Experiential learning through a real and live case study model

Experiential learning is active learning process mainly through reflection and analysis. Experiential Learning Theory (ELT) provides a holistic model of the learning process and is a multi-linear model of adult development, both of which are consistent with what we know about how we naturally learn, grow, and develop. The theory is called Experiential Learning to emphasize the central role that experience plays in the learning process. The way I integrated experiential learning through a real and a live case study model as part of fulfillment for our Capstone Strategy class is as follows: 1. 6 weeks of student consulting cell as a part of fulfilling the requirement of their undergraduate capstone project on advanced global strategy course 2. Reported to the corporation\u27s middle manager on project progress on a weekly basis 3. Presented to the top management in the form of a presentation and a detailed written report on the strategic nature of the project at the end 4. Integration of theories to the live and real-time case model. The conclusions and the goals achieved are discussed during the presentation

O(d, d) invarijantno rješenje prostorno-vremenski ovisnih vakuuma struna

We solve the O(d, d) invariant equation of motions for string vacua for v(ϕ) of the form v(ϕ) = −B0e −αϕ.Riješena je O(d, d) invarijantna jednadžba gibanja za vakuume struna za v(ϕ) oblika v(ϕ) = −Be −αϕ

O(d, d) invarijantno rješenje prostorno-vremenski ovisnih vakuuma struna

We solve the O(d, d) invariant equation of motions for string vacua for v(ϕ) of the form v(ϕ) = −B0e −αϕ.Riješena je O(d, d) invarijantna jednadžba gibanja za vakuume struna za v(ϕ) oblika v(ϕ) = −Be −αϕ

The strategic shift of U.S. firms towards Vietnam at the expense of China: A business system analysis

In the recent past, Vietnam has dramatically increased its investment relationship and trade with the United States. At the same time, United States foreign direct investment and trade with China has been decreasing. This is even more significant when we are in a period of internal growth within the United States. Using comparative business system analysis theory and a mixed method approach we conclude that Vietnam is turning into the new China for United States firms due to the fewer differences that exist between their business systems. The Chinese business system has major differences when compared with the economic system of the United States, whereas the Vietnam system has closer resemblance to the United States system. We have laid out inferences of our arguments for future research, particularly in the area of institutional comparative advantage

A Comparative Analysis of Application of Genetic Algorithm and Particle Swarm Optimization in Solving Traveling Tournament Problem (TTP)

Traveling Tournament Problem (TTP) has been a major area of research due to its huge application in developing smooth and healthy match schedules in a tournament. The primary objective of a similar problem is to minimize the travel distance for the participating teams. This would incur better quality of the tournament as the players would experience least travel; hence restore better energy level. Besides, there would be a great benefit to the tournament organizers from the economic point of view as well. A well constructed schedule, comprising of diverse combinations of the home and away matches in a round robin tournament would keep the fans more attracted, resulting in turnouts in a large number in the stadiums and a considerable amount of revenue generated from the match tickets. Hence, an optimal solution to the problem is necessary from all respects; although it becomes progressively harder to identify the optimal solution with increasing number of teams. In this work, we have described how to solve the problem using Genetic algorithm and particle swarm optimization

AN OPD BASED PROSPECTIVE EXPLORATORY STUDY OF DERMATOPHYTOSIS - FOCUS ON TREATMENT OUTCOMES, MEDICATION ADHERENCE, AND QUALITY OF LIFE

