Informatics Publishing Limited

M. Nirmala ¹, A. M. Uma Devi ¹

Affiliations
1 Canara Bank School of Management Studies, Central College Campus, Bangalore University, Bangalore, Karnataka, IN

Abstract

Human resource is the most precious resource for every business in comparison to other resources like money, material, and technology as it cannot be replicated. Human capital is the only asset involved in all the operations of the enterprise right from the manufacture of goods to delivery to the consumer. Enterprises have realised the significance of this resource and have started investing huge amounts of their budget to develop this resource. These investments will be rewarding only if the human resources are properly managed and effectively utilised. This paper is an attempt to further such investigations. In this paper the researcher intends to investigate the HRM practices in the following three areas: 1. Change Management-developing an adaptable workforce, 2. Innovation and Learning, and 3. Global Integration, in select Indian and foreign companies and whether the nature of firm ownership has an influence on the HRM practice. This paper is aimed at a comparative study of the HR practices in foreign owned and domestic companies in India that address the HR preparedness of these companies in facing the challenges listed above. The outcome of the study would help the organisations to learn from each other's strengths and weaknesses and develop on them.

Keywords

HRM Practices, Firm Ownership, Competitive Advantage, FDI, Country of Origin.

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M. Nirmala ¹, V. Palanisamy ¹

Affiliations
1 INFO Institute of Engineering, Coimbatore, IN

Abstract

The most significant tasks in data mining are the process of discovering frequent item sets and association rules. Numerous efficient algorithms are available in the literature for mining frequent item sets and association rules. The time required for generating frequent item sets plays an important role. Some algorithms are designed, considering only the time factor. Incorporating utility considerations in data mining tasks is gaining popularity in recent years. Our study includes depth analysis of algorithms and discusses some problems of generating frequent item sets from the algorithm. The time of execution for each data set is also well analyzed. The work yields a detailed analysis of the algorithms to elucidate the performance with standard dataset like Adult, Mushroom etc. The comparative study of algorithms includes aspects like different support values, size of transactions and different datasets.

Keywords

Data Mining, FP Growth, Frequent Item Set Mining, Mushroom.

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M. Nirmala ¹, Pratima Pandey ¹

Affiliations
1 CBSMS, Bangalore University, IN

Abstract

In contemporary times, the influence of technology has made the world a global village. Advanced means of communication and transportation has reduced the distance of miles into few hours/minutes. The advent of computers and internet has its significant impact on every aspect of society. Today the business world cannot survive without technology. This paper tries to explore and study in an empirical way, the impact of technology on contemporary practices of HR and its role in enhancing the organizational effectiveness.

Keywords

Technology, Human Resource, Organizational Effectiveness.

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S. Kannan ¹, G. Hema Dharshini ¹, R. Ishwarya ¹, K. Lakshmipriya ¹, M. Nirmala ¹

Affiliations
1 Department of EEE, Ramco Institute of Technology, Rajapalayam, IN

Abstract

The usefulness of most high technology devices such as cell phones, computers, and sensors is limited by the storage capacity of batteries. .In the future, these limitations will become more pronounced as the demand for wireless power outpaces battery development which is already nearly optimized. We need to develop electricity generating techniques with the help of wasted human energy which is in the form of mechanical pressure and vibration for our better future .Thus, new power generation techniques are required for the next generation of wearable computers, wireless sensors, and autonomous systems to be feasible. Nano generators are excellent power generation devices because of their ability to couple mechanical and electrical properties. For example, when an electric field is applied to Nano sheets a strain is generated and the material is deformed. Consequently, when a Nano sheets is strained it produces an electric field; therefore, Nano generators can convert ambient vibration into electrical power. Piezoelectric materials have long been used as sensors and actuators; however their use as electrical generators is less established. A piezoelectric power generator has great potential for some remote applications such as in vivo sensors, embedded MEMS devices, and distributed networking. Developing piezoelectric Nano generators is challenging. Piezoelectric properties are controlled/tuned by externally applied force/pressure, such as diode, strain sensor and strain-gated logic unites, which are a new field called piezotronics. Our paper presents a practical analysis to increase the power generation using Nano generators.

Keywords

Nano Generator, Mechanical Stress, Power Generation, Piezotronics.

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M. Nirmala ¹, V. Saravanan ²

Affiliations
1 Department of Computer Applications, Hindusthan College of Engineering and Technology, IN
2 Department of Information Technology, Hindusthan College of Arts and Science, IN

Abstract

Natural disasters are utmost incidents inside the earth's system that lead to sudden demise or bruise to humans, and destruction of precious materials, involving buildings, conveyance systems, farming land, forest and natural environment. Occurrences of economic losses due to natural disasters have resulted owing to the escalated susceptibility of the society globally and also due to weather-related disasters. Satellite image sensing remains the hypothetical instrument for disaster management as it provides information spanning wide-reaching areas and also at short time period. In this work we plan to develop a method called, Enhanced Frost Filter and Tanimoto Similarity Classification (EFF-TSC) for efficient disaster management using satellite images is proposed. The EFF-TSC method for disaster management is split into three steps. They are pre-processing, segmentation and classification. With the input image collected from satellite image database, first preprocessing is performed to preserve important features at the edges and remove the noisy pixel by means of an Enhanced Frost Filter Preprocessing model. Second, to the pre-processed satellite image, Threshold Pixel Segmentation is applied to partition into multiple segments. Finally, to the partitioned images, Tanimoto Similarity Classification is applied to classify the segmented image into two types, namely disastrous image and non-disastrous image. With this, an efficient disaster management is carried out with better accuracy and minimal time consumption. The application of the study is demonstrated using the Disaster image data set collected from Kaggle during the 2017. The results show the capability of the proposed EFF-TSC method for disaster management across time and space from different images with considerable accuracy by also reducing peak signal to noise ratio with considerable time. The findings also suggest that the potential for forensic analysis of disasters using pixel segmentation and classification based on collected images can be utilized to several locations affected by disasters.

Keywords

Disaster Management, Frost Filter, Threshold Pixel Segmentation, Tanimoto Similarity Classification, Satellite Image.

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