An empirical analysis of the factors affecting bank crises in Japan : learning points for Bangladesh

This paper analyzes the factors that affect bank crises in Japan. There are numerous factors, qualitative and quantitative, identified from the analysis. For the quantitative analysis, the study employs the factor analysis, which detects three major components of factors that affect banking or financial crises in Japan. These are (i) common macro factors; (ii) bank sensitive micro factors; and (iii) household spending related factors. There are other factors, for example, policy dilemma, delayed or faulty deregulation measures and weak banking activities, which are not extracted from the factor analysis but adversely affect bank crises in Japan and hence discussed in details. The paper indicates some policy implications for the banking/financial sector of Bangladesh

The Swap Matching Problem Revisited

In this paper, we revisit the much studied problem of Pattern Matching with Swaps (Swap Matching problem, for short). We first present a graph-theoretic model, which opens a new and so far unexplored avenue to solve the problem. Then, using the model, we devise two efficient algorithms to solve the swap matching problem. The resulting algorithms are adaptations of the classic shift-and algorithm. For patterns having length similar to the word-size of the target machine, both the algorithms run in linear time considering a fixed alphabet.Comment: 23 pages, 3 Figures and 17 Table

Algorithms to Compute the Lyndon Array

We first describe three algorithms for computing the Lyndon array that have been suggested in the literature, but for which no structured exposition has been given. Two of these algorithms execute in quadratic time in the worst case, the third achieves linear time, but at the expense of prior computation of both the suffix array and the inverse suffix array of x. We then go on to describe two variants of a new algorithm that avoids prior computation of global data structures and executes in worst-case n log n time. Experimental evidence suggests that all but one of these five algorithms require only linear execution time in practice, with the two new algorithms faster by a small factor. We conjecture that there exists a fast and worst-case linear-time algorithm to compute the Lyndon array that is also elementary (making no use of global data structures such as the suffix array)

A study on small business enterprises in Bangladesh : searching for growth factors and obstacles

Small businesses are the heart of the market-based economy with their business operations in rural and urban areas of developed and developing countries. In Bangladesh, small business enterprises are playing a significant role by contributing to the production and services, employmnet and thereby to GDP. But these are found to face servere competition and different types of constraints. As a result, these have not achieved substantial growth. In view of this, the present study is primarily aimed at identifying factors and obstacles that influence the growth of SBEs. Finally, the paper suggests some policy measures which are expected to excel the growth of SBEs

Geometric distortion measurement for shape coding: a contemporary review

Geometric distortion measurement and the associated metrics involved are integral to the rate-distortion (RD) shape coding framework, with importantly the efficacy of the metrics being strongly influenced by the underlying measurement strategy. This has been the catalyst for many different techniques with this paper presenting a comprehensive review of geometric distortion measurement, the diverse metrics applied and their impact on shape coding. The respective performance of these measuring strategies is analysed from both a RD and complexity perspective, with a recent distortion measurement technique based on arc-length-parameterisation being comparatively evaluated. Some contemporary research challenges are also investigated, including schemes to effectively quantify shape deformation

Breast Cancer Detection by Extracting and Selecting Features Using Machine Learning

The cancer of the breast is a significant cause of female death worldwide, but especially in developing countries. For better results and higher survival rates, early diagnosis and screening are crucial. Machine learning (ML) methods can aid in the initialdiscovery and diagnosis of breast cancer by choosing the most informative elements from medical data and eliminating irrelevant ones. The approach of feature extraction involves taking unstructured data and extracting a representative set of characteristics that may be used to classify or forecast data. The aim is to decrease the dimensionality of the feature space while upholding or even refining the accuracy of the ML model. An artificial intelligence model is developed on the given features to categorize mammography images into benign and malignant groups. Different supervised learning techniques, including support vector machines, random forests, and artificial neural networks, are employed and contrasted in order to select the best-performing model. This research offers a comprehensive framework for utilizing machine learning methods to detect breast cancer. The technique demonstrates how it might assist radiologists in the early detection of breast cancer by effectively extracting and selecting critical characteristics that could improve patient outcomes and potentially save lives

Implications of ecotourism development in protected areas: A study from Rema-Kalenga Wildlife Sanctuary, Bangladesh

This article is based on visitors profile study of protected area based tourist spots of Rema-Kalenga Wildlife Sanctuary (RKWS), Bangladesh to ascertain the potential of ecotourism. Study findings shows that 69% male constitute the visitors group while the maximum number of visitors was found in the age of below 30 years. Most of the visitors were literate and among them 43% visitors were student. Most (53%) of visitors preferred to get recreation in holidays as they were employed. Visitors were highly preferred to come with friends group. About 92% respondents showed positive mind to come here in future while 89% respondents view that park has tourism potential. Most of the respondents reported the presence of wildlife (48%) most notable followed by plant diversity and tribal community as recreational. From χ2 test it is found that highly significance association present between tourism potentiality of the wildlife sanctuary and some demographic variable like income of tourists (χ2 = 49.138, p < 0.000), visiting pattern (χ2 = 19.344, p < 0.000), education of tourists (χ2 = 50.226, p < 0.000), travelling distance (Km - χ2 = 11.427, p < 0.022), duration of staying (χ2 = 12.867, p < 0.002), frequency of visit (χ2 = 8.456, p < 0.015), visiting time (χ2 = 6.530, p < 0.011), problem in the study area (χ2 = 14.962, p < 0.021), occupation of tourists (χ2 = 8.848, p < 0.031). If the problems addressed by the visitors were solved, RKWS would be a bright place of eco-tourism in Bangladesh