TCI College of Technology

The interest in two-dimensional (2D) carbon allotropes arises from their ability to alter their properties based on the atomic topology employed, which can significantly affect their electronic properties and benefit advancements in new technologies. This work presents a new nanoporous graphene (NPG) allotrope obtained through lateral heterojunctions via pairs of trivalent sp2 carbon atoms of armchair graphene nanoribbons (AGNRs). These pairs were used as linkers between AGNRs to achieve this structure, forming connections that enhance the porous architecture. This novel planar and porous 2D carbon allotrope integrates some structural and electronic advantages of AGNRs into a 2D framework. Composed of 3-, 6-, and 12-membered carbon rings, the NPG was investigated using density functional theory (DFT) calculations and ab initio (AIMD) and classical molecular dynamics (CMD) simulations to explore its structural, electronic, and mechanical properties. Among the results presented, we show that the material demonstrates high dynamical and thermal stability at 1000 K. Furthermore, the NPG exhibits metallic and nonmagnetic behavior and is achieved by transitioning from the semiconducting nature of some AGNRs to a metallic 2D carbon system. The elastic properties reveal the material's distinct response to applied strain, with fractures occurring in the nanoribbon segment along the x-direction. However, fractures are observed in the C-C bonds involved in the heterojunction region in the y-direction. The calculated Young's modulus ranges from 394 to 690 GPa, which is lower but comparable to graphene. The formation energy of NPG decreases with increasing width of the AGNRs used to compose the 2D material, indicating enhanced stability for wider nanoribbons. These findings highlight the potential of NPG for applications in nanoelectronics and advanced new technologies.

In many real-world scenarios, decision making is crucial especially under uncertainty. Such environments require appropriate models to evaluate the data effectively. One such task is assessing how closely stakeholder's opinions or judgements align with the ideal or actual values. To address this, we suggest a prototype using soft similarity measures between two soft sets for making decisions. We define various soft similarity measures in relation to a reference soft set (ℱ, P)and analyze properties of these measures like monotonicity, sub additivity and additivity. We introduce concepts such as Pseudo signed soft similarity measures, Pseudo positive soft sets, Pseudo negative soft sets and soft integral. We applied this framework to the problem of selecting a reliable stock market analyst by comparing analyst's predictions with actual data across multiple trails. The result showed that the method effectively identified the most consistent analyst. This approach offers a flexible and functional procedure for making decisions in the contexts of uncertainty where human judgement is the key factor.

An equity analyst’s opinion of stocks summarizes how a variety of different forces (such as geopolitical, macroeconomic, country, industry, and company-specific) and their interaction may affect the future performance of a company. In this article, we constructed an analyst-sentiment factor that tracks changes in analyst expectations, and then examined its relationship with global equity performance. We also sought to define the analyst-sentiment factor and learn about its stability and performance. Our analysis revealed that analyst sentiment has been a robust and differentiated investment factor with strong associated risk premiums. It exhibited unique characteristics and information relative to traditional equity style factors such as value, quality, and momentum.

Abstract This paper describes the challenge of Teaching Critical Thinking to a class of physics students at TCI, The College for Technology in the fall semester of 2000. Besides achieving its goal of helping students to think critically, teaching critical thinking provides fun and students find it quite rewarding. Students are encouraged to work on creativity throughout the semester, in class, in laboratory experiments, on homework problems and in the creation of examinations.

