, and an adequate understanding of introductory calculus (Zumdahl A266). Some of these students have never taken physics, or any science course, for that matter, during their previous educational endeavours. As a result, by the time they take the course, they often already have come to “dislike” physics, and feel frustrated and discouraged because they do not understand it. Furthermore, even when they understand the concepts, they find it very difficult to solve physics problems because of lack of visualization and critical thinking skills. These could be some of the reasons why many students do not consider science careers as professional options despite the great demand in the United States for potential scientists (AACU 9; Mervis, “NIH Told” 328; Mervis, “NIH Wants” 1119; Rochin and Mello 305), as well as mathematics and science middle school and high school teachers. To address this problem, among others, the Natural Sciences Department and the Mathematics Department, with the help of the Office of Academic Affairs at Hostos, created and began offering the Intersession Science Institute in the winter of 2010. This institute was tailored primarily for students enrolled in one of the four initial Hostos Engineering programs (Civil, Chemical, Electrical and Mechanical), but is open to all students who intend to take a Physics or Chemistry course for their respective degrees.

Here's a link to a partial version of the chapter:

The book, still at the final editing stage, is "the story of the interaction between Teaching-Research and Creativity, both mathematical and pedagogical. Creativity had explicitly been introduced into Teaching-Research NYCity Model by Vrunda Prabhu through the Bisociation theory of Arthur Koestler formulated in his Act of Creation (1964), which was found to correspond to Prabhu’s spontaneous organization of the Learning Environment in her classes of mathematics at the Bronx Community College of CUNY. Bisociation, that is, the creative leap of insight that connects previously unconnected frames of reference, allowing the reality to be experienced in several planes at once – the definition of an Aha moment or the Eureka experience - defines also a bisociative framework that makes bisociation possible. It is the framework composed of at least two unconnected frames of reference. Teaching-Research, the integration of two “habitually unconnected” frames of reference, teaching and research, is therefore such a bisociative framework which particularly strongly promotes pedagogical and mathematical creativity in the classroom. It is fascinating to mention that the same bisociative theory recently became the basis for the Computer Creativity, a new domain in Artificial Intelligence (Berthold, 2012). Collaborative investigations into Human and Computer Creativity based on the bisociation theory promise to be a fascinating “bisociative” endeavour. The story of the book has many interweaving themes, some of them explicit and some of them implicit. The explicit themes are formulated by the guiding theme of each unit and their chapters. The structure and organization of the volume introduces the reader to basic TR ideas ...that are applied to the design of instruction in the context of Creative Learning Environment in the classroom... We apply TR methods to the creation of several learning trajectories in Arithmetic and Algebra... we demonstrate the creative power of different bisociative frameworks through TR collaborations of mathematics with different academic disciplines. [Another unit] discusses different roles of a concept map, a pedagogical conceptual tool, which we found very useful in TR work as manifestly evident throughout the book. We close the book with a unit that reports on and analyses two different Professional Developments of Teacher-Researchers, in Tamil Nadu, India and in Europe, each creating a developmental model of a teacher-researcher adapted to the conditions of teaching and learning.

The implicit themes, on the other hand, crisscross different chapters in different units. One of the central such implicit themes is, of course, the relation between practice and. theory and research results. Many aspects of this relationship are weaved in throughout the book. Application of learning theories to classroom practice, derivation of research hypotheses from pilot teaching-experiments. Special attention was given to the presentation and weaving in the bisociation theory into the basic fabric of mathematics education research and practice The relationship between learning mathematics and learning language has been one of the more pressing themes given that our colleges Hostos CC and Bronx CC are minority colleges. Of course, the themes of creativity, discovery and understanding with related methodological comments reappear freely in many different contexts and chapters. Teachers-researchers are the only ones who can establish fruitful relationships between the theory and research results underlying the approach of Learning Trajectories, the backbone of the curriculum design, and their practical classroom utilization, assessment and refinement. Yet in order to fully use the potential of the teaching-research for classroom activity, teachers need to be awarded the systematic time for reflection (see Chapter 6.2). "

Currently, I am very heavily involved in applying the above theory to the subject of quantitative reasoning and literacy, and am very curious about similar projects that other educators might be undertaking for a collaborative effort on a QRTR theory and practice investigation. I am currently teaching and developing the following courses:

Quantitative Reasoning 1: This course is designed to help students gain an understanding of fundamental numerical and quantitative skills and their application to everyday life. The focus will be on applying basic mathematical concepts to solve real-world problems, and to develop skills in interpreting and working with data in order that students become able to function effectively as professionals and engaged citizens. Topics will include problem-solving and back-of-the-envelope calculations, unit conversions and estimation, percentages and compound interest, linear and other models, data interpretation, analysis and visualization, basic principles of probability, and an introduction to quantitative research and statistics. Another important objective of the course is a clear introduction to and a development of appropriate working knowledge of MS-Excel as well as some of the software’s most common applications in a variety of contexts.

Quantitative Reasoning 2 - Quantitative Research Methods: This course is aimed at developing students’ ability to (i) identify a well-formed data-based research question, (ii) find, analyze and present the relevant quantitative information in support of the pertinent argument, and (iii) to compile all results and construct a sophisticated data analysis project. Building upon QR1’s numerical and quantitative skills, this course will focus on quantitative research methods and skills, including elements of statistical analysis and their application to business and social sciences. Students will develop an ability to identify, understand, and critique primary and secondary research in industry, scholarly, government, and other specialized publications; they will also gain familiarity with the use of large data sets.

The USA is a very powerful country with strong paradigms and curriculum structures that links US university research and professional profiles to the needs of US private corporations and the US government. It seems that Mexico is at risk of adopting US paradigms and priorities of US universities when Mexican universities have great need to research about key Mexican issues as massive poverty, indigenous populations, regional inequalities, food production, health policy, etc. Mexico should be very careful, avoiding a critical adaptation of US science and technology paradigms that are far away from responding to social needs and ethical responsibility.

Why are driverless cars still so rare and what could be done to accelerate their approval process?

I was skeptical when we first started working on self-driving cars because I cannot drive. I worried about its economic viability. I still feel that its high price is currently its sales-limiting factor. Like me, most people seem to subconsciously consider a car and its driver as an imperatively indivisible pair/unit, which is necessary for driving. Jose broke this misconception by telling about horses, who pick up their owner when hearing him/her whistling. This removed the constraint posed by lacking cheap parking space because self-driving cars can park in big free parking lots outside the big crowded cities. This removes the need for tall and expensive parking garages. It allows everyone to ride all the way to the door of any university building regardless how limited parking space may be on campus.

While listening to Jose I inadvertently imagined 100 brand-new completely automated bright colored self-driving cars in front of my house and my mom directing them to the address of their next passenger by clicking on them using SAP software.

This morning I felt unhappy because I could not envision how Design Thinking could lead to new insights. I felt so frustrated since I had no luck in finding any kind of meaningful costumer statistics about our Betty Westcott persona. Since I cannot skim text for keywords on my small laptop screen because my visual field is too small due to me needing too high magnification, I searched for images instead of text, since they tend to much better resemble the proportions of screen dimensions. But all I could find was the highly oversimplified histogram below, which I had already discarded before understanding all of its messages.

📷

I used the following search terms to find it on Google: "american driver population breakdown by age group"

The link for retrieving my search results for the string above is https://images.search.yahoo.com/yhs/search;_ylt=A0LEViNvNVVZNzcAFgEnnIlQ?p=american+driver+population+breakdown+by+age+group&fr=yhs-mozilla-002&fr2=piv-web&hspart=mozilla&hsimp=yhs-002#id=32&iurl=http%3A%2F%2Fwww.fhwa.dot.gov%2Fpublications%2Fpublicroads%2F07nov%2Fimages%2Fbandpic3.gif&action=click

I noticed a roughly normal distribution of the average miles driven per day by the five age groups. I wanted to find out whether the number of miles, which our target persona, i.e. Betty Westcott, would love to drive if she had no limitations, was representative of an average elderly driver. I noticed that 16 years had elapsed since the average number of miles driven per day by each age-group had been conducted. Nevertheless, I proceeded since another group was already presenting while I still had nothing new and exciting to report.

The unexpectedly steep decline in the daily driving average for 65+ year old drivers by at least half when compared to 20-64 aged drivers drew my attention. Why? Are the elderly driving less because they lack desire (i.e. declining driving wants) or because they can't drive as much as they'd like and they were used to? I neglected possible driving-limitations for all four - but the oldest - age-bracket.

Maybe Betty Westcott could help to figure this out. How many miles would Betty drive if she could? That is easy! At least four times the distance between San Francisco and Los Angeles every month for her bimonthly visits or 24 round trips from San Francisco to Los Angeles per year.

What is the distance between San Francisco and Los Angeles and how long does it usually take?

According to http://www.trippy.com/distance/Los-Angeles-to-San-Francisco one way takes 5 hours and 37 minutes for a total distance of 381 miles or 613 kilometers. Betty wants to drive this one-way distance at least four times per month or 48 times per year. This causes her driving-wants to exceed 381 miles * 4 per month = 1,524 miles per month or 48 times 381 miles = 16,288 miles per year.

Who is competing against us?

To cover my bases, I consider all, i.e. plane, train, bus, taxi and Uber. My intention is no longer to develop a solution only for the Betty persona - but instead - I am interested in finding out the commercial viability constraints for any transportation alternatives we could offer to our Betty-like travelers.

According to https://www.google.com/flights/#search;f=SFO;t=LAX;d=2017-07-20;r=2017-07-25;sel=SFOLAX0DL4909,LAXSFO0DL2772;q=cheap+google+flights+to+travel+from+san+francisco+to+Los+Angeles a round trip costs $108. Lets round it up to $110. Lets add $50 to let Betty pay for checking in her suitcase.

Betty could easily find airfare for a round trip for $160. Lets add another $100 for getting from and to the airport. For $260 Betty could see her family. Take that twice per month = $520/month. Take this times 12 months = $6240 per year.

