641 research outputs found
Strategic planning for a SME
The purpose of this research is to find competitive advantages for an organisation and prepare a long-term strategic planning for the SME. In a New Zealand context, small business enterprises play vital roles in business and the economic sector. However, most small business do not have specific competitive advantage and long-term strategies to compete in the market. Both qualitative and quantitative approaches have been used as mixed method research. Interviews and surveys have been done. Using those methods, researchers are intended to use the most effective implementation methodology to find out the best solution to the problem and cause of a SME. Location and customer satisfaction have been identified as the prime factors for the firm to run the business successfully. The business has been operating smoothly without using any further strategies to compete in the market. Recommendations involve pricing, advertising and stock management
Strategic planning for a SME
The purpose of this research is to find competitive advantages for an organisation and prepare a long-term strategic planning for the SME. In a New Zealand context, small business enterprises play vital roles in business and the economic sector. However, most small business do not have specific competitive advantage and long-term strategies to compete in the market. Both qualitative and quantitative approaches have been used as mixed method research. Interviews and surveys have been done. Using those methods, researchers are intended to use the most effective implementation methodology to find out the best solution to the problem and cause of a SME. Location and customer satisfaction have been identified as the prime factors for the firm to run the business successfully. The business has been operating smoothly without using any further strategies to compete in the market. Recommendations involve pricing, advertising and stock management
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Leveraging Emotional Engagement Techniques and Adult Learning Principles to Transform Safety Training
Safety training despite being the key measure to keeping workers safe within any occupational environment has not kept pace with the significant advancement in the fields of behavioral psychology and education. As a result, researchers have found that the pre-dated safety training techniques on construction sites fail in communicating information in a way that promotes long-term retention of knowledge among adult learners and they also end up generating a negative attitude towards safety among workers. Understanding the psychological antecedents to risk-taking behavior and utilizing prominent adult learning theories to revolutionize safety training could allow academics and practitioners to improve workers’ hazard recognition performance and risk assessment skills while promoting risk-averse behavior. This dissertation therefore aims to (1) test and validate the role of integral and incidental affective arousal in influencing key safety outcomes (hazard recognition performance, valuation of danger, and safety decisions); (2) use the findings to design a safety training program that generates targeted affective arousal but is also rooted in self-directed learning model to facilitate learning; (3) deliver the simulation-based multimedia training module as an intervention to construction workers in a quasi-field experiment to measure changes in affect and situational interest; and (4) apply multivariate statistics to validate if the training environment generated the desired emotional engagement and learning outcomes among workers.Analysis of the proposed conceptual model showed that the integral negative affective arousal increased perception of risk and promoted risk-averse decision-making in construction safety training context. The quasi-field experiment on 489 construction workers showed that the proposed safety training module generated context-driven negative emotions and also improved situational interest levels regarding safety training which is a primary precursor to learning. Moreover, these results were consistent across all relevant demographical groups common to construction sites in the United States. This work is the first effort that ascertains the efficacy of various adult learning mechanisms incorporated in the proposed training module and also validates relationship between affect, risk perception, and decision-making in an occupational training environment. Future research should seek to validate the application of this format of safety training for safety training in other domains and study the long-term effects of such training on skills and retention of knowledge of the workforce
Ideal-Theoretic Explanation of Capacity-Achieving Decoding
In this work, we present an abstract framework for some algebraic error-correcting codes with the aim of capturing codes that are list-decodable to capacity, along with their decoding algorithm. In the polynomial ideal framework, a code is specified by some ideals in a polynomial ring, messages are polynomials and their encoding is the residue modulo the ideals. We present an alternate way of viewing this class of codes in terms of linear operators, and show that this alternate view makes their algorithmic list-decodability amenable to analysis.
Our framework leads to a new class of codes that we call affine Folded Reed-Solomon codes (which are themselves a special case of the broader class we explore). These codes are common generalizations of the well-studied Folded Reed-Solomon codes and Univariate Multiplicity codes, while also capturing the less-studied Additive Folded Reed-Solomon codes as well as a large family of codes that were not previously known/studied.
More significantly our framework also captures the algorithmic list-decodability of the constituent codes. Specifically, we present a unified view of the decoding algorithm for ideal-theoretic codes and show that the decodability reduces to the analysis of the distance of some related codes. We show that good bounds on this distance lead to capacity-achieving performance of the underlying code, providing a unifying explanation of known capacity-achieving results. In the specific case of affine Folded Reed-Solomon codes, our framework shows that they are list-decodable up to capacity (for appropriate setting of the parameters), thereby unifying the previous results for Folded Reed-Solomon, Multiplicity and Additive Folded Reed-Solomon codes
On the Probabilistic Degree of OR over the Reals
We study the probabilistic degree over R of the OR function on n variables. For epsilon in (0,1/3), the epsilon-error probabilistic degree of any Boolean function f:{0,1}^n -> {0,1} over R is the smallest non-negative integer d such that the following holds: there exists a distribution of polynomials Pol in R[x_1,...,x_n] entirely supported on polynomials of degree at most d such that for all z in {0,1}^n, we have Pr_{P ~ Pol}[P(z) = f(z)] >= 1- epsilon. It is known from the works of Tarui (Theoret. Comput. Sci. 1993) and Beigel, Reingold, and Spielman (Proc. 6th CCC 1991), that the epsilon-error probabilistic degree of the OR function is at most O(log n * log(1/epsilon)). Our first observation is that this can be improved to O{log (n atop <= log(1/epsilon))}, which is better for small values of epsilon.
In all known constructions of probabilistic polynomials for the OR function (including the above improvement), the polynomials P in the support of the distribution Pol have the following special structure: P(x_1,...,x_n) = 1 - prod_{i in [t]} (1- L_i(x_1,...,x_n)), where each L_i(x_1,..., x_n) is a linear form in the variables x_1,...,x_n, i.e., the polynomial 1-P(bar{x}) is a product of affine forms. We show that the epsilon-error probabilistic degree of OR when restricted to polynomials of the above form is Omega(log (n over <= log(1/epsilon))/log^2 (log (n over <= log(1/epsilon))})), thus matching the above upper bound (up to polylogarithmic factors)
On the Probabilistic Degree of OR over the Reals
We study the probabilistic degree over reals of the OR function on
variables. For an error parameter in (0,1/3), the -error
probabilistic degree of any Boolean function over reals is the smallest
non-negative integer such that the following holds: there exists a
distribution of polynomials entirely supported on polynomials of degree at
most such that for all , we have . It is known from the works of Tarui ({Theoret.
Comput. Sci.} 1993) and Beigel, Reingold, and Spielman ({ Proc. 6th CCC} 1991),
that the -error probabilistic degree of the OR function is at most
. Our first observation is that this can be improved
to , which is better for small
values of .
In all known constructions of probabilistic polynomials for the OR function
(including the above improvement), the polynomials in the support of the
distribution have the following special structure:, where each is a linear form in
the variables , i.e., the polynomial is a
product of affine forms. We show that the -error probabilistic degree
of OR when restricted to polynomials of the above form is where . Thus
matching the above upper bound (up to poly-logarithmic factors)
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