Discovering E-commerce Sequential Data Sets and Sequential Patterns for Recommendation

In E-commerce recommendation system accuracy will be improved if more complex sequential patterns of user purchase behavior are learned and included in its user-item matrix input, to make it more informative before collaborative filtering. Existing recommendation systems that use mining techniques with some sequences are those referred to as LiuRec09, ChoiRec12, SuChenRec15, and HPCRec18. LiuRec09 system clusters users with similar clickstream sequence data, then uses association rule mining and segmentation based collaborative filtering to select Top-N neighbors from the cluster to which a target user belongs. ChoiRec12 derives a user’s rating for an item as the percentage of the user’s total number of purchases the user’s item purchase constitutes. SuChenRec15 system is based on clickstream sequence similarity using frequency of purchases of items, duration of time spent and clickstream path. HPCRec18 used historical item purchase frequency, consequential bond between clicks and purchases of items to enrich the user-item matrix qualitatively and quantitatively. None of these systems integrates sequential patterns of customer clicks or purchases to capture more complex sequential purchase behavior. This thesis proposes an algorithm called HSPRec (Historical Sequential Pattern Recommendation System), which first generates an E-Commerce sequential database from historical purchase data using another new algorithm SHOD (Sequential Historical Periodic Database Generation). Then, thesis mines frequent sequential purchase patterns before using these mined sequential patterns with consequential bonds between clicks and purchases to (i) improve the user-item matrix quantitatively, (ii) used historical purchase frequencies to further enrich ratings qualitatively. Thirdly, the improved matrix is used as input to collaborative filtering algorithm for better recommendations. Experimental results with mean absolute error, precision and recall show that the proposed sequential pattern mining-based recommendation system, HSPRec provides more accurate recommendations than the tested existing systems

Stability of demand for money function in Nepal: A cointegration and error correction modeling approach

This paper examines the long run and short run demand for money functions and their stability issues for Nepal using the annual data set of 1975-2009 by using the recently developed ARDL modeling to cointegration popularized by Pesaran and Shin (1999). The bounds test shows that there exists the long run cointgrating relationship among demand for real money balances, real GDP and interest rate in case of both narrow and broad monetary aggregates. Further, the CUSUM and CUSUMSQ test reveal that both the long run narrow and broad money demand functions are stable. The results show that demand for real money balance in Nepal is a stable and predictable function of a few variables and the central bank can rely on the monetary aggregates as intermediate targets for achieving the broad economic objectives

Optimal Rate of Inflation in Nepal : An Empirical Investigation

This paper attempts to empirically examine the optimal rate of inflation for Nepalese Economy on the basis of annual data over the period 1975 to 2014. It employs the non-linear specification by Sarel (1996) and Conditional Least Squares Specification by Khan and Senhadji (2001) to estimate the optimal rate of inflation. The results from the study suggest that the threshold rate of inflation is 6 percent for the Nepalese case. When inflation is below this threshold, it does not have any significant effect on growth or it may have a slightly positive effect, whereas inflation has significant retarding effects on growth beyond the threshold. It is, thus, desirable to contain inflation to less than 6 percent to ensure that economic growth is unharmed by the pernicious effects of high inflation

Allocative efficiency and adoption of improved maize variety: A case of eastern hills of Nepal

Production and  profit from maize farming can be substantially increased by allocating resources efficiently and adopting improved maize variety. In this context, a study was undertaken to determine the allocative efficiency and factors affecting adoption of improved maize variety in Eastern hills of Nepal. Random sampling was conducted in eastern part of Khotang district namely, Halesi municipality and Diktel Rupakot Majuwagadi municipality during month of March 2019. Pretested semi-structured questionnaire was administered among 80 randomly selected farmers cultivating maize since last two years. Face to face interview was scheduled to obtain data. Cobb Douglas production function was used to determine allocative efficiency; probit regression model was launched to determine factors affecting adoption of improved maize variety.  Significant positive relation of cost of seed, planting, and weeding with income has suggested to increase expenditure on certified maize seed over own farm seed, line sowing over broadcasting, and weeding. The model revealed that increasing all the factors of production by 100% would result in increase in income by 71.83%. Furthermore, cultivating improved maize variety is more profitable than own farm seed. Probit regression model showed that, farmers who have received training, who were member of cooperatives and who have received high schooling were more likely to adopt open-pollinated improved maize variety. Unavailability of inputs (seed, fertilizer, and labor), insect pest attack and adverse climatic conditions were major constraint of maize farming. Therefore, it would be better to suggest maize producers to increase expenditure on seed; make maize field weed free and adopt line sowing method. In addition, providing training, increasing access over inputs and encouraging farmers towards cooperatives could be virtuous for sustainable maize production

Stability of demand for money function in Nepal: A cointegration and error correction modeling approach