Objective: The study was planned primarily to judge the effectiveness, safety, and adherence of the prescribed treatments in dermatophytosis along with the effect on the Quality of Life (QoL) of the affected individuals. Methods: In this prospective observational study, spanning over 5 months, participants (dermatophytosis patients) were assessed at baseline and 6 week-follow-up at study site. Information about their clinical presentation, QoL (Quality of Life) parameters, medication adherence, and adverse drug reaction (ADR) were entered in the Case Report Form (CRF) prepared by utilizing global standard tools such as 5D-itch scale, Dermatology Life Quality Index (DLQI), Medication Adherence Rating Scale (MARS), and WHO-ADR reporting form respectively. Results: Total 60 subjects (33 males and 27 females) had completed the study. Overall, tinea cruris (40%) was the most common variety followed by combination of tinea corporis and cruris (35%), tinea corporis (20%), and tinea incognito (3%). Pruritus was the predominant symptom. There was a significant (p<0.001) improvement of both 5D-itch & DLQI scores from baseline to follow-up stage (after 6 weeks). Treatment regimens were well tolerated (only eight subjects reported any adverse event such as gastric irritation and sedation). Medication adherence to the prescribed treatment was good; (mean MARS score 7.588±1.82). Mostly prescribed regimen was a combination of antifungal (oral plus topical) and antihistamine tablet (58/60, 96.66%). The most common drug combination was capsule itraconazole, luliconazole cream, and cetirizine or levocetirizine tablet with or without ketoconazole soap (35/60, 58.33%). Conclusion: Prescribed treatment regimen for dermatophytosis was effective, tolerable, acceptable with high medication adherence and also improved the QoL of the study subjects

Fast and accurate correction of optical mapping data via spaced seeds

Motivation: Optical mapping data is used in many core genomics applications, including structural variation detection, scaffolding assembled contigs and mis-assembly detection. However, the pervasiveness of spurious and deleted cut sites in the raw data, which are called Rmaps, make assembly and alignment of them challenging. Although there exists another method to error correct Rmap data, named cOMet, it is unable to scale to even moderately large sized genomes. The challenge faced in error correction is in determining pairs of Rmaps that originate from the same region of the same genome. Results: We create an efficient method for determining pairs of Rmaps that contain significant overlaps between them. Our method relies on the novel and nontrivial adaption and application of spaced seeds in the context of optical mapping, which allows for spurious and deleted cut sites to be accounted for. We apply our method to detecting and correcting these errors. The resulting error correction method, referred to as Elmeri, improves upon the results of state-of-the-art correction methods but in a fraction of the time. More specifically, cOMet required 9.9 CPU days to error correct Rmap data generated from the human genome, whereas Elmeri required less than 15 CPU hours and improved the quality of the Rmaps by more than four times compared to cOMet.Peer reviewe

Logarithmic corrections to finite size spectrum of SU(N) symmetric quantum chains

We consider SU(N) symmetric one dimensional quantum chains at finite temperature. For such systems the correlation lengths, ground state energy, and excited state energies are investigated in the framework of conformal field theory. The possibility of different types of excited states are discussed. Logarithmic corrections to the ground state energy and different types of excited states in the presence of a marginal opeartor, are calculated. Known results for SU(2) and SU(4) symmetric systems follow from our general formula.Comment: 5 pages, 1 figure; Typos corrected and minor changes made for clarit

Abnormality Detection in ECG Signal applying Poincare and Entropy-based Approaches

Detection of abnormality in heart is of major importance for early and appropriate clinical medication. In this work, we have proposed two models for detection of abnormality in ECG signals. The normal ECG signals are closely repetitive in nature to a large extent, whereas ECG signals with abnormalities tend to differ from cycle to cycle. Hence, repetitive plot like the Poincare is efficient to detect such non-repetitiveness of the signal; thereby, indicating abnormalities. Hence, we have used Poincare plot to develop the two proposed models. One of the models uses direct analysis of the binary image of the plot to detect the difference in retracing, between the healthy and unhealthy samples. The other model uses entropy of the Poincare plot to detect the difference in randomness of plots between the two classes. Most importantly, we have used only lead II ECG signal for analysis. This ensures ease of computation as it uses signal of only a single lead instead of the 12 leads of the complete ECG signal. We have validated the proposed models using ECG signals from the ‘ptb database’. We have observed that the entropy analysis of the Poincare plots gives the best results with 90% accuracy of abnormality detection. This high accuracy of classification, combined with less computational burden enables its practical implementation for the development of a real life abnormality detection schem