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Multi-Agent Based Diagnostic Model for Breast Tumour Classification
Yusuf Musa Malgwi,
Gregory Maksha Wajiga,
Etemi Joshua Garba
Issue:
Volume 4, Issue 1, June 2019
Pages:
1-7
Received:
5 February 2019
Accepted:
14 March 2019
Published:
10 April 2019
Abstract: Breast cancer is one of the most hazardous of all types of cancer affecting mainly women. It is the second leading cause of death in Nigerian women. It is difficult to classify breast tumour. The diagnosis of breast cancer on patients in hospitals and clinics is highly subjective and it is reliant on the physician’s expertise. This may often lead to incorrect diagnosis and long waiting time to diagnose breast tumour which may increase the possibility of Cancer metastasizing. This study focused on developing a multi-agent based model for diagnosis of breast tumours using the k-Nearest Neighbor (k-NN) algorithm by classifying the nature of the tumours based on their associated patterns of symptoms and other risk factors of Cancer diseases. A k-NN algorithm using Java and MYSQ was developed to extract and classify the symptoms associated with Breast Cancer. Java Agent Development Environment (JADE) was used for the modeling and simulation. The accuracy score was tested on a breast tumour clinical datasets which were gotten and formed from Federal Medical Centers (FMC) Yola and Gombe in Nigeria. The experimental result of the prediction model shows a percentage accuracy score of 98.9%.
Abstract: Breast cancer is one of the most hazardous of all types of cancer affecting mainly women. It is the second leading cause of death in Nigerian women. It is difficult to classify breast tumour. The diagnosis of breast cancer on patients in hospitals and clinics is highly subjective and it is reliant on the physician’s expertise. This may often lead t...
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Level of Obesity and Socioeconomic Factors of a Group of Adult People of Bangladesh: A Factor Analysis Approach
Bhuyan Keshab Chandra,
Fardus Jannatul
Issue:
Volume 4, Issue 1, June 2019
Pages:
8-14
Received:
5 December 2018
Accepted:
21 March 2019
Published:
13 April 2019
Abstract: The present study was based on data collected from 900 respondents of both urban and rural areas of Bangladesh. Among them 44.3 percent were overweight and obese. Majority (70.6%) were diabetic patients. With the increase in age significant increase in prevalence rate of obesity was observed. Higher prevalence rate was also observed among housewives. An upward shift of prevalence rate was observed among the higher educated respondents. Overweight and obesity were more among urban residents compared to rural residents and they were thirty two percent more exposed to overweight and obesity. Higher prevalence of obesity was noted among females. The proportion of overweight and obese was higher among them who did not do any physical labor. According to factor weights it was noted that the important factors for variation in the level of obesity were mainly gender variation followed by occupation, education and type of work.
Abstract: The present study was based on data collected from 900 respondents of both urban and rural areas of Bangladesh. Among them 44.3 percent were overweight and obese. Majority (70.6%) were diabetic patients. With the increase in age significant increase in prevalence rate of obesity was observed. Higher prevalence rate was also observed among housewive...
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The Effect of Exchange Rates on Nigerians Currency and Projecting the Naira for the Year 2025
Ledisi Giok Kabari,
Osuo-Genseleke Macarthy
Issue:
Volume 4, Issue 1, June 2019
Pages:
15-18
Received:
2 March 2019
Accepted:
2 April 2019
Published:
26 April 2019
Abstract: Exchange rate instability is a good pointer for monitoring Nigerian currency and it has always been a key economic indicator to sustain Nigeria and her economic growth. Linear regression is a great statistical tool used to find, predict and also to assess whether there is an undeviating correlation and dependences between numerical variables. This study investigates the instabilities in exchange rate of five countries’ currencies which includes European Euro, United Kingdom Pounds, Saudi Arabian Riyal, Switzerland swissf and the Nigerian Naira with key interest on Naira. This was done to ascertain whether changes in other countries will affect the exchange rate of Naira. The stable and fluctuating exchange rate of these countries were examined and used to plot a digital signal structure. Data used for this study is the daily exchange rate of five countries’ currencies (Euro, Pounds, Riyal, Swissf and Naira) from 12th October, 2005 to 2nd October, 2018 obtained from https://www.cbn.gov.ng/rates/exchratebycurrency.asp. We applied linear regression tool on our source data and also applied the equation for prediction on our coefficients so we were able to predict the exchange for Naira come year 2025 which gave us N311.076. The rate of accuracy (R2) and the coefficient of our model were used in predicting Nigerians exchange rate for year 2025. The 99% rate of accuracy of our model reveals that our model is perfect and the impression from this study is that the exchange rate of other countries affects Naira.
Abstract: Exchange rate instability is a good pointer for monitoring Nigerian currency and it has always been a key economic indicator to sustain Nigeria and her economic growth. Linear regression is a great statistical tool used to find, predict and also to assess whether there is an undeviating correlation and dependences between numerical variables. This ...
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Extermination of Obsolete Relationship Through KTMIN-JAK-MAXAM Algorithm in Confusion Mining
Kittappa Thiagarajan,
Jeyavel Kavitha,
Karunakaran Sarukesi,
Avudaiappan Maheshwari
Issue:
Volume 4, Issue 1, June 2019
Pages:
19-23
Received:
25 February 2019
Accepted:
10 April 2019
Published:
11 May 2019
Abstract: At the present time web contains many indistinguishable documents. Much effort made towards in investigates mechanism with identical detection algorithms, still the retrieved web documents with outmodedlink. In this proposed system, we are successfully identifying and minimize the redundant information and like link in web documents. We introduce the correct graph theory based KTMIN-JAK-MAXAM algorithm filters out the redundant link. From the proposed system, we have relevant information with more accuracy. Using this KTMIN-JAK-MAXAM algorithm accessing of web pages with reduced time and space complication.
