Dissemination Strategies for Higher Educational Institutions for Geo-Social Necessities: A Synergic Model

Higher education institutions (HEIs) are expected to be established in conjunction with the specificities of the regions to which they are supposed to belong. But over the years, the regional necessities based on its resourcefulness and demographic potential are seldom accounted for in their justifiable dissemination across the state. This article analyze (a) whether our HEIs are established by satisfying the needs of its geographical area and (b) whether the programmes offered by them have any mutual benefits to the regional populace and academic community. Various resource diversities are attached with every institution, in the context of contesting components of science and other academic disciplines. This study proposes a synergic model to facilitate the allocation of academic programmes and dissemination of institutions with 10 broad synergic bands, each incorporating various resource potentials available with every geographical niche. A total of 54 government arts and science colleges of the state have been geocoded and tagged with these bands, to find the institutional synergies with their surrounding resources. Although colleges capture synergy points ranging from two to nine, but only a few of the institutions are enriched with higher numbers of bands. The more synergy points the institution captures, the more will be its academic potential in terms of feasibility of programmes in consideration of sustainable development of the locality in which they are situated. This model is therefore an instrument for every institution and to self-evaluate its performance for the societal prosperity of their immediate neighbourhood.

Increase of banks’ credit risks forecasting power by the usage of the set of alternative models

The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of default models give underestimated results. As a result of the assigning of optimal weights and monotonic transformations to these models, the new synergic model of banks’ credit risks with higher forecasting power (predicted 44% of precise estimates) was obtained.

A Novel Idea for Optimizing Condition-Based Maintenance Using Genetic Algorithms and Continuous Event Simulation Techniques

Effective maintenance strategies are of utmost significance for system engineering due to their direct linkage with financial aspects and safety of the plants’ operation. At a point where the state of a system, for instance, level of its deterioration, can be constantly observed, a strategy based on condition-based maintenance (CBM) may be affected; wherein upkeep of the system is done progressively on the premise of monitored state of the system. In this article, a multicomponent framework is considered that is continuously kept under observation. In order to decide an optimal deterioration stage for the said system, Genetic Algorithm (GA) technique has been utilized that figures out when its preventive maintenance should be carried out. The system is configured into a multiobjective problem that is aimed at optimizing the two desired objectives, namely, profitability and accessibility. For the sake of reality, a prognostic model portraying the advancements of deteriorating system has been employed that will be based on utilization of continuous event simulation techniques. In this regard, Monte Carlo (MC) simulation has been shortlisted as it can take into account a wide range of probable options that can help in reducing uncertainty. The inherent benefits proffered by the said simulation technique are fully utilized to display various elements of a deteriorating system working under stressed environment. The proposed synergic model (GA and MC) is considered to be more effective due to the employment of “drop-by-drop approach” that permits successful drive of the related search process with regard to the best optimal solutions.