The flight itself takes only about 90 minutes = 1.5 hours. This is less than 1/3rd of the driving time. But one needs to consider extra time for check-in. Betty must report to her airline at least 1.5 hours before departure. This alone increases travel time to at least 3 hours, i.e. more than half of her driving time.

Betty must pass the TSA security-checks and give up control over her possessions. This could raise Betty's risk for losing her valuables most likely due to stealing. This is a serious problem at international airports and flights.

Moreover, Betty needs additional time to travel to and from the airports. She might have to pay for airport parking or taxi.

MegaBus.com is a serious competitor, who I respect very much and with whom I had very positive experiences, because its friendly, accommodating, helpful, efficient and offers bussing the 381 miles between San Francisco and Los Angeles for as few as $10 and up to $41, depending on travel date and time. It only takes 7 hours and 25 minutes for a one-way trip. MegaBus offers plenty of seating space and can accommodate disabled travelers very well despite being much cheaper than Greyhound. But it has no buildings at its stops and transfer centers. That's how it saves money. But since Betty can keep sitting in the same bus for the entire trip without long layovers, there is no objective reason why Betty could not take it. All she needs to do is to sit down at one of its tables. She could take it every weekend and still save money.

There is no bus transfer. Riding the MegaBus is not even taking 2 hours longer than driving by car. Recall that it takes 5 hours 37 minutes by car and 7 hours 25 minutes by MegaBus. What's wrong with taking the bus? One could get a round-trip for as low as $20 when buying tickets well in advance.

I took this red double-decker MegaBus from Little Rock, AR. to present my discoveries at a conference in Atlanta, GA last summer and enjoyed the ride for only $14 one-way. It only took one night with one layover in Memphis. This could ruin everything I explained below unless most people keep refusing considering bussing as a commercially viable alternative to driving. Although we don't seem to consider this alternative here, please keep this competitor in mind before making real-life investment decisions. Its a great alternative for the younger traveler segment.

www.greyhound.com is another alternative for less frequently travel routes but more expensive than MegaBus. I am sorry! Just kidding! I just checked it online. Greyhound seems to have responded to its most fierce competitor, i.e. MegaBus. Its seems to offer one-way trips for as low as $16 and as much as $31, depending on travel date and time. Its travel time varies from as short as 7 hours 35 minutes to as much as 12 hours. No bus transfer is needed. How did Greyhound manage to bus for so much less within less than a year? Why do most people seem to keep driving if bussing is so much cheaper?

Taking the train is another option. The cheapest train tickets I could find for one-way are as low as $59 (see https://tickets.amtrak.com/itd/amtrak). But one needs to switch trains. Most trains seem to be busses run by a train company. The shortest travel time seems to exceed 12 hours. Hence, no option for Betty.

Uber costs more than $500 one way. Carpooling could reduce costs. But Uber seems to be no serious competition for us nor the airlines.

For $520 per month or $6,240 per year Betty could fly and save time compared to driving. The airlines and busses are our most challenging competitors. I am not sure whether we could ever undercut the bus prices.

Betty needs to drive 22.5 hours to visit twice a month. If she flew, it would cost her $520 per month. Hence, Betty would pay no more than $520 / 22.5 hours = $23.15/hour to rent our self-driving car. There is some flaw in this calculation that I am too tired to figure out how to fix. But Betty won't buy our self-driving car if its more expensive than flying.

If Betty would be the sole owner of our self-driving car, she'd use it at least 24 hour per month to see her family. But an average month has 24 hours * 30 days = 720 hours/month.

Lets recap! Betty needs 5.62 hours to drive one way. Since she wants to ride 4 times per month she'd need our car for 5.62 hours * 4 = 22.5 hours per month or for 269.6 hours per year.

But the average month has 24 hours times 30 days = 720 hours/month

The year has 24 hours * 365 days = 6760 hours/year.

So Betty needs at least 22.5 hour/month / 720 hours per month = 0.031 of our car per month

or at least 269.6 hours/year / 6760 hours/year = 0.03 of our car per year.

So we need to provide Betty with at least 4% of our car to see her family. To play it safe lets assume Betty needs our self-driving car for the same time to shop and to get to social events. To make calculations easy and to be on the safe side lets assume Betty needs our car less than 10% of the time. If Betty bought it, our car would stand idle more than 90% of the time. What a waste!

But what if, Betty Westcott would share our self-driving car with 9 additional similar fictitious other Betties on average? This would allow us to serve an average of 10 Betties with a single of our autonomously self-driving cars. This could cut cost by 10 times. Since the car is self-driving, it does not need Betty to get to its next passenger.

Betty can travel 1,524 miles/month by plane for $520. So we cannot charge her more than 1,524/$520 = $0.34/mile.

