Search results for: automation impact regression

Authors: Tadele Tesfay Teame, Tsegaye Abrehame, Hágen István Zsombor

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Liquidity is one of the main concerns for banks, and thus achieving the optimum level of liquidity is critical. The main objective of this study is to discover the driving force of selected private commercial banks’ liquidity. In order to achieve the objective explanatory research design and quantitative research approach were used. Data has been collected from a secondary source of the sampled Ethiopian private commercial banks’ financial statements, the National Bank of Ethiopia, and the Minister of Finance, the sample covering the period from 2011 to 2022. Bank-specific and macroeconomic variables were analyzed by using the balanced panel fixed effect regression model. Bank’s liquidity ratio is measured by the total liquid asset to total deposits. The findings of the study revealed that bank size, capital adequacy, loan growth rate, and non-performing loan had a statistically significant impact on private commercial banks’ liquidity, and annual inflation rate and interest rate margin had a statistically significant impact on the liquidity of Ethiopian private commercial banks measured by L1 (bank liquidity). Thus, banks in Ethiopia should not only be concerned about internal structures and policies/procedures, but they must consider both the internal environment and the macroeconomic environment together in developing their strategies to efficiently manage their liquidity position and private commercial banks to maintain their financial proficiency shall have bank liquidity management policy by assimilating both bank-specific and macro-economic variables.

Keywords: liquidity, Ethiopian private commercial banks, liquidity ratio, panel data regression analysis

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Authors: Sayantan Khanra, Rojers P. Joseph

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This study attempts to analyze the impact of demography and service quality on the adoption and diffusion of e-Government services in the context of India. The objective of this paper is to study the users' perception about e-Government services and investigate the key variables that are most salient to the Indian populace. At the completion of this study, a research model that would help to understand the relationship involving the demographic variables and service quality dimensions, and the willingness to adopt e-Government services is expected to be developed. Dedicated authorities, particularly those in developing economies, may use that model or its augmented versions to design and update e-Government services and promote their use among citizens. After all, enhanced public participation is required to improve efficiency, engagement and transparency in the implementation of the aforementioned services.

Keywords: adoption and diffusion of e-government services, demographic variables, hierarchical regression analysis, service quality dimensions

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Authors: Sadhana Ghnayem

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This article examines the relationship between several socio-economic and background variables of Arab-Israeli families and their effect on the conflict management style of forcing, where teenage children are expected to obey their parents without questioning. The article explores the inter-generational gap and the desire of Arab-Israeli parents to force their teenage children to obey without questioning. The independent variables include: the sex of the parent, religion (Christian or Muslim), income of the parent, years of education of the parent, and the sex of the teenage child. We use the dependent variable of “Obedience Without Questioning” that is reported twice: by each of the parents as well as by the children. We circulated a questionnaire and collected data from a sample of 180 parents and their adolescent child living in the Galilee area during 2018. In this questionnaire we asked each of the parent and his/her teenage child about whether the latter is expected to follow the instructions of the former without questioning. The outcome of this article indicates, first, that Christian-Arab families are less authoritarian than Muslims families in demanding sheer obedience from their children. Second, female parents indicate more than male parents that their teenage child indeed obeys without questioning. Third, there is a negative correlation between the variable “Income” and “Obedience without Questioning.” Yet, the regression coefficient of this variable is close zero. Fourth, there is a positive correlation between years of education and obedience reported by the children. In other words, more educated parents are more likely to demand obedience from their children.  Finally, after running the regression, the study also found that the impact of the variables of religion as well as the sex of the child on the dependent variable of obedience is also significant at above 95 and 90%, respectively.

Keywords: conflict, religion, conflict management style, obedience

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Authors: Naser Zourikalatehsamad, Seyed Abdorreza Payambarpour, Ibrahim Alwashali, Zahra Abdolkarimi

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The paper aims to evaluate the effect of online advertising on consumer purchase behavior in Malaysian organizations. The paper has potential to extend and refine theory. A survey was distributed among Students of UTM university during the winter 2014 and 160 responses were collected. Regression analysis was used to test the hypothesized relationships of the model. Result shows that the predictors (cost saving factor, convenience factor and customized product or services) have positive impact on intention to continue seeking online advertising.

