Data-driven time-frequency analysis of multivariate data

Empirical Mode Decomposition (EMD) is a data-driven method for the decomposition and time-frequency analysis of real world nonstationary signals. Its main advantages over other time-frequency methods are its locality, data-driven nature, multiresolution-based decomposition, higher time-frequency resolution and its ability to capture oscillation of any type (nonharmonic signals). These properties have made EMD a viable tool for real world nonstationary data analysis. Recent advances in sensor and data acquisition technologies have brought to light new classes of signals containing typically several data channels. Currently, such signals are almost invariably processed channel-wise, which is suboptimal. It is, therefore, imperative to design multivariate extensions of the existing nonlinear and nonstationary analysis algorithms as they are expected to give more insight into the dynamics and the interdependence between multiple channels of such signals. To this end, this thesis presents multivariate extensions of the empirical mode de- composition algorithm and illustrates their advantages with regards to multivariate non- stationary data analysis. Some important properties of such extensions are also explored, including their ability to exhibit wavelet-like dyadic filter bank structures for white Gaussian noise (WGN), and their capacity to align similar oscillatory modes from multiple data channels. Owing to the generality of the proposed methods, an improved multi- variate EMD-based algorithm is introduced which solves some inherent problems in the original EMD algorithm. Finally, to demonstrate the potential of the proposed methods, simulations on the fusion of multiple real world signals (wind, images and inertial body motion data) support the analysis

Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis

We propose a generic multivariate extension of detrended fluctuation analysis (DFA) that incorporates interchannel dependencies within input multichannel data to perform its long-range correlation analysis. We next demonstrate the utility of the proposed method within multivariate signal denoising problem. Particularly, our denosing approach first obtains data driven multiscale signal representation via multivariate variational mode decomposition (MVMD) method. Then, proposed multivariate extension of DFA (MDFA) is used to reject the predominantly noisy modes based on their randomness scores. The denoised signal is reconstructed using the remaining multichannel modes albeit after removal of the noise traces using the principal component analysis (PCA). The utility of our denoising method is demonstrated on a wide range of synthetic and real life signals

Data-driven Signal Decomposition Approaches: A Comparative Analysis

Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent amplitude- and frequency-modulated components. This represents an important preprocessing step in many practical signal processing pipelines, providing useful knowledge and insight into the data and relevant underlying system(s) while also facilitating tasks such as noise or artefact removal and feature extraction. The popular SD methods are mostly data-driven, striving to obtain inherent well-behaved signal components without making many prior assumptions on input data. Among those methods include empirical mode decomposition (EMD) and variants, variational mode decomposition (VMD) and variants, synchrosqueezed transform (SST) and variants and sliding singular spectrum analysis (SSA). With the increasing popularity and utility of these methods in wide-ranging application, it is imperative to gain a better understanding and insight into the operation of these algorithms, evaluate their accuracy with and without noise in input data and gauge their sensitivity against algorithmic parameter changes. In this work, we achieve those tasks through extensive experiments involving carefully designed synthetic and real-life signals. Based on our experimental observations, we comment on the pros and cons of the considered SD algorithms as well as highlighting the best practices, in terms of parameter selection, for the their successful operation. The SD algorithms for both single- and multi-channel (multivariate) data fall within the scope of our work. For multivariate signals, we evaluate the performance of the popular algorithms in terms of fulfilling the mode-alignment property, especially in the presence of noise.Comment: Resubmission with changes in the reference lis

IMPACT OF SERVICE QUALITY ON CUSTOMER SATISFACTION: EVIDENCES FROM THE RESTAURANT INDUSTRY IN PAKISTAN

The purpose of this study is to contribute to the literature of service quality importance in restaurant industry. The study has been based upon the Servqual technique and Dineserv tool of improving the quality by the service providing organizations. The study is undertaken from the perspective of Pakistani Restaurant Industry and the customers' perceptions vis-à-vis restaurant dining. Two variables of Servqual, i.e. Tangibles and Responsiveness, have been examined to demonstrate the significance of service quality on customer satisfaction. The results endorse the importance of enhanced complementary service standards in restaurant industry. Finally, the findings provide an insight for the Pakistani restaurant service providing establishments and suggestion have been made for the caretakers of the industry on ways to improve service quality.marketing; restaurants; servqual; customer satisfaction

IS JHRM Style Can Be Effectively Implemented In Developing Nations of ASIA (The Case of five Pakistan, Bangladesh, Afghanistan, Nepal, Vietnam,)

In this research work Impact of JHRM Japanese Human recourse Management practices were trying to implement on different countries among developing nation in Asian continent. The countries for this research study were Pakistan, Afghanistan .Nepal, Vietnam, and Bangladesh. The reason for selecting these countries among Asian continent is because of their response rate, information in hand from different sources, and most importantly their ranking among developing nation as well as their importance to international community. As all of the above mention countries facing serious threat on its national as well as international front in order to solve these problem we are trying to evaluate the importance of HR from Japanese prospective as the same circumstances were there before WWII but when there concentrate on their HR Japanese become the leading country for other nations. For this purpose we select 20 firms from each countries and data was collected through published material as well as their HDI and HR departments. In order to get more comprehensive data .A well designed questioners was sent to respective department via email. The main concept was derived from (JSM) and it is implemented to all the above mention countries.Chai square test was used for testing the hypothesis. The result shows different attributes after analyzing the data in all of the above mention countries. As in case of Afghanistan, Pakistan and Bangladesh the major problems in order to implement these JHRM practices  was bureaucratic nature of government, centralized government, top to down decision making style, and institutiolized corruption are the major problem in way of implanting JHRM style. While in case of Vietnam, Bangladesh when JHRM important feature regarding Quality was investigated the results shows that although there is great desire to implement it but the main problem is lack of knowledge and no training & development concept in this regard. Hence from the current research we can conclude that although there is a chance to implement JHRM style in these developing countries but first of all we should removed all the barriers in its effectiveness. Key words; JHRM, Developing nations, Quality, Human Recourse, Asian countries

Multi-scale image denoising based on goodness of fit (GOF) tests

A novel image denoising method based on discrete wavelet transform (DWT) and goodness of fit (GOF) statistical tests employing empirical distribution function (EDF) statistics is proposed. We formulate the denoising problem into a hypothesis testing problem with a null hypothesis corresponding to the presence of noise, and alternate hypothesis representing the presence of only desired signal in the image samples being tested. The decision process involves GOF tests, employing statistics based on EDF, being applied directly on multiple image scales obtained from DWT. We evaluate the performance of the proposed method against the state of the art in wavelet image denoising through extensive experiments performed on standard images

Brain controlled human robot interface

This Paper emphasizes on the ever increasing need of better communication medium between a human and a robot in order to control it precisely. Brain Computer Interface (BCI) is the most suitable mean of communication between them, especially for the rehabilitation of disabled people and for accomplishment of sophisticated tasks like surgery, rehabilitation and operations etc. This paper in depth reviews the state of-the-art of BCI systems for robotics which can be named as Brain Robot Interface (BRI). Various BRIs reported in the literature have been presented by categorizing them. The past, present and future of the subject area has been discussed in detail. Finally, the paper comments on contribution of BCI in the area of robotics. © 2012 IEEE

Assessing the Impact of Eucalyptus Plantation on Groundwater Availability in Pakistan

Eucalyptus tree was first planted in Pakistan in the 1980s under the project of Pakistan Forest Institute sponsored by United States Agency for International Development. It is not native to Pakistan's environment, so it has become a threat to the ecosystem. A mature Eucalyptus tree shape is like a shrub or tall tree. It is centered by the number of controversies like allelopathy, loss of soil fertility, the substitution of conventional forests and causing various hydro-ecological imbalances of an ecosystem. Eucalyptus tree consumes three times more water in arid and semi-arid environments, because of vapor pressure deficit. About 80% of Pakistan's area is present in the semi-arid and arid climate. Pakistan is facing a serious water shortage and rapid groundwater level depletion in many parts of the country. It is believed that species of Eucalyptus tree are extracting more groundwater than water recharge. Therefore, the present study is conducted to identify the adverse impacts of Eucalyptus plantation on the groundwater level of Lahore. Six parks in Lahore were selected as study sites, i.e., Gulshan-e-Iqbal Park, Bagh-e-Jinnah, Jillani Park, Nawaz Sharif Park, Jallo Park, and Johar Town Park. A total of 3,484 Eucalyptus trees were identified with different age groups. These trees belong to the species of Eucalyptus camaldulensis, Eucalyptus citriodora and Eucalyptus sideroxylone. The study reveals that since 1990, the groundwater level has significantly reduced in study sites. It is recommended that Eucalyptus trees may be replaced with other indigenous species so that the rate of groundwater depletion can be slowed down