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Initiating Interdisciplinary Projects: Finding Common Ground Gil Laware, Beverly Davis, and Karl Perusich Purdue University, College of Technology, 1733 Northside Blvd. South Bend, IN 46634 Abstract Successful approaches to interdisciplinary projects depend on several key components. The first and foremost is to recognize commonality in purpose. In an educational setting, that is the student. As colleagues at a prominent university, we have been encouraged by the president of our university and the dean of our college to work collaboratively across our disciplines. Most of the interdisciplinary projects and scholarly activities undertaken by the authors cooperatively have involved supporting the educational mission of our institution. In fact, some of our more research-oriented projects have their roots in teaching techniques and instructional problems. And more importunately, successful and meaningful interdisciplinary collaboration cumulatively benefits students in the classroom. A second key component of interdisciplinary collaboration is to let go of rigidity of thought and process and find common ground. Lastly, a key component is institutional support. Institutional leadership should not only recognize but encourage interdisciplinary cooperation. In this paper, the authors review the strategies and rationales they have used in interdisciplinary activities. With creativity and a disciplined focus, the authors have found common ground in collaboration and objectives across disciplines. Although not always “politically” easy, an interdisciplinary approach to teaching and scholarship has often been preferable to other alternatives, and, in some cases, necessitated by circumstances. Recommendations will be shared for new faculty so their transition toward interdisciplinary collaborations will be successful. Introduction Interdisciplinary collaborations have become a way of life and are flourishing, leaving behind the isolated disciplinary silos that have characterized many academic campuses in the past [3]. Current research supports the efficacy of student active learning approaches within the context of the traditional lecture/lab classroom structure. Problem-based learning, problem-centered learning, experiential learning, cooperative team learning and service learning share common attributes that foster learning behaviors and outcomes consistent with learning objectives. Problem-based learning (PBL) stimulates engagement and learning by presenting students with complex problems. PBL can also share qualities with experiential, service and cooperative learning. Designing open-ended, directed problems for small groups of students with the intent to produce solutions that benefit real life people and institutions can be a powerful pedagogical construction. Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright © 2005, American Society for Engineering Education

This paper presents a new approach for optimal placement of Distributed Generators (DGs) utilizing a generic multi-objective performance function considering dynamic relevance (weight) factors and various levels of the DG penetration. The suggested approach can place the fixed size as well as the variable size of multiple DGs in single or multiple stage(s), considering any type of load model. The technical performance of the system, with the dynamic relevance factors is found to be better than with the fixed relevance factors approach. The effect of considering system constraints on the DG size and its location has been studied. A look up table approach is also suggested to place the DG at locations other than the most optimal one. The impact of the DG placement on the system voltage profile and line loss has also been investigated on 33-bus and 41-bus (Indian system) distribution systems. The critical cases with extreme DG output power and distribution load demand are simulated on these systems to study the technical viability of the DG planning under such circumstances.

This article reviews the active management opportunity in different market segments, and discusses the role of very active mandates across segments in a core–satellite portfolio structure. Research based on manager performance data over the last 10 years indicates that there is little evidence that average emerging market or small-cap managers have produced higher or more persistent risk-adjusted returns relative to their developed market large-cap peers. Therefore, institutional investors may consider active and passive management as complementary strategies across all equity segments. Due to the outperformance of high active risk mandates over the analyzed period, a simulated core–satellite structure across different equity segments achieved a higher information ratio than a combination of low active risk managers. The outperformance of high active risk mandates may reflect links between higher manager skill, higher investment conviction, and/or fewer constraints. Depending on investment beliefs, institutional investors might explore such a core–satellite structure to implement the global equity allocation.

Knowledge of spatial and temporal patterns of groundwater levels is useful to evaluate efficacy of existing groundwater monitoring network. Present study demonstrates application of graphical and multivariate statistical techniques to evaluate monitoring network of 50 sites in hard-rock aquifers of Ahar River catchment of Udaipur, Rajasthan. The graphical analysis included plotting of time plots and box-whisker plots for monthly groundwater levels for three years (May 2006-July 2009). The result revealed that temporal pattern of the groundwater level was almost similar for majority of the sites. Box-whisker plots revealed that the spatial variations of the groundwater levels were smaller in post-monsoon compared to that in the pre-monsoon season. Furthermore, principal component analysis (PCA) of the groundwater levels revealed that the first two principal components (PC) characterized as ‘hydraulic connectivity factor’ and ‘rainfall factor’ explained more than 75% of the total variance. Based on the PCA, the monitoring sites were classified into five groups according to behavior or