I am getting confused here! To rent out our car to as many passengers as we possibly can, driving time - but not total driving mileage - seems to count, i.e. not considering fuel and wear and tear on the car to keep it simple. But it seems that we can't use the airfare to calculate the maximum threshold by which we could charge Betty to rent our self-driving car by the hour and still be cheaper than the airline. How can we calculate for how many $/hour we need to bill Betty for riding our self-driving car to cost the same as the airline? If Betty decides to drive slower she'd take longer. This would raise the denominator. But since the airfare is fixed, the ratio of $/hour, above which Betty would prefer the plane over riding our self-driving car, would decline as she slows down her driving. But can it be that as Betty drives slower, she'd be more inclined to take the plane instead of our car? How can her driving speed affect the critical price point above which the plane seems to be cheaper to Better than riding our car? Why does it seem as if we need too charge her fewer Dollars/hour as the driving time between these 2 cities increases? This would imply that traffic jams would cause our return on investment to decline. This does not make sense! But if it does not seem to make sense how can we possibly compare prices between ground and air travel? If the plane gets delayed we'd face the same problem. Now I am confused! It makes sense that if our self-driving car could drive faster, we could rent it out to more Betties per unit time. This would require each Betty to pay less for renting it.

But since driving-speeds vary between cities and interstates, its seems challenging to deduce the maximum hourly car-rent, at which we'd still be cheaper than the airline.

The plane costs Betty $34 cents/mile. But to compare, we'd need to know how many miles our self-driving car can drive in its lifetime.

What is the best way to figure out the number of Betties, who can - on average - share one of our fully remotely controlled autonomously self-driving smart cars, which can be directed to any location without depending on humans sitting inside? Can the Google car be directed remotely or programmed to drive to a destination without having anybody inside while driving? The feature that such an autonomously self-driving smart car can pickup its owner/renter or driver, whose role has changed to passenger, without needing anyone being inside, adds an entirely novel dimension, which can contribute a lot towards enhancing its commercial viability and competitiveness.

Be as it may, if we can use one self-driving car to serve 10 Betties, we'd either have 10 times more money to add new features for Betty, or we could earn 10 times as much by renting it out to different passengers, i.e. each of them resembling one instance of Betty, rather than trying to sell it to a single instance of Betty, i.e. making any instance of Betty the sole car-owner and user.

Although I am feeling too tired to understand the math now, I still understand that the winner will most likely be the company, which succeeds in renting out completely autonomously self-driving cars to passengers just like driverless taxis.

We just need to find out the price for already fully technologically approved traffic-ready completely safe self-driving cars that can be directed like drones from a computer.

If they exist, it should be easy to let passengers rent them on a per-trip-basis like a driverless taxi. Since everyone with this idea could buy such kind of remote-controlled self-driving cars without needing to develop technical expertise the fastest will benefit most. This new market-niche will get over-saturated quickly. This kind of time-sharing will make such kind of fully remote-controlled autonomously self-driving cars at least 10 times more economically viable. This could make such self-driving cars much cheaper than currently dominating traditional driver-dependent cars, which are most familiar to us. Soon we could have more people renting instead of owning their cars. Uber and traditional taxi companies could go out of business very soon since they can no longer compete. The cash flow of airlines, trains, shuttle, bus and other transportation-companies would drastically shrink. If fully automated remotely controlled self-driving cars are already feasible, we could easily extend it to trucks. This would revolutionize the cargo-industry. We no longer need to go shopping because we could order online everything we want the store-owned or rented remote-controlled car to bring to our doorstep. In emergency cases, such kind of cars could be driven remotely by a human, who - like a traditional driver can see everything on his/her computer screen. All these drastic changes could take place in only a few months if the smart car I am envisioning is already technically feasible. But since all of this sounds so simple why is it not already happening without us noticing beforehand? What am I (or are we) missing?

Based on my readings, intuition and experiences, extending the time that the elderly can identify themselves with the independence associated with driving, allowing them to drive longer will treat their depression better than any drugs or hospitalization while potentially costing less than those medical traditional more mainstream interventions for treating depression.

The same goes for jobs because having a meaningful job or at least a hope of getting one outperforms any anti-depressant drugs.

If we can prove this, we could market self-driving car as medical devices and jobs as medical treatment deserving at least the same funding as current medical treatments because of their superior outcome. Since this academy has meaning to me, I could stop taking all my anti-depressant drugs. Despite me stopping to take them I feel much better than I felt before coming here, when I apparently had to take them because I felt lacking realistic chances for ever finding a meaningful job. Therefore, assistance in finding jobs should be funded at the same level as hospitalizations for depression and self-driving cars, which allows to extend the age of save driving, should be funded at the same level as anti-depressant drugs.

If we could prove this, we could market our self-driving cars as medical devices demanding Medicaid funding, and job-finding-assistance-programs like our academy as medical treatment for depression demanding reimbursement by health insurances because its still cheaper and much more useful than hospitalization.

This could cause a long overdue paradigm shift from treating the causes instead of the symptoms of depression.

People need a purpose as much as they need food because without it they'll get sick. If we can show that our self-driving level 4 and soon level 5 cars and our academy reduce healthcare costs while enhancing quality of life, we'd have the chance to spark a trend away from only addressing the physiological symptoms and towards eliminating the true reasons, which are causing depression.