Keywords: consumer purchase, convenience, customized product, cost saving, customization, flow theory, mass communication, online advertising ads, online advertising measurement, online advertising mechanism, online intelligence system, self-confidence, willingness to purchase

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Gayathri P. Nair

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The focus of this study is to identify whether the board structure has any significant impact on the firm performance and finding out any evidence of being listed in the Fortune 500 list compiled and published by the American business magazine, Fortune and published globally by Time Inc., as the world’s wealthiest companies. The list has been released based on the ranking obtained for the total revenues for the respective fiscal year which has ended on or before March 31st. The study has been conducted on the Indian companies that were listed in the Fortune 500 list for the past 10 years. This study employs a logical regression between the variables, firm performance and board composition as mentioned in the clause 49 of companies act 1956 and 2013. For getting the firm performance, ROA has selected as the key performance metric, as it focuses the management attention on the assets required to run the business. The highlight of the study is that the tools had been applied between public and private sector firms so that, it reveals whether the board composition is helping out to maintain the position in the list. In addition, the findings reveal that apart from independent directors, all other variables have significant impact on firm performance.

Keywords: board structure, Fortune 500 company, firm performance, India

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Authors: Franklin N. Mabe, Samuel A. Donkoh, Seidu Al-Hassan

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In order to increase and bridge the differences in rice yield, many farmers have resorted to adopting Farmer Innovation Systems (FISs) and Improved Agricultural Technologies (IATs). This study econometrically analysed the impacts of adoption of FISs and IATs on rice yield using multinomial endogenous switching regression (MESR). Nine-hundred and seven (907) rice farmers from Guinea Savannah Zone (GSZ), Forest Savannah Transition Zone (FSTZ) and Coastal Savannah Zone (CSZ) were used for the study. The study used both primary and secondary data. FBO advice, rice farming experience and distance from farming communities to input markets increase farmers’ adoption of only FISs. Factors that increase farmers’ probability of adopting only IATs are access to extension advice, credit, improved seeds and contract farming. Farmers located in CSZ have higher probability of adopting only IATs than their counterparts living in other agro-ecological zones. Age and access to input subsidy increase the probability of jointly adopting FISs and IATs. FISs and IATs have heterogeneous impact on rice yield with adoption of only IATs having the highest impact followed by joint adoption of FISs and IATs. It is important for stakeholders in rice subsector to champion the provision of improved rice seeds, the intensification of agricultural extension services and contract farming concept. Researchers should endeavour to researched into FISs.

Keywords: farmer innovation systems, improved agricultural technologies, multinomial endogenous switching regression, treatment effect

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Peter Temitope Agboola

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Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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Authors: Peng-Shao Chen, Yen-Jong Chen

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In recent years, global warming, the dramatic change in energy prices and the exhaustion of natural resources illustrated that energy-related topic cannot be ignored. Despite the relationship between the cities and CO₂ emissions has been extensively studied in recent years, little attention has been paid to differences in the geographical location of the city. However, the geographical climate has a great impact on lifestyle from city to city, such as the type of buildings, the major industry of the city, etc. Therefore, the paper instigates empirically the effects of kinds of urban factors and CO₂ emissions with consideration of the different geographic, climatic zones which cities are located. Using the regression model and a dataset of urban agglomeration in East Asia cities with over one million population, including 2005, 2010, and 2015 three years, the findings suggest that the impact of urban factors on CO₂ emissions vary with the latitude of the cities. Surprisingly, all kinds of urban factors, including the urban population, the share of GDP in service industry, per capita income, and others, have different level of impact on the cities locate in the tropical climate zone and temperate climate zone. The results of the study analyze the impact of different urban factors on CO₂ emissions in urban area with different geographical climate zones. These findings will be helpful for the formulation of relevant policies for urban planners and policy makers in different regions.

Keywords: carbon emissions, urban agglomeration, urban factor, urban geography

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Authors: M. Stelmachowski, M. Wojtczak

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The aim of the work was to assess the environmental impact of the selected small and medium-sized companies supplying heat and electricity to the cities with a population of about 50,000 inhabitants. Evaluation and comparison of the impact on the environment have been carried out for the three plants producing heat and two CHP plants with particular attention to emissions into the atmosphere and the impact of introducing a system of trading carbon emissions of these companies.

Keywords: CO2 emission, district heating, heat and power plant, impact on environment

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.

Keywords: hedonic regression, urban node, distance variables, multicollinerity, collinearity

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Authors: Petr Šimek, Kamil Kostruk

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This paper deals with the problem of testing the Electronic Control Unit (ECