Mind mapping management

A mind map is a diagram used to represent words, ideas, tasks, or other items linked to and arranged around a central key word or idea. Mind maps are used to generate, visualize, structure, and classify ideas, and as an aid to studying and organizing information, solving problems, making decisions, and writing. The fundamentals of mind map are arranged naturally according to the importance of the concepts, and are classified into groupings, branches, or areas, with the goal of representing semantic or other connections between portions of information. Mind maps may also aid recall of existing memories. The ideas are documented in a mind map radiate from the center of diagram, similar the branches or root system of a tree. The colors are important because they provide an extra dimension of information to help your brain interpret the data more effectively. The mind mapping technique can be used as a authoritative, creative and dynamic way to administer projects, structure and classify multifaceted information, and provide motivating reports that grasp people’s attention. By minimizing words and focusing on associations, mind maps allow project managers and team members to rapidly see dependencies and problems, saving time and money. Using mind maps can notably improve a project team’s productivity.Mind mapping management

The management learning tool: Andragogy

The name andragogy was first used by a German grammar school teacher named Alexander Kapp in 1833 to portray the educational theory of the Greek philosopher Plato. He used it to refer to the normal process by which adults engage in continuing education. The first use of the term "andragogy" to catch the extensive attention of adult educators was in 1968, when Knowles, then a professor of adult education at Boston University, introduced the term (then spelled "andragogy") through a journal article. Andragogy is an educational theory that utilizes the adult’s life experiences to teach and aid in learning rather than using someone else’s experience in an attempt to teach. Since this is a way of teaching and learning, the principles lend andragogy to be accepted as a theory. Andragogy applies to any form of adult learning and has been used extensively in the design of organizational training programs (especially for "soft skill" domains such as management development). Andragogical methods are best when they can be applied are in community situation and industry/corporate situations that are supportive of a self-directed learner. Human Resource departments should also consider andragogical principals when designing their employee development programs, providing the organization whose management style is one that is represented by McGregor’s Theory Y. By placing a value on training and development, employees will be motivated to learn new skills to help them in their career development.Andragogy, Management learning tool

Continuous supply chain collaboration : Road to achieve operational excellence

Supply chain management (SCM) is becoming critical as firms recognize that competition is shifting from company versus company to supply chain versus supply chain. In the present competitive scenario, the fierce competition has driven most companies to seek means of enhancing performance beyond their four wall boundaries. The firm’s ability in collaborating with its upstream and downstream partners determines its success in attaining better performance with supply chain collaboration; a firm is able to serve fragmented markets in which end customers require more product varieties and availability with shorter product life cycle and at the same time lower supply chain costs. Hence, this paper introduces the framework of continuous supply chain collaboration (CSCC), which extends the traditional frame of reference in strategic sourcing from a supplier centric to a supply-chain-scope as continuous improvement efforts to enhance the customer satisfaction. CSCC practices are rather exceptional, yet CSCC is believed to be the single most comprehensive framework for attaining operational excellence.Continuous supply chain collaboration (CSCC); Supply chain management: Continuous improvement; Operational excellence; Supply Chain Management

A study on occupational health hazards among women beedi rollers in Tamilnadu, India.

The beedi industry occupies a prominent place in rural development in terms of its capacity to offer potential employment opportunities to a large number of people. For the beedi industry Tamilnadu is one of the major hub in India. It is estimated that around one million workers mostly woman and children are employed in Beedi making. It is an ardu¬ous, labour intensive task because each beedi is rolled individually. Beedi industry is almost an unorganized sector hence even the government officials finding it difficult to enforce the various legal requirements. Apart from the other legal implications the health hazards which the women employees who are rolling the beedis are enormous. This study aims to explore the level of health hazards experienced by the woman beedi rollers in Tamilnadu. A total of 388 usable responses obtained from women beedi rollers comprising from the beedi rollers concentrated districts i.e., Tirunelveli, Tuticorin, Tiruchirappalli & Vellore are used for this study. The study found that more than 70% of the beedi rollers suffered from eye, gastrointestinal and nervous problems while more than 50% of the respondents suffered from respiratory problems, mostly throat burning and cough. More than 75% of the respon¬dents faced osteological problems. From the study is it understood that the health hazards level is very high. This study proposes a framework to be implemented with the Government agencies, NGOs and Welfare organizations for the welfare of the beedi rollers.Beedi rollers, Health Hazards, Welfare measures, Tamilnadu.

Quality of work life: Perception of college teachers

Several Research Studies in the world have measured the Quality of Work of Employee’s in Industries, Universities, Schools, Government and Non Government Organizations. This research study highlights the quality of work life of college teachers under various dimensions. New Challenges can be faced with employee’s commitment and involvement in achieving organizational goals. This study helps the college teachers to know the level of perception towards QWL and to enhance the same by the educational administrators.. Quality of Work Life is the essential concept of favorable situations in a working environment. The Quality of Work Life facilitates employee’s training opportunities, job satisfaction and working conditions. A better Quality of Work Life improves the growth of the employee’s along with the organization growth. The universe of the study includes 12 colleges located within the Tiruchirappalli city limit and 1279 college teachers were working during May 2008 – February 2009. A sample of 239 respondents was collected from the universe. The collected data after being coded were analyzed using Statistical Package for Social sciences Research (SPSS) and various statistical tests were applied based on hypotheses and matching variables. There is a significant association between quality of work life total and quality of life in teaching environment total. It shows QWL of college teachers is in low level.Quality of Work Life: College Teachers; Perception

Spoof detection using time-delay shallow neural network and feature switching

Detecting spoofed utterances is a fundamental problem in voice-based biometrics. Spoofing can be performed either by logical accesses like speech synthesis, voice conversion or by physical accesses such as replaying the pre-recorded utterance. Inspired by the state-of-the-art \emph{x}-vector based speaker verification approach, this paper proposes a time-delay shallow neural network (TD-SNN) for spoof detection for both logical and physical access. The novelty of the proposed TD-SNN system vis-a-vis conventional DNN systems is that it can handle variable length utterances during testing. Performance of the proposed TD-SNN systems and the baseline Gaussian mixture models (GMMs) is analyzed on the ASV-spoof-2019 dataset. The performance of the systems is measured in terms of the minimum normalized tandem detection cost function (min-t-DCF). When studied with individual features, the TD-SNN system consistently outperforms the GMM system for physical access. For logical access, GMM surpasses TD-SNN systems for certain individual features. When combined with the decision-level feature switching (DLFS) paradigm, the best TD-SNN system outperforms the best baseline GMM system on evaluation data with a relative improvement of 48.03\% and 49.47\% for both logical and physical access, respectively

Non-Negative Matrix Factorization Based Single Channel Source Separation

The significance of speech recognition systems is widespread, encompassing applications like speech translation, robotics, and security. However, these systems often encounter challenges arising from noise and source mixing during signal acquisition, leading to performance degradation. Addressing this, cutting-edge solutions must effectively incorporate temporal dependencies spanning longer periods than a single time frame. To tackle this issue, this study introduces a novel model employing non-negative matrix factorization (NMF) modelling. This technique harnesses the scattering transform, involving wavelet filters and pyramid scattering, to compute sources and mitigate undesired signals. Once signal estimation is achieved, a source separation algorithm is devised, employing an optimization process grounded in training and testing approaches. By quantifying performance metrics, a comparative analysis is conducted between existing methods and the proposed model. Results indicate the superior performance of the suggested approach, underscored by these metrics. This signifies that the NMF and scattering transform-based model adeptly addresses the challenge of effectively utilizing temporal dependencies spanning more than a single time frame, ultimately enhancing speech recognition system efficacy

Enhancing the Performance of Single-Channel Blind Source Separation by Using ConvTransFormer

In the specialized field of audio signal processing, this study introduces a pioneering ConvTransFormer architecture aimed at enhancing the performance of single-channel blind source separation (SCBSS). This innovative architecture ingeniously combines the strengths of a multiple simple-weak attention mechanism with the triple-gating feature of a Gated Attention Unit (GAU) within the ConvTransFormer. This combination allows for a more focused and effective targeting of specific segments within the input sequence. The efficacy of this ConvTransFormer architecture is rigorously evaluated using the WSJ0-2mix dataset, a standard benchmark in the field. The results of this evaluation are significant, demonstrating substantial improvements in key performance metrics. Notably, there is an increase in the Signal-to-Interference (SI)-Signal-to-Noise Ratio improvement (SNRi) by 16.5 and in the Signal-to-Distortion Ratio improvement (SDRi)-Signal-to-Interference (SDRi) by 16.8. These improvements are crucial indicators of the quality of source separation in SCBSS. The findings of this research are groundbreaking, indicating that the proposed ConvTransFormer architecture surpasses existing methods in both SI-SNRi and SDRi performance metrics. This advancement marks a significant step forward in the field of SCBSS, offering new avenues for more effective and precise audio signal processing, especially in scenarios where isolating individual sound sources from a single- channel input is essential

Improved Soil Data Prediction Model Base Bioinspired K-Nearest Neighbor Techniques for Spatial Data Analysis in Coimbatore Region

In this research paper, agricultural Data Mining data are summarized. An improved Soil Data Prediction Model is developed to estimate the above parameters at locations for Coimbatore city. 142 locations were investigated for the development of the model. The model involves multiple regression equation, chi-square test and Bio inspired k-nearest neighbor classification. The GIS was used to manage the database and to develop thematic maps for depth, N value, free swell, liquid limit, plastic limit, plastic index, percentage gravel, percentage sand and percentage slit and clay. Field and laboratory studies were conducted in four locations and are compared with the predicted values

Predictor Analysis of the Non-parametric Bulk Arrival Fuzzy Queueing System

In general, queueing methodology is most helpful for design the system and that may achieve the described performance level. This paper, we discuss the fuzzy queueing model with fuzzy parameter. First we construct the membership function of the fuzzy queueing character where the arrival and service rates are triangular fuzzy numbers. Consider the service node as k-phase and to provide the equal service rate in all the phases. Second we shows that the method for constructing the membership function of finite capacity queueing system. A pair of nonlinear program is developed to describe the family of crisp membership functions of finite capacity through which the membership functions of the system performance measures are derived. Finally, we obtain the lower and upper bound of the system performance measure at the different possibility level of alpha. Third we analyze the optimal level of the queueing system, this work extended in [13, 14]. A numerical example is solved successfully