HCBST: An Efficient Hybrid Sampling Technique for Class Imbalance Problems

Class imbalance problem is prevalent in many real-world domains. It has become an active area of research. In binary classification problems, imbalance learning refers to learning from a dataset with a high degree of skewness to the negative class. This phenomenon causes classification algorithms to perform woefully when predicting positive classes with new examples. Data resampling, which involves manipulating the training data before applying standard classification techniques, is among the most commonly used techniques to deal with the class imbalance problem. This article presents a new hybrid sampling technique that improves the overall performance of classification algorithms for solving the class imbalance problem significantly. The proposed method called the Hybrid Cluster-Based Undersampling Technique (HCBST) uses a combination of the cluster undersampling technique to under-sample the majority instances and an oversampling technique derived from Sigma Nearest Oversampling based on Convex Combination, to oversample the minority instances to solve the class imbalance problem with a high degree of accuracy and reliability. The performance of the proposed algorithm was tested using 11 datasets from the National Aeronautics and Space Administration Metric Data Program data repository and University of California Irvine Machine Learning data repository with varying degrees of imbalance. Results were compared with classification algorithms such as the K-nearest neighbours, support vector machines, decision tree, random forest, neural network, AdaBoost, naïve Bayes, and quadratic discriminant analysis. Tests results revealed that for the same datasets, the HCBST performed better with average performances of 0.73, 0.67, and 0.35 in terms of performance measures of area under curve, geometric mean, and Matthews Correlation Coefficient, respectively, across all the classifiers used for this study. The HCBST has the potential of improving the performance of the class imbalance problem, which by extension, will improve on the various applications that rely on the concept for a solution.

A new approach for solving multi-pantograph type delay differential equations

<p>In this paper, a modified procedure based on the residual power series method (RPSM) was implemented to achieve approximate solution with high degree of accuracy for a system of multi-pantograph type delay differential equations (DDEs). This modified procedure is considered as a hybrid technique used to improve the curacy of the standard RPSM by combining the RPSM, Laplace transform and Pade approximant to be a powerful technique that can be solve the problems directly without large computational work, also even enlarge domain and leads to very accurate solutions or gives the exact solutions which is consider the best advantage of this technique. Some numerical applications are illustrated and numerical results are provided to prove the validity and the ability of this technique for this type of important differential equation that appears in different applications in engineering and control system.</p>

Innovation Attributes of F2F Computer Assisted Cooperative Learning in Teaching Reading Skills

This study aimed at investigating the innovation attributes of face-to-face Computer Assisted Cooperative Learning (CACL). It employed a mixed method design as the data were collected through a survey and semi-structured interviews. The findings showed that face to face CACL has a high degree of adoption in higher education institutes to teach EFL/ESL learners. Also, the regression analysis showed that the five factors are strong predictors of innovation adoption with complexity has the highest significance, followed by compatibility, relative advantage, observability and trialability respectively. The study found that accessibility is an emerging innovation attribute which increases the adoption of any innovation practice. The paper concluded that the human element of face-to-face cooperative learning increases the adoption of CACL, and that relative advantage has influence on the other innovation attributes. The study recommends using face-to-face CACL in teaching EFL/ESL learners, and using accessibility as an innovation attribute.

The Impact of Risk-aware Consumer Trust on CB E-commerce Platforms on Purchase Intention

Cross-border e-commerce(CBRC) is increasingly affecting the value of traditional trade due to its rich variety, convenient operation, and free of time and space restrictions, and has also changed the consumer's Shopping habits. However, the development of CBEC still faces many problems, resulting in domestic consumers' willingness to consume on CBEC platforms is not high. Based on the above background, the research content of this paper is the influence of consumer trust on purchase intention based on perceived risk of CBEC platforms. In this paper, a questionnaire survey is used to collect data for simulation. The results show that from the regression results of the five dimensions of trust on purchase intention, the adjusted R2 is 0.466, indicating a high degree of fit. When the exploratory value in perceived promotional gains is high, it will leave consumers in an irrational state and weaken the perception of risk.

The Impact of Risk-Aware Consumer Trust on CB E-Commerce Platforms and Purchase Intention

Cross-border e-commerce(CBRC) is increasingly affecting the value of traditional trade due to its rich variety, convenient operation, and free of time and space restrictions, and has also changed the consumer's Shopping habits. However, the development of CBEC still faces many problems, resulting in domestic consumers' willingness to consume on CBEC platforms is not high. Based on the above background, the research content of this paper is the influence of consumer trust on purchase intention based on perceived risk of CBEC platforms. In this paper, a questionnaire survey is used to collect data for simulation. The results show that from the regression results of the five dimensions of trust on purchase intention, the adjusted R2 is 0.466, indicating a high degree of fit. When the exploratory value in perceived promotional gains is high, it will leave consumers in an irrational state and weaken the perception of risk.