This paper examines the long run and short run demand for money functions and their stability issues for Nepal using the annual data set of 1975-2009 by using the recently developed ARDL modeling to cointegration popularized by Pesaran and Shin (1999). The bounds test shows that there exists the long run cointgrating relationship among demand for real money balances, real GDP and interest rate in case of both narrow and broad monetary aggregates. Further, the CUSUM and CUSUMSQ test reveal that both the long run narrow and broad money demand functions are stable. The results show that demand for real money balance in Nepal is a stable and predictable function of a few variables and the central bank can rely on the monetary aggregates as intermediate targets for achieving the broad economic objectives

Characterization of Nepalese Barley Gene Pool for Leaf Rust Resistance

Barley (Hordeum vulagare L) is the major crop for the people living in the high hills and mountainous region of Nepal. Leaf rust (caused by Puccinia hordei) is one of the major production threats for barley cultivation. A lot of variation can be observed on Nepalese barley accessions with respect to leaf rust resistance characteristics. Two hundred and forty one barley accessions were screened for leaf rust resistance characteristics on heading stage at Khumaltar, Lalitpur, Nepal. Among them, one hundred and nine Nepalese barley accessions showing promising for disease resistance were screened using six SSR markers linked to leaf rust resistance genes. Bonus and Local Jau was used as the resistant and susceptible check respectively. Leaf rust resistance genes Rph1, Rph2, Rph3, Rph7, QBLR-P and QTL on chromosome 5HS were detected on Nepalese barley accessions using respective SSR markers. Eight Nepalese barley accessions showed presence of three and more leaf rust resistant genes. The poor relationship between the field disease resistance and molecular markers linked with specific leaf rust resistance gene proved that Nepalese barley gene pool contains other leaf resistance genes

Effect of plastic mulches on growth and yield of potato (Solanum tuberosum L.) in Dadeldhura, Nepal

A field experiment was conducted from February to June, 2020 at Bhatkanda, Dadeldhura, Nepal to assess the effectiveness of plastic mulches in potato production. The experiment was laid out in Randomized Complete Block Design (RCBD) with four replications comprising of five treatments viz: T1: white plastic mulch (white on black colored), T2: silver plastic mulch (silver on black colored), T3: perforated black plastic mulch, T4: black plastic mulch and T5: control (without mulch). Results revealed that the black plastic mulch significantly increased the rate of emergence while perforated black plastic exhibited highest values of all other studied growth parameters, yield components and quality parameters. The highest marketable tuber yield was obtained in perforated black plastic (6.05 kg/m2) followed by silver plastic (5.62 kg/m2), white plastic (5.46 kg/m2), black plastic (5.14 kg/m2) and lowest marketable tuber yield was obtained in control condition (4.07 kg/m2). Similarly, temperature difference between controlled and mulched condition at 15 cm depth of soil was observed up to 2.8°C with its highest value in black plastic mulch and lowest in control condition. The perforated black plastic mulch was found most economical with maximum value of net return (NRs. 1904.31 thousands/ha) and B: C ratio (5.83). This study concludes that the use of perforated black plastic mulch is most economical with optimum plant growth and yield, producing best quality potatoes under climatic condition of Dadeldhura, Nepal

Genetic variability, heritability, genetic advance and correlation among yield and yield components of rice (Oryza sativa L.)

This study was conducted during summer 2015 at Regional Agriculture Research Station, Dipayal, Doti, Nepal to estimate the genotypic and phenotypic variability, heritability, genetic advance and correlation on grain yield and yield associated traits using 26 advance genotypes of lowland irrigated rice. Analysis of variance revealed the existence of significant difference for days to flowering, maturity, plant height, panicle length, thousand grain weight and grain yield. High heritability was estimated for days to flowering (0.88), maturity (0.79), thousand grain weight (0.48) and plant height (0.43) suggesting these traits are under high genetic control. High phenotypic variation was observed for grain yield (24.87%), number of grains/panicle (22.45%), number of panicles/m2 (20.95%) and straw yield (20.75%) while grain yield had medium (12.02%) and remaining traits showed low genotypic coefficient of variation (<10%). High phenotypic coefficient of variation estimated as compared to genotypic coefficient of variation showed environmental influence on the expression of traits. Grain yield (11.98) and days to flowering (10.32) showed medium and remaining traits sowed low genotypic advance as percent of mean. High to low heritability with moderate to low genotypic advance as percent of mean suggested these traits were governed by non additive gene thus direct selection is not beneficial. Further improvements on yield potentiality and yield traits on these genotypes are suggested by creating variation and selection. Panicle length (r = 0.230), days to flowering (r = 0.247), effective tillers (r = 0.488) and straw yield (r = 0.846) manifested significant positive association with grain yield indicating that yield can be increased if selection applied in favor of those yield components

Newton type iterative methods with higher order of convergence

Newton type iterative methods are obtained with higher order of convergence and with higher efficiency. The methods have been compared with the similar existing methods of recent times