Analysis of Academic Interpersonal Communication Factors in the Covid-19 Pandemic Period of Buddhist College Students

This study aims to determine the factors influencing interpersonal communication of Buddhist College students, in the online learning process during the covid-19 pandemic, and (2) know the indicators that affect the student's interpersonal communication factors. This study uses a mixed-method. Qualitative methods are used to describe the data descriptively, while quantitative methods are used in factor analysis. Respectively, the most influential factor on interpersonal communication is the motivation in communicating in the academic field, with a score of 0.81, followed by self-confidence with a score of 0.67, and lastly, openness, with a score of 0.67. Each factor is composed of four indicators as follows. For example, confidence is composed of belief, a sense of responsibility, objectivity, and rationality. The strongest indicator of the self-confidence factor is the belief in one's abilities. Meanwhile, achievement motivation factors are mostly composed of such indicators as a willingness to learn, adaptability, the desire to excel, and the existence of communication efforts. The indicator of the strongest motivational factors is achievement motivation. In addition, the openness factor is composed of indicators of equality, environmental interaction, mutual trust, and values. The strongest indicator of the openness factor is the value of interpersonal communication, especially in online learning processes. Received: 31 October 2021 / Accepted: 3 December 2021 / Published: 3 January 2022

El sistema de mercadotecnia como apoyo para lograr la ventaja competitiva

El objetivo de este trabajo es analizar cómo los directores de las mypes del municipio de Santa Cruz Xoxocotlán gestionan las relaciones con los integrantes del sistema de mercadotecnia para obtener una ventaja competitiva. El instrumento se aplicó a 474 directores. El tamaño de la muestra considera un valor de p = 50%, un nivel de confianza de 95% y un margen de error de 5%. El estudio es cualitativo y de alcance descriptivo con un diseño transversal-descriptivo. Los resultados indican que las empresas deben mejorar en el plano de análisis del entorno, en la relación con el cliente y con los integrantes del microentorno para tener ventas frecuentes, clientes leales y satisfechos. AbstractThe objective of this research is to analyze how MSE directors from the municipality of Santa Cruz Xoxocotlan manage relationships with members of marketing systems to obtain a competitive advantage. An instrument was applied to 474 directors. The size of the sample considered a value of de p = 50%, a confidence factor of 95% and a 5% margin of error. The study is qualitative with a descriptive scope and of a cross-sectional descriptive design. The results indicate that the companies must improve the level of analysis of their surroundings in relation to their clients and the members of their micro-environment to achieve frequent sales, loyal and satisfied clients.

ScD of Computer Science. Load balancing method in SDN networks based on ACS with improved dynamic resiliency

The article discusses the topical issue of load balancing in distributed computing systems. The analysis of existing solutions is carried out, tasks, problems and practical significance are determined. An improved balancing method using the checkpoint method and an additional confidence factor is proposed, which made it possible to ensure a uniform load on the controllers, while maintaining an acceptable level of efficiency. An assessment of the performance and comparison of the proposed method with existing methods is carried out, as well as steps for further research are indicated.

Expertise

Professionals are in good standing in the principal-agent literature. With a sense of professional responsibility, an honor code or an oath, they bring extra effort to challenging and difficult to monitor tasks. Often they repay our trust. But there are also substantial challenges in delegating to those with difficult to replace knowledge and specialized training. These challenges are discussed in this chapter in a variety of individual and organizational contexts and in particular in analyzing the use that religious institutions and governments make of those with specialized training. Notwithstanding their rigidly hierarchical organizational structures, complete with rules of conduct and quite fearsome methods of control, the Catholic Church and the military have difficulty keeping agents on task. The chapter shows how these agents exploit their positions. Observing the theoretically unexpected passivity of principals when confronted with non-compliant behavior in these organizations, this chapter modifies the accepted account with the argument that group loyalties, asset specificity, and what the author refers to as the “agent confidence factor” put up the cost of punishment for the principal and protect noncompliant agents from the normal consequences of their actions.