Innovation Attributes of F2F Computer-Assisted Cooperative Learning in Teaching Reading Skills

This study aimed at investigating the innovation attributes of face-to-face Computer Assisted Cooperative Learning (CACL). It employed a mixed method design as the data were collected through a survey and semi-structured interviews. The findings showed that face to face CACL has a high degree of adoption in higher education institutes to teach EFL/ESL learners. Also, the regression analysis showed that the five factors are strong predictors of innovation adoption with complexity has the highest significance, followed by compatibility, relative advantage, observability and trialability respectively. The study found that accessibility is an emerging innovation attribute which increases the adoption of any innovation practice. The paper concluded that the human element of face-to-face cooperative learning increases the adoption of CACL, and that relative advantage has influence on the other innovation attributes. The study recommends using face-to-face CACL in teaching EFL/ESL learners, and using accessibility as an innovation attribute.

Studies in Canarium urceus (Linnaeus, 1758) Part 6: A new Canarium species from the Andaman Sea (Gastropoda: Strombidae) and discussion on related species

This part of the Canarium (Canarium) urceus-complex (Linnaeus, 1758) review after Abbott’s revision (Abbott, 1960) revision examines material from the Andaman Sea. At present, material from that region has been synonymised under the name Canarium (Canarium) urceus (Linnaeus, 1758). Canarium (Canarium) andamanense new species is known from the Andamanian Subprovince, a semi enclosed basin that is centered on the Andaman Sea and enclosed by the west coasts of Myanmar and Thailand and the Mergui Archipelago in the east, to the northern Malacca Strait in the south, and to the Andaman and Nicobar Islands in the west. This species is recognized and differentiated by solid, sturdy shells with a triangular body whorl, large knobs on the shoulder and bright orange aperture. This study further confirms that there is a high degree of bioregionalisation within the Canarium complex.

Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation

Segmentation and reconstruction of arteries is important for a variety of medical and engineering fields, such as surgical planning and physiological modeling. However, manual methods can be laborious and subject to a high degree of human variability. In this work, we developed various convolutional neural network ( CNN ) architectures to segment Stanford type B aortic dissections ( TBADs ), characterized by a tear in the descending aortic wall creating a normal channel of blood flow called a true lumen and a pathologic channel within the wall called a false lumen. We introduced several variations to the two-dimensional ( 2D ) and three-dimensional (3 D ) U-Net, where small stacks of slices were inputted into the networks instead of individual slices or whole geometries. We compared these variations with a variety of CNN segmentation architectures and found that stacking the input data slices in the upward direction with 2D U-Net improved segmentation accuracy, as measured by the Dice similarity coefficient ( DC ) and point-by-point average distance ( AVD ), by more than 15\% . Our optimal architecture produced DC scores of 0.94, 0.88, and 0.90 and AVD values of 0.074, 0.22, and 0.11 in the whole aorta, true lumen, and false lumen, respectively. Altogether, the predicted reconstructions closely matched manual reconstructions.

WAYS TO IMPROVE THE EFFICIENCY OF TELECOMMUNICATIONS SECTORS: THE EXAMPLE OF ARMENIA

Both worldwide and in Armenia, the telecommunications market is saturated. In order to understand the role of services offered by telecom operators, determine the availability of innovative technologies and identify problems that arise among subscribers, we conducted an anonymous sociological survey among the population of Armenia and also developed a system consisting of several indicators to measure the effectiveness of the sector. The results of the sociological survey prove once again that innovations and new technologies ensure customer loyalty. From the answers, it can be concluded that the reforms carried out in different years: the expansion of the network, the import of new technologies and their implementation contribute to the formation of loyal customers. To measure the effectiveness of the sector, the elasticity of various indicators in relation to each other was measured. As a result, the elasticity of real imports of innovative equipment in relation to real revenue is considered the most elastic of these indicators, which means that equipment imports are sensitive to a decrease in revenue. The results obtained indicate that the sector is in a fairly high degree of saturation, further growth of subscribers is accompanied by a decrease in revenue, since their attraction mainly occurs in the case of lower prices for the services provided. And the only way to be competitive is to provide new services by importing innovative equipment, especially by offering Internet services to consumers at affordable prices, thanks to increasing their loyalty.

Theoretical and experimental study of motion and sinking time of Saxon Bowls

This work focuses on investigating the time of sinking of a Saxon bowl proposed by ‘International Young Physicists’ Tournament in 2020. A quasi-static model is built to simulate the motion path of the bowl and predict the sinking time subsequently. The model assumes an open axisymmetric bowl with a hole in its base. The hole is modelled as a pipe for which the flow profile is governed by a modified Bernoulli’s equation which has a Coefficient of Discharge (C_d) added to account for energy losses. The motion of the entire bowl is assumed to be in quasi-static equilibrium for an infinitesimal time interval to calculate the volumetric flow rate through the hole. The model is used to predict the sinking times of various bowls against independent variables - hole radius, bowl dimensions, mass of bowl, mass distribution of bowl, and Coefficient of Discharge - and predict the motion path of bowls of different, axisymmetric geometries. Characterisation of C_d was done by draining a bowl filled with water and measuring the time taken to do so. Experimental verification was completed through measuring sinking times of 3D printed hemispherical bowls of the different variables in water. Motion tracking of bowls with different geometries was done using computational pixel tracking software to verify the model’s predictive power. Data from experiments for sinking time against the variables corroborate with the model to a great degree. The motion path tracked, matched the modelled motion path to a high degree for bowls of different shapes, namely a hemisphere, cylinder, frustum, and a free-form axisymmetric shape. The work is poised for an undergraduate level of readership.