Search results

Si-based micro electro mechanical systems (MEMS) magnetometer does not require specialized magnetic materials avoiding magnetic hysteresis, ease in fabrication and low power consumption. It can be fabricated using the same processes used for gyroscope and accelerometer fabrication. The paper reports the dicing mechanism for the released MEMS xylophone magnetic sensor fabricated using wafer bonding technology and its characterization in ambient pressure and under vacuum conditions. The purpose of this paper is to dice the wafer bonded Si-magnetometer in a cost-effective way without the use of laser dicing and test it for Lorentz force transduction.

A xylophone bar MEMS magnetometer using Lorentz force transduction is developed. The fabricated MEMS-based xylophone bars in literature are approximately 500 µm. The present work shows the released structure (L = 592 µm) fabricated by anodic bonding technique using conducting Si as the structural layer and tested for Lorentz force transduction. The microstructures fabricated at the wafer level are released. Dicing these released structures using conventional diamond blade dicing may damage the structures and reduce the yield. To avoid the problem, positive photoresist S1813 was filled before dicing. The dicing of the wafer, filled with photoresist and later removal of photoresist post dicing, is proposed.

The devices realized are stiction free and straight. The dynamic measurements are done using laser Doppler vibrometer to verify the released structure and test its functionality for Lorentz force transduction. The magnetic field is applied using a permanent magnet and Helmholtz coil. Two sensors with quality factors 70 and 238 are tested with resonant frequency 112.38 kHz and 114.38 kHz, respectively. The sensor D2, with Q as 238, shows a mechanical sensitivity of 500 pm/Gauss and theoretical Brownian noise-limited resolution of 53 nT/vHz.

The methodology and the study will help develop Lorentz force–based MEMS magnetometers such that stiction-free structures are released using wet etch after the mechanical dicing.

There has been a lot of research on how to set marketing budgets, but the overlooked aspect was how allocating funds influences business performance in a multi-goal context. This study aims to examine the relationship between business performance, the process of allocating funds to multiple goals and the interaction among the goals.

Ratio data were generated through “a constant sum scale” from a sample of 362 managers from the B2C sector, besides data on after-tax revenue for two years. The data file was created. Then, a factor analysis was performed on the data. Furthermore, an econometric model with interaction terms was fitted to the data.

The results show that allocating funds to multiple marketing goals – demand generation, customer experience, brand image, marketing competency and purchase intention – influences business performance. Furthermore, a goal’s impact on business performance is higher when coupled with other goals than in isolation.

The findings of the study should assist managers in increasing revenue while spending less on marketing and shifting funds from less efficient goals and pairs of goals to highly efficient ones.

By extending the relevant theory on the relationship between the process of marketing fund allocation, multiple goals and business performance, this study contributes to the literature on marketing.

The impact of COVID-19 has caused a recession in economies all over the world. In this context, the current study aims to analyze the prevailing economic scenario using a machine learning approach and suggest sustainable measures to recover the global economy taking the case of Make in India (MII) initiative of developing the economy as a base for the study.

A well-known topic modeling technique – Latent Dirichlet allocation (LDA) algorithm has been employed to extract useful information characterizing the existing state of selected sectors under the MII initiative alongside catalytic policies that have been implemented for the same. The textual data acts as the base of the study upon which suggestions are provided.

The findings obtained suggest that digital transformation will play a key role in concerned sectors to optimize the performance of manufacturing organizations. Additionally, inter-relationship between Key Performance Indicators for the economy's revival is crucial for effective utilization of foreign direct investment resources.

The novel efforts to utilize MII initiative as a case present crucial information which can be used by policy makers and various other stakeholders across the globe to enhance decision-making and draft legislation across different sectors to empower the economy.

The study presents a novel approach to utilize the MII initiative by identifying important measures for crucial sectors and associated policies that have been presented by employing a text mining approach which in itself makes it unique in its contribution to research literature.