An Innovative Approach to Integrated Fluid Typing in Depleted Reservoirs

The economic value of completing a reservoir is strongly influenced by the fluid type. Wells drilled in developed brown field penetrate reservoirs with significant pressure loss due to offset production. A major challenge in evaluating mature reservoirs is the uncertainty introduced by pore fluids with unknown or varying petrophysical properties, such as change hydrocarbon gravity, diminishing pore pressures, and low to absent gas level indication. These are prone to error and uncertainty. Accurate understanding of reservoir fluid properties is therefore a key requirement for successful reservoir management. This manuscript illustrates a successful integrated workflow to ascertain. An integration between LWD triple combo data, near/far neutron, mud logs, pressure measurement, and production history of neighbouring wells, are critical to confirm fluid type within the drilled reservoirs. Cross plots, ratios and confidence analysis are required to ascertain the confidence level. Acquired data was ranked according to uncertainty associated with the acquisition technique, rate of penetration, lag time, mud type, and pre-test drawdown. Mobility was used as an indicator of fluid type or phase change in absence of any major rock type changes. Gas data were verified for any mud contamination and analysed using ratios to verify Hydrocarbon wetness. Data was ranked based on confidence factor determined through data precision and reservoir propertied. We also highlight the uncertainty in measurements. The fluid typing workflow used successfully identified the correct fluid typing, and reduced the reliance on single conventional method, or the need to run pre-test measurements. Data in intervals dominated with residual oil saturation showed misleading fluid type, same applies in high permeability sand, corrected gas data analysis gave a good indication of fluid type and mapped the change in fluid phase when combined with log data, while near/ far neutron aided to correlate the different sands, however due to its relationship with porosity, there is no one correlation could be derived. This paper illustrates that standard petrophysical techniques, such as analysis of density and neutron porosity logs, near/far neutrons, pretest can give misleading results if used in solo without consideration to the uncertainty associated with the measurement. The integration of fundamentally different data has resulted in identifying the fluid typing and its distribution in the reservoir and without integrating other measurements. A fluid typing systematic was developed to ensure the best and cost-effective model to assure the correct fluid type is identified. In this paper, a methodology is proposed which uses the geodesic transform, and integrate various source fundamentally different data, which is routinely acquired, then develop a systematic reasoning of confidence on data precision and accuracy. The system followed ensured the correct mapping of fluid typing in various reservoirs with different petrophysical properties. It is the first time such workflow is followed, and an integrated approach is consistently used in different sandstone reservoirs.

Utilizing the Genetic Algorithm to Pruning the C4.5 Decision Tree Algorithm

A decision tree (DTs) is one of the most popular machine learning algorithms that divide data repeatedly to form groups or classes. It is a supervised learning algorithm that can be used on discrete or continuous data for classification or regression. The most traditional classifier in this algorithm is the C4.5 decision tree, which is the point of this research. This classifier has the advantage of building a vast data set and does not stop until it reaches the desired goal. The problem with this classifier is that there are unnecessary nodes and branches leading to overfitting. This overfitting can negatively affect the classification process. In this context, the authors suggest utilizing a genetic algorithm to prune the effect of overfitting. This dataset study consists of four datasets: IRIS, Car Evaluation, GLASS, and WINE collected from UC Irvine (UCI) machine learning repository. The experimental results have confirmed the effectiveness of the genetic algorithm in pruning the effect of overfitting on the four datasets and optimizing confidence factor (CF) of the C4.5 decision tree. The proposed method has reached about 92% accuracy in this work.

Implementasi Perbandingan Algoritma Apriori Dan FP-Growth Untuk Mengetahui Pola Pembelian Konsumen Pada Produk Panel Di PT Surya Multi Perkasa Movinko

Beberapa perusahaan belum banyak memanfaatkan data transaksi pembelian konsumen sebagai salah satu strategi penjualannya, data transaksi ini meliputi barang apa saja yang sering dibeli oleh konsumen dalam satu transaksi pembelian pada struk dan waktu yang berbeda. Jika data transaksi tersebut dianalisis dan digali lebih mendalam, maka perusahaan mendapatkan suatu insight berupa analisis pola pembelian konsumen dan menguntungkan bagi perusahaan. Pada penelitian ini dilakukan analisis data transaksi pembelian konsumen menggunakan perbandingan algoritma Apriori dan FP-Growth, dimana keduanya merupakan kelompok Metode Association Rule yang bertujuan untuk mengetahui pola pembelian konsumen. Data yang digunakan pada penelitian ini diperoleh dari data transaksi pembelian produk panel pada PT Surya Multi Perkasa Movinko. Data transaksi tersebut terdiri dari 23 jenis item produk dan 492 transaksi. Hasil eksperimen dari penelitian ini menunjukkan bahwa kinerja terbaik algoritma Apriori dengan support factor sebesar 0.0054 dan confidence factor sebesar 0.30 menghasilkan 12 aturan asosiasi, sedangkan kinerja terbaik algoritma FP-Growth dengan support factor sebesar 2 dan confidence factor sebesar 0.7 menghasilkan 9 aturan asosiasi.

A new approach for EOQ calculation using modified opportunity cost

Introduction: Optimal inventory levels are necessary for a firm to avoid shortage/excess of an item. Shortage of an item leads to stock out conditions which results in loss of profit. When items are correlated with each other, stock out condition of one item may result in non purchase of its associated items also which, in turn, further brings down the profit. In this paper, this loss in profit is used to modify opportunity cost of an item resulting in its modified EOQ. Method: One illustrative example has been discussed which incorporates purchase dependencies in retail multi-item inventory management. The model discussed in this research paper will be motivational for researchers and inventory managers and provides a method for incorporating correlation among items while managing inventory. Result: The EOQs of items are estimated both by using traditional method and then by using modified opportunity cost (modeled as loss profit). Results show that in frequent item set A, B, D, EOQs of all three items increased when correlation among them is considered resulting in increase in profit. Conclusion: One of the major focus areas of inventory management is to determine when and how much quantity of items needs to be ordered so that total inventory cost can be minimized and profit of a firm can be maximized. However, while calculating the true value of an item and the profit it brings to the firm, it is very essential to analyze its effect on the sale of other items. Asso-ciation rule mining provides a way to correlate items by calculating support and confidence factor. Discussion: In inventory management system, for increasing the profit of a firm, EOQs of items need to be calculated in order to avoid shortage or excess of inventory. For explaining the approach a very small database is taken consisting of only 5 items and 10 transactions therefore the increase in profit is minimal however, when this approach applies on real database consisting of thousands of items and transactions, the increase in profit will be significant.

Actitud hacia las matemáticas en el Grado de Maestro de Primaria

La actitud hacia las matemáticas de los futuros maestros puede condicionar la enseñanza de esta materia en los primeros niveles educativos. Para conocer cual es la actitud de los alumnos del Grado de Maestro de Primaria se ha consultado a lo largo de seis cursos académicos a 1150 alumnos de la facultad de Educación de la universidad de CCC de 2.º, 3.º y 4.º. Se les ha aplicado el cuestionario de Auzmendi (1992) que consta de 25 ítems en una escala de Likert de 1 a 5. Los resultados indican que uno de cada tres alumnos tiene una actitud negativa (inferior a 3), y que los alumnos de 4.º tienen una actitud más alta. El ítem de mejor puntuación es uno del factor confianza y el de peor uno del factor agrado. Future teachers' attitudes towards mathematics can influence the teaching of this subject-matter in the earlier years. In order to know their attitudes, 1,150 Primary Education students (2nd, 3rd and 4th years) of the Faculty of Education at the University of CCC were surveyed during 6 academic years. They were given the Auzmendi (1992) test which is composed of 25 items on a 1-5 Likert scale. The results show that 1 in 3 students has a negative attitude (lower than 3). They also show that men have a more favourable attitude than women and that 4th-year students have the highest attitude. The item with the highest score refers to the self-confidence factor whereas the one with the lowest score relates to the liking factor.