Especially medical interventions for the elderly are limited by how many drugs they can safely tolerate at the same time. Removing anti-depressant drugs from the workload of their aging liver could add another 2 years to their lifespan. This means that shifting from addressing causes instead of symptoms for depression could become the first lifespan-extending intervention that can be proven to work in humans. Many anti-depressant drugs increase the risk for developing age-associated degenerative diseases, such as diabetes or cataract sooner in life.

Many elderly die due to the overwhelmingly many interactions between their drugs. As we reduce them we increase their health- and lifespan as well as quality of life.

Based on what you can find at these links we can decide, which of them to share with our group. I am getting the feeling for needing lots of lobbying based on well analyzed solid data that nobody dares to question.

Driving Life Expectancy of Persons Aged 70 Years and Older in the United States

Depressive Symptoms Among Older Adults Who Do Not Drive: Association With Mobility Resources and Perceived Transportation Barriers

Comment by Thomas Hahn about citation below:

I got this one because its about San Francisco

Citation:

Comments by Thomas Hahn

Just copy-paste including "doi:" and all what follows it, i.e. in case of the citation above you need to copy-paste " doi:10.1080/08959420.2014.854140" into the search box, which you'll see when going to "http://sci-hub.cc/". If you can find the doi, you have good chances for getting access to the PDF file of the full publication.

I am disappointed because all of my readings treat the loss of driving-capabilities in the elderly like an inevitably unavoidable loss, we lack the power to restore because they focus on alternatives to driving instead of developing cars, which can soon do all the driving for us. This might be our chance because it could make our solution stand out from all the other proposed driving-alternatives since they may never restore all the lost independence caused by the gradually declining skills, physiological and cognitive functions needed for save driving with advancing age. Making self-driving cars to take over those declining physiological functions of the elderly is only an intermediate step in striving to fully restore their declining physiological functions by reversing all adverse effects of aging.

If we could use driving to discriminate between long-lived and short-lived cohorts we could discover differences revealing the regulation of the aging process, which could help us to get inspired to try new interventions until we have figured out to reverse our aging clock. This has already been proven to work in bees by changing their casts, i.e. the equivalents of social factors, which doubled the lifespan of short-lived nectar-collecting bees to much longer lived nursing-bees.

Citation:

Comments by Thomas Hahn:

If loosing the option to drive increases depression, then extending the upper age limit for driving is equivalent to a medical treatment delaying the onset of depressive symptoms in the elderly. Therefore, our novel and most likely superior approach to treating depression in the elderly deserves at least the same level of funding as currently standard medical practices. We might benefit from marketing our accessible self-driving car in this way as superior medical alternative. If we had access to only a fraction of the funds currently spend on treating depression in the elderly, our innovation budget would far exceed our wildest dreams beyond all of our most optimistic imaginations combined.

I have developed a lobbying strategy to achieve this. Once I found the right words to explain it concisely I'll share it with you. It may only make sense to our group members, who attended our car-feature brainstorming post-it note session this morning (i.e. Wednesday, July 5th) because it sparked this initially far-fetched seeming but nevertheless potentially highly effective approach to get what we need from the government.

Trust me on that the first company, which succeeds in commercially offering vehicles, which are approved to drive without requiring any human inside it while driving, can get filthy rich quickly, if it can switch to more appropriate and profitable marketing strategies, which require driverless-driving and which can implement them fasted. The boost in profit will be unparalleled but very brief because it is so ridiculously easy.

We should investigate the technology of self-driving tanks because the military has much better funding.

If we are the first company meeting the milestone "to get governmental approval for driverless driving vehicles", which cannot be made without our input, we'd revolutionize driving at least as profoundly as SAP revolutionized optimization of business decision-making process starting with 5 visionary German IBM employees in the 1970s.

First of all there'd be many more shapes for driverless-driving vehicles, which none of us would even call a car anymore.

For example, instead of driving grocery shopping, Betty would prefer to place all items she wants into a virtual basket. The grocery store would then send Betty's purchase to her doorstep using our driverless completely-self-driving vehicle. Since people are no longer required to be present for driving, the delivery vehicle may no longer look like a car, but instead, may lack windows and mirrors. It may only have one instead of four doors to allow for inserting and removing Betty's purchases. It may indeed look like a shopping cart driving down the streets and call Betty's cell phone when it reached her doorstep, i.e. just like a traditional taxi driver informs his/her passenger about waiting for him/her to come outside to hop in the car and start the ride. I am sure Amazon would love this if its cheaper than their delivery drones. So we may soon see lots of boxes of all shapes and sizes on wheels busily delivering goods if we succeed.

Retail would change because the constraints causing the division between retail specialties, such as food, clothes, computers, accessories, phones, office supplies, furniture, tools, washers, fast-food delivery and services, such as dry-cleaning, will cease to exist.

Betty could order a bunch of unrelated items and her self-driving basket optimized for her order would collect all her purchased items from specialized warehouses. This is the future of Amazon, to whom we should be the first one to market a level-five fully governmentally approved self-driving driverless vehicle. This would affect the entire transportation industry because the same technology needed for making fully driver-independent tanks can be used to make driver-independent trucks, trains, ships and any other kind of delivery and passenger-carrying vehicles.

To pressure governmentally controlled regulatory agencies into agreeing to approve such kind of fully driver-independently completely autonomously self-driving vehicles, we might want to consider asking for their approval in rare and exceptional cases because governments tend to avoid decisions with potentially unpredictable outcome. We also need to consider fierce opposition of the driver's unions because the approval of level 5 completely driver-independent self-driving cars will take away most paid driving jobs while only replacing a very small fraction of those jobs in manufacturing new advanced features in our fully driverless autonomous car.

=========== Short discourse for future ==========

Are we the good or the bad guys if we'll take away millions of driving jobs? Can our economy produce winners without losers? Should we focus on losers instead of winners to drive our economy? Does a loosing competitor, who is about to go out of business, deserve at least part of the credit for the innovation, which allowed his winning competitor to take away all of his costumers? Would this innovation have taken place without the loosing competitor? Is being a looser a bad thing? Does our economy not depend on those kinds of losers to remain functional and on them to keep trying again as an indirect mechanism to keep challenging the winner to come up with an even better innovation? What can we do to raise the demand faster than productivity to force unemployment rates to decline? What is the difference between absolute and relative inclusion/exclusion? Does being nice to employees and communities yields more return on investment than being mean and exclusively focusing on making profit only? Can the cooperation replace the political decision-making process and affect policies more efficiently than national governments? SAP is proof-of principle but can we generalize? Should companies instead of universities get governmental funding to train talented high school graduates with exactly the skills they need for their job instead of spending so much money on teaching them hard skills, which they can't apply on their job because nobody can tell, who'll end up hiring them?

The specific needs among different high tech IT- and AI-based employers, such as SAP, who are so highly specialized that they need to develop their own database concepts and software, such has HANA/S4, seems too diverse for possibly being addressed by any university curriculum.

If solving the hiring question before starting with post-secondary education, i.e. deciding on the future employer, it will be much easier to determine what needs to be learned to excel on the job later. Trump wants to cut educational funding. Here is a chance without adversely affecting businesses. Can cooperation take over the moral commitment to research and innovation to improve our lives from academia? Like universities, NSF and NIH, SAP too offers fellowships.

I worked conceptually through these kind of questions over the 4 day July 4th holidays I came to very interesting conclusions that surprised me very much. I am glad to share my thoughts and findings to the questions above with anyone interested.

========== End of this Short Discourse for future ====================

In an article titled "California regulators require self-driving car firms to report when humans had to take over from robot drivers for safety, though Google is giving only select data", which is a little over a year old, Google admitted 272 failures of its driver-independent controls, when the self-driving car asked the driver for help. But Google argues that accidents were avoided only in 13 cases. For details see https://www.theguardian.com/technology/2016/jan/12/google-self-driving-cars-mistakes-data-reports

Our research and business data analysis team brainstormed this to offer modules for each medical conditions, such as heart disease, hypertension, pressure, diabetes, etc.

To understand this I am using an analogy to C#, i.e. a Microsoft programming language I learned in 2010. It has parent and child classes. A child-class has all property of its parent-classes plus some extra specifics. It allows for the instantiation of objects thus makes object-oriented programming possible.

Lets assume a Betty-parent class representing the elderly person facing some driving limitation. Then Betty Westcott would be a specific instance, i.e. object of the Betty class, who refuse to consider taking the bus. But another instance of Betty, e.g. Betty Hahn would love taking busses and trains, because that is what she did all her life.

So lets assume an instance of Betty, i.e. Betty Emergency, whose heart needs to be monitored while driving. If her heart is working she can focus well and has no problem driving for many hours. But her high cholesterol levels put her at high risk for sudden heart attacks. Betty Emergency's car would notice a weakening in the strength of her grip to the steering wheel. If this coincides with alarming changes of her ongoing EKG (heart-rate monitoring) data, the car would try to initiate communication with Betty. If Betty does not respond, it would contact an ambulance helicopter. PJ told about such services but I forgot their exact name. Then a software would calculate the optimal location, where helicopter and car could meet to minimize the time Betty needs to wait for her life-saving treatment. If the point of contact between helicopter and car is on a highway or interstate with much lower risk for accident than inner-city traffic, our level-4 self-driving car would assume the role of an ambulance. It would switch on its blue medical emergency lights and warning sirens to send the same implied message to everyone seeing it; just like any traditional ambulance.

Its implied message is:

"My passenger's life is in danger. There is not much time left to save it. Please yield when I am coming. I may need to violate traffic rules and run a red light to save my passenger's life."

Unlike an ambulance our self-driving car may add to this implied message to everyone seeing it:

"Unlike an ambulance, I don't have a human driver because she is unconscious. To save her life, I must drive without human control. Please forgive my mistakes! Please excuse my errors! I am still considered experimental. Please yield when I am coming to the side of the road until I have met the emergency helicopter halfway."

