Tutor Assisted Browser-based Learning Environment for Students

poster abstractTutor Assisted Browser-based Learning Environment for Students (TABLES) is a collaborative online synchronous learning center for math assistance. Our proposed project is intended to recreate a MATH tutor center which provides guidance and assistance to students on mathematics concepts. The TABLES project will provide online access in a collaborative learning environment (through a "table"), moderated by a tutor, who is expert in a particular subject domain. TABLES is built to help students and teachers interact in real-time, which affords them the opportunity for group learning which is critical in a math learning environment. A combination of tutor-based and peer assisted learning strategies help students consistently engage in the concepts and learn faster. Site Observations have provided us with several insights into this proposed design solution. TABLES must consist a student and tutor interface each of which must be specifically designed to re create the experience of a physical learning center. Through the help of queues, a virtual whiteboard and innovative chat sessions we intend to improve collaboration across the student population and facilitate a more holistic experience for all individuals involved. The virtual whiteboard is intended to provide a range of benefits such as cross collaboration across geographical locations which has been shown to improve learning outcomes. In conclusion this proposed project, TABLES has the potential to create a MATH repository for common problems and solutions that would eventually assist all new incoming students that join the learning center. By leveraging the advantages of online synchronous learning environments we propose to create a scalable, reliable and efficient learning environment which is able to connect a diverse variety of students with individual expert tutors. Acknowledgements. Mathematics Assistance Center [MAC] at IUPUI with the guidance of Dr. Kevin Berkopes who supports this research project work under the COMET lab

IUPUI Faculty Mentoring Exchange: A Platform to Seek and Volunteer Mentoring

poster abstractMentoring combines the impact of learning with the human need for social connection; it helps individuals achieve their best potential in a competitive and challenging world. Within educational organizations, people are willing to seek advice on various topics, including teaching, research, service, civic engagement, and mutual concerns. The IUPUI Faculty Mentoring Exchange is an application, which allows, faculty to seek mentoring, or offer to mentor to those who could benefit from their insights, expertise, and experience. The Mentoring Exchange delivers three core functionalities: 1.) Voluntary mentoring, 2.) A way to seek to mentor, and 3.) Establishing a social connection chain among the faculty from diverse departments and locations. Participating in the Mentoring Exchange is entirely voluntary. Users fill out a checklist to describe the types of insights and experience they wish to discuss with a colleague. The Mentoring Exchange will then offer a list of potential mentors who have described themselves as having such insights to offer. Then, it is up to the user to contact any of these colleagues and take it from there. Human-centered design processes were followed to deliver the system: user research, prototyping, implementation and iterative analysis. After observations and contextual inquiry, data was collected for sketching and prototyping. We learned about the types of mentoring faculty wish to seek out. Senior faculties were asked about their willingness to provide mentoring. Currently, we are evaluating what users are searching for with an ongoing collection of data. Next, we plan build intelligent social matchmaking ecosystem using machinelearning algorithm. Our work contributes to the enhancing of mentoring culture and creating social connections within the organization

Mentoring Exchange

This poster describes the progress and lessons learned as a result of newly implemented Faculty Mentoring Program in the Indiana University School of Informatics and Computing

Ayurveda and Modern considerations on Pathogenesis and Prognosis of Diabetes

Prameha is a condition described in traditional Ayurveda texts and this disease associated with other conditions including obesity, stress and other metabolic syndrome. Indulgence in the Nidanas (causes) leads disturbances in Kapha associated with Pitta. The imbalance of Kapha and Pitta increases Kleda in body and these all consequences initiates pathogenesis of Prameha. Modern science described disease as diabetes and mentioned several pathological events associated with disease including disturbed metabolic and hormonal regulations, etc. This article emphasizes ayurveda and modern considerations related to the pathogenesis and prognosis of diabetes

Ayurveda view on Prameha w.s.r. to causes and approaches of Management

Prameha is pathological condition which mainly arises due to the excessive consumption of Madhura, Snigdha, Guru and Picchila Aharas. As per modern view sedentary habits, stress and lack of exercises, etc. are responsible for such types of metabolic disorder. Prameha is related to the diabetes as per the modern science, the disease mainly found in middle aged and elderly population but current life style also increases prevalence amongst young population. Aharaj & Viharaj factors play important role towards the disease pathogenesis including Kam-krodha, Shoka, Chinta and Bhaya, etc. are play vital role towards the disease pathogenesis. This article presented view on prameha W.S.R. to its causes and management

Evaluation of sampling gear for demersal resource surveys

The three demersal trawls evaluated were 38 m HSDT-II, indigenously developed by CIFT for deep sea fishing in Indian EEZ; and two imported designs, viz., 45.6 m Expo model demersal trawl and 50 m fish trawl operated from vessels of FSI and IFP, respectively. Vertical opening at trawl mouth was heighest for 50 m fish trawl (3.2 m), followed by Expo model demersal trawl (2.5 m) and 38 m HSDT-II (2.2 m), due to differences in overall dimensions and design features. Estimate of horizontal opening between otter boards was highest for 38 m HSDT-II probably due to low drag of the gear, followed by 45.6 m and 50 m trawls. Lowest catch per unit effort obtained by 38 m HSDT-II is presumably due to smaller dimensions of the gear, larger codend mesh size and difference in ground rig, in addition to chance factors. However, 38 m HSDT-II scores on several features desirable in demersal sampling gear such as simplicity in design and construction, ease of operation; lower twine surface area and drag; and ground rig suitable for wider range of bottom conditions. Modifications to make it more effective while sampling for crustaceans and small sized finfish components are described

Efficient Goodness‐of‐Fit Tests for the Maxwell–Boltzmann Distribution via Stein‐Type Characterization With Applications to (Un)censored Data

Understanding molecular motion in an ideal gas is fundamental to thermodynamics, yet directly measuring individual molecular velocities remains impractical. The Maxwell-Boltzmann (MB) distribution provides a well-established statistical model for describing the distribution of molecular speeds. In this study, we propose efficient goodness-of-fit tests for the MB distribution with unknown parameters, leveraging a novel fixed-point characterization derived from a Stein-type identity. We derive the asymptotic distribution of the proposed test statistic and establish its consistency against a broad class of alternative distributions. Furthermore, we extend the methodology to handle right-censored data, broadening its applicability to real-world scenarios where incomplete observations are common. The performance of our approach is evaluated through extensive Monte Carlo simulations, and its practical utility is demonstrated with applications to empirical data

Economic Assessment of Biodiesel Production

Biodiesel production as well as consumption in the European nations are augmenting, taking into account the uncertainties connected to fossil fuel reserves and the related natural effects of their use. This biofuel can be generated from numerous oil-rich feedstocks and by using different processing technologies. Therefore, the techno-economic assessment for biodiesel production becomes of high relevance to make critical decisions under uncertainties that are essential for the successful implementation of the process on an industrial scale. The economic aspects of using different triglycerides and non-triglycerides based lipid biomass as well as the processing technologies for biodiesel production are thoroughly discussed and compared in this chapteracceptedVersio