PSG College of Technology

About: PSG College of Technology is a based out in . It is known for research contribution in the topics: Machining & Thin film. The organization has 3174 authors who have published 3575 publications receiving 40690 citations.

Split-step θ-methods for stochastic age-dependent population equations with Markovian switching

Abstract: In this paper, a class of split-step θ -methods for solving stochastic age-dependent population equations with Markovian switching is constructed. The main aim of this paper is to investigate the convergence of the split-step θ -methods of stochastic age-dependent population equations with Markovian switching. It is proved that the split-step θ -methods converge to the analytical solutions of the equations under given conditions. An example is given for illustration.

Preserving Health Care Data Security and Privacy Using Carmichael's Theorem-Based Homomorphic Encryption and Modified Enhanced Homomorphic Encryption Schemes in Edge Computing Systems.

Abstract: With the tremendous growth of technology, providing data security to critical applications such as smart grid, health care, and military is indispensable. On the other hand, due to the proliferation of external data threats in these applications, the loss incurred is incredibly high. Standard encryption algorithms such as RSA, ElGamal, and ECC facilitate in protecting sensitive data from outside attackers; however, they cannot perform computations on sensitive data while being encrypted. To perform computations and to process encrypted query on encrypted data, various homomorphic encryption (HE) schemes are proposed. Each of the schemes has its own shortcomings either related to performance or with storage that acts as the barrier for applying in real-time applications. With that conception, our objective is to design HE schemes that are simple by design, efficient in performance, and highly unimpeachable against attacks. Our first proposed scheme is based on Carmichael's Theorem, referred to as Carmichael's Theorem-based Homomorphic Encryption (CTHE), and the second is an improved version of Gorti's Enhanced Homomorphic Encryption Scheme, referred to as Modified Enhanced Homomorphic Encryption (MEHE). For brevity, the schemes are referred to as CTHE and MEHE. Both the schemes are provably secure under the hardness of integer factorization, discrete logarithm, and quadratic residuosity problems. To reduce the noise in these schemes, the modulus switching method is adopted and proved theoretically. The schemes' efficiency is proven by collecting the data from cardiovascular dataset (statically)/blood pressure monitor (dynamically) and is homomorphically encrypted in the edge server. Further analysis on encrypted data is carried out to identify whether a person has hypotension or hypertension with the aid of parameters, namely, mean arterial pressure. As the schemes are probabilistic in nature, breaking the schemes by a polynomial time adversary is impossible and is proven in the article.

A Survey on Ontology Evaluation Tools

Abstract: Ontologies play an important role for the semantic web which aims at capturing domain knowledge and provide a commonly agreed understanding of a domain, which may be reused and shared across applications and groups. Developing and deploying large-scale ontology solutions typically involves several separate tasks and requires applying multiple tools. Different tools from different sources need to inter operate and are integrated into frameworks. These frameworks must be open to other commercial environments and provide connectors and interfaces to industrial standards. In this paper we propose an evaluation framework for properties of ontologies and technologies for developing and deploying ontologies.

Development and investigations of kapok fiber based needle punched nonwoven as eco-friendly oil sorbent

Abstract: In this work an attempt has been made to produce kapok/polypropylene (80/20) needle punched nonwoven for oil spill clean-up process. The difficulties involved in structuring kapok fiber through nee...

A hierarchical heterogeneous ant colony optimization based approach for efficient action rule mining

Abstract: Most data mining algorithms aim at discovering customer models and classification of customer profiles. Application of these data mining techniques to industrial problems such as customer relationship management helps in classification of customers with respect to their status. The mined information does not suggest any action that would result in reclassification of customer profile. Such actions would be useful to maximize the objective function, for instance, the net profit or minimizing the cost. These actions provide hints to a business user regarding the attributes that have to be changed to reclassify the customers from an undesirable class (e.g. disloyal) to the desired class (e.g. loyal). This paper proposes a novel algorithm called Hierarchical Heterogeneous Ant Colony Optimization based Action Rule Mining (HHACOARM) algorithm to generate action rules. The algorithm has been developed considering the resource constraints. The algorithm has ant agents at different levels in the hierarchy to identify the flexible attributes whose values need to be changed to mine action rules. The advantage of HHACOARM algorithm is that it generates optimal number of minimal cost action rules. HHACOARM algorithm does not generate invalid rules. Also, the computational complexity of HHACOARM algorithm is less compared to the existing action rule mining methods.