Abstract: At the present time web contains many indistinguishable documents. Much effort made towards in investigates mechanism with identical detection algorithms, still the retrieved web documents with outmodedlink. In this proposed system, we are successfully identifying and minimize the redundant information and like link in web documents. We introduce t...
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Application of Fuzzy Clustering Methodology for Garment Sizing
Adepeju Abimbola Opaleye,
Adekunle Kolawole,
Oliver Ekepre Charles-Owaba
Issue:
Volume 4, Issue 1, June 2019
Pages:
24-31
Received:
16 April 2019
Accepted:
28 May 2019
Published:
12 June 2019
Abstract: With the growing demand for Ready-To-Wear outfits especially in African textile prints, the currently used European, American and Asian garment sizing systems seems unsuitable for the Nigerian garment industry where customer’s choose clothing item not only due to fit in terms of body measurements but also the dress culture, style, preference and some other implicit requirements. This study aims to develop a size chart for different styles of trousers worn by Nigeria male population. Anthropometric data of 500 customers were taken in a natural random process and from stable tailoring establishments. The data was analysed using descriptive statistics and the fuzzy clustering methodology (FCM) was used as a suggestive approach which describes subjectivity in customer preferences. Analysis of the FCM output shows that the number of individual measurements with misfit has no significant difference (Festimated= 1.119, p-value=0.375 and Fcritical= 2.866) across cluster. The percentages of misfit were 38.0, 23.4, 31.6, 31.4 and 3.8% for hip measurement, length, waist, thigh and bottom-girth respectively. The developed sizing system which reflects subjectivity in customer’s selection of trouser may also enhance both producer and retailer’s production and replenishment policy.
Abstract: With the growing demand for Ready-To-Wear outfits especially in African textile prints, the currently used European, American and Asian garment sizing systems seems unsuitable for the Nigerian garment industry where customer’s choose clothing item not only due to fit in terms of body measurements but also the dress culture, style, preference and so...
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A New Similarity Measure for Time Series Data Mining Based on Longest Common Subsequence
Gholamreza Soleimany,
Masoud Abessi
Issue:
Volume 4, Issue 1, June 2019
Pages:
32-45
Received:
3 May 2019
Accepted:
3 June 2019
Published:
20 June 2019
Abstract: In this research, a new similarity measurement method that named Developed Longest Common Subsequence (DLCSS) is suggested for time series data mining. The main idea of the DLCSS is using the logic of the Longest Common Subsequence (LCSS) method and the concept of similarity in time series data. In most studies related to time series data mining, referred to the LCSS and Dynamic Time Warping (DTW) methods as the best and most usable for similarity measurement methods, but the LCSS is intrinsically designed to measure the similarity of two sequences of character, which later was developed for time series by defining and determining the similarity threshold. The value of similarity threshold has huge impact on the quality of time series data mining. In the DLCSS by defining two similarity thresholds and determining the values of them, this defect is eliminated. The performance of the DLCSS will be compared with the LCSS and DTW in time series data mining by the Query by content and K-medoids Clustering techniques on 23 datasets from the UCR datasets. The result shows that it is possible to claim that the performance of the DLCSS is better than the LCSS and DTW with 90% confidence.
Abstract: In this research, a new similarity measurement method that named Developed Longest Common Subsequence (DLCSS) is suggested for time series data mining. The main idea of the DLCSS is using the logic of the Longest Common Subsequence (LCSS) method and the concept of similarity in time series data. In most studies related to time series data mining, r...
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Remittances, Poverty and Welfare: Evidence from Cumilla, Bangladesh
Issue:
Volume 4, Issue 1, June 2019
Pages:
46-52
Received:
11 April 2019
Accepted:
5 June 2019
Published:
24 June 2019
Abstract: International remittance is now one of talking issues around the world as it has been playing a vital role in socio-economic development of the developing countries like Bangladesh since last few decades. Thus, the present study explores the impact of international remittances on household poverty and welfare in Bangladesh. To achieve this objective, the study analyses primary data collected from 360 households from Cumilla district of Bangladesh. To find out the impact of remittances on poverty, the study employs the Foster-Greer-Thorbecke (FGT) index. On the other hand, a one way ANOVA test is used to examine the impact of remittances on household welfare. The paper finds that the incidence, depth and severity of poverty among remittance recipient households is quite less than that of remittance non-recipient households. Empirically, the study finds that about 6 percent of remittance recipient households lives below the poverty line while this rate is 48 percent for non-recipient households. The study also finds that the average gross per capita expenditure of remittance receiving households is three times higher than that of non-recipient households which interprets that recipient households enjoy higher level of welfare. Thus, it is found that remittances have significant influence on household welfare. The study recommends nursing international remittances as an important tool in reducing poverty and enhancing welfare.
Abstract: International remittance is now one of talking issues around the world as it has been playing a vital role in socio-economic development of the developing countries like Bangladesh since last few decades. Thus, the present study explores the impact of international remittances on household poverty and welfare in Bangladesh. To achieve this objectiv...
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Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive
Issue:
Volume 4, Issue 1, June 2019
Pages:
53-56
Received:
17 April 2019
Accepted:
31 May 2019
Published:
24 June 2019
Abstract: In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.
Abstract: In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probabil...
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