In a first step we'd only lobby for approval for driverless driving in such extreme cases, in which the government cannot refuse to agree. This will give us the opportunity to identify and eliminate more risk factors for accidents. This will give the public some time to get used to level-5 completely driver-independent autonomously self-driving cars. My hope is that over time this will help to pave the way for government approval for all level-5 driver-independent driverless vehicles in general to drive without requiring any human inside it while driving in all traffic setting.

At least 5% of the population cannot drive because of their visual disabilities but only 10% of them are completely blind. The article titled: " The Blind Community Has High Hopes for Self-Driving Cars" (see https://www.technologyreview.com/s/602555/the-blind-community-has-high-hopes-for-self-driving-cars/) highlights the hope of this group. It was published in "Business Impact" in MIT's Technology review. Strangely, I noticed disproportionably many people with Asperger's, who chose not to drive even though they seem to be easily able to learn it .

Having been inspired by the presentations of all of our groups, I am leaning towards Brian's group approach of a board computer to accommodate as many of Betty's needs as possible for the following reasons:

A board-computer and the features for our Betty-class, which it may control, could easily be installed into most cars on the market. That way we don't need to compete against them because they have more experience in optimizing the self-driving features than we do. So our essential contribution to the self-driving car pie might be the disability-compensating features, which only we can add to their already self-driving cars, in a modular fashion. This is also better to get government funding for the following reasons:

Personal example:

Until 2009, my vocational rehab paid for a new computer to help me compensate for the shortcomings caused by my vision loss and to reduce their adverse effects on my schooling. But in 2009, all PC funding for VR-clients was terminated arguing that every non-disabled student needs a PC for college. That is why from then onwards VR stopped funding computers but remained strong commitment to keep pay for anything extra a client may need to access computers. Under this changed policy VR generously paid for having my visual needs evaluated, to purchase my Zoomtext, JAWS and Dragon Dictate for getting trained in the usage and hotkeys of those programs (i.e. $35/hours for 50 hours total), for two very bright, high-resolution 65-inch external screens to connect to my laptop (i.e. one for home and the other for office).

By the same token governmentally funded agencies may probably never pay for the whole car because even non-handicapped people need to pay for their car but I can envision that they will gladly pay for many features, which will make cars and driving accessible for more people facing challenges in this area. Vocational Rehabilitation Services, i.e. very helpful and open-minded state-agencies, whose state-funding is matched by federal grants, will be one of our best and most interested paying customers for our disability- and driving-inability compensating car features for our Betty class and other user segments. They will be much more open to buy our accessibility-features, which we initially developed for the Betty consumer class, when they feel confident that they are paying not for the regular car - but instead - and according to their mission only for what is needed to better integrate the disabled by helping them in finding meaningful and gainful employment.

There are many low-vision driving programs in America.

Information about some of them can be found by clicking the links below:

So if our new features could take any of the visual burden, especially for those, who cannot meet the minimal visual requirements for the low-vision-driving program in their home state, VR would gladly pay for them; thus raising our accessibility feature-innovation budget tremendously. VR is a powerful stakeholder. We should care about learning and understanding its expectations!

Most elderly people loose their driving ability due to macular degeneration. If living long enough we all get it because every day lots of our photoreceptors in our retina die.

My visual impairment, which is caused by Albinism, and which refers to the lack of melanin, i.e. the brown human pigment needed for tanning and for developing our macular (i.e. the small area of highest vision acuity in the center of our retina), is very similar to macular degeneration, except for that my macular never developed. Therefore, I am more used to having to work around visual challenges using my remaining vision as effectively as I possibly can to make inferences about things, which I cannot see directly, such as faces, signs, prints and mirrors. But unlike people with macular degeneration I don't subjectively perceive my vision as bad when using it because it has never been any better for me.

Despite lacking a macular I can drive my bike safely. I have no more bike accidents than normal sighted people. I feel confident seeing enough for driving around obstacles, such as cars, bikes, pedestrians, poles, holes, branches, cats, dogs, rabbits and squirrels. I can see enough not to run into anything because my peripheral vision is fine. Most visually impaired and legally blind people, who cannot get a license, can still ride a bike safely. What's holding me back from driving a car is that I cannot read signs and that I cannot see in a mirror if someone is behind me. While biking I don't need mirrors to tell how fast a car is approaching me from behind because I can tell this by sound. I noticed this because I suddenly got scared when riding my bike wearing the motorcycle helmet of my friend since I could no longer hear the car-engines clearly behind me.

So if our level-4 self-driving car could read out street signs to me and tell me whether its save to change lanes and turn left, I'd apply for low-vision driving before my VR-case gets closed. My VR would gladly pay for having such features added to my car. Since those features are pretty car-model independent I am much more inclined to advise our manager, Jim Smith, to develop such features independent of any specific car-model because this would make marketing any accessibility-feature to huge governmental-funded clients, such as VR, for full reimbursement much easier than trying to infer how much to bill them if they are an integral and indivisible part of a new SuperCar model, from which they cannot be separated, because our SuperCar alternative model is not designed to be manufactured without them.

Let's strive to offer accessibility features primarily to those, who really need them. In general, vision is more helpful than sound for navigation. But I can imagine many sighted drivers, who'd be at much lower risk of missing their exit if their car would read the names of the city on the signs out aloud to them.

I can even see traffic lights and STOP signs well with my eyes. Except for, that I cannot read any of the letters on the STOP sign because to me it looks like a regular red octagon with a thick white horizontal line in the middle.

If I cannot find signs or traffic lights I can infer what they must say by observing the driving behavior of the other cars on a busy four-way intersection. It almost works as well as seeing the signs or traffic lights although its backwards and not supposed to be that way. I know that reversing cause (i.e. sign or signal light) and effect (cars driving by obeying to them) may sound dangerous and suicidal at the first glance but it seems to work well as long as I am the only one, who is reversing the order of cause and consequences. But if two visually impaired drivers would reach the same intersection at the same time and reverse cause and effect like I often have to, it would raise the risk for serious accidents. However, if our four-level self-driving car could read out the signs aloud to me - or even better - let me know when its my turn, I could drive such a car much saver than I can riding my bike. The main reason why reversing cause and effect works well for me as long as I am the only one doing it is because cars are much bigger and noisier than traffic signs and signal lights.

When biking I cannot deal with electric cars because their sound gets lost between the much louder sound of the gasoline-driven cars. This has caused accidents in the past. That is why I realized that the sooner I can switch to a level-4 self-driving car with accessibility features the safer and better.

I also noticed that almost all the cars, which ever hit me while biking, had drivers older than 60. They all were very sorry. They went out of their way to drive me to the bike shop to pay for repairing my bike without me explicitly asking. They even paid for extra bright flashing powerful lights and bike gear for increasing my visibility in the dark even though I did not have them when they hit me. But while riding with them at night, even I with only 20/200 vision got scared by how late such older driver respond to curbs, medians and trash cans. I felt that despite being legally blind, I could see the curbs and medians sooner than the old driver, who just hit me in the dark on my bike and who gave me a ride to the bike shop to pay for getting my bike fixed. In contrast to macular-degeneration, my night vision is not adversely affected by my visual impairment, because my rods, which are the photoreceptors that can see at dim light, are still fully functional in the peripheral.

This implies that older drivers need sensors and self-driving to avoid hitting curbs, medians, trashcans and bikers while driving when dark. I feel that over time people with macular degeneration subconsciously develop adaptations to compensate for the shortcomings of their vision loss, similar to me reversing cause and effect, which may work surprisingly well as long as they are the only one doing it. But it would be much safer if they could directly see signs and obstacles on their own without having to develop tricks to infer them because they cannot see them anymore. That is why we could lobby DMV to required drivers above 65 to have such kind of safety features.

Hence, the entire low-vision driving market is still wide-open to our solutions. I hope to have shown that there is plenty of funding for vision and navigation enhancing features.

_9S�P�`�

I am looking to do a research project centered around how individual with ADHD and mental illness are stigmatized, biased, and prejudiced against in higher learning institutions. I feel there is a need to address how behavioral aspects of these diagnosis-es are perceived in a negative light and are used against individuals in classrooms, on social media, learning interfaces, and with policies and procedures, that effect learning and employment outcomes.

I believe that most of it can be addressed through designing instruction with Universal designs of learning. And promoting positive ways individuals with the diagnosis of ADHD, bipolar, PTSD and others can become more than just productive members of society but able to contribute to jobs that are related to education, psychology, technology, math, engineering, and science.

There needs to be a shift in our society that addresses why the norm is actually not as conducive to individuals who have certain strengths and abilities in these areas, but are kept out due to how they are perceived or mis- perceived.

SECONDARY SCHOOL TEACHERS’ AND STUDENTS’ PERCEPTIONS OF INTEGRATING MOBILE DEVICES (SMARTPHONES AND TABLET PCS) INTO SCIENCE AND MATHEMATICS INSTRUCTION IN UGANDA.

I have adopted the UTAUT2 model by Venkatesh et al. (2012) as my theoretical framework to review related literature on the perceptions and readiness of secondary school teachers’ and students’ to use smartphones and tablet PCs in the teaching and learning of Science (Physics, Chemistry, Biology, Agriculture) and Mathematics subjects in different parts of the world and compare the situation with that in Uganda. My proposed research model consists of constructs such as Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV), Self-Management Learning (SML) and Behavioral Intention (BI). The Challenges I am grappling with and I kindly request your help on: Whether to continue using the UTAUT2 model by Venkatesh et al. (2012) or to change to the UTAUT model by Venkatesh et al. (2003) since the use of smartphones and tablet PCs in Education is not yet implemented in secondary schools in Uganda. Wondering whether some of the constructs of UTAUT2 model may not seem applicable in the context of my study “middle secondary school teachers and students in Uganda”. I would also like to get a team of experts in the field of mobile technology adoption in secondary schools to help me reach a consensus on the statements I have used in my questionnaires since I am planning to use the Delphi technique as a research method. Thank you so much for your attention and hoping for your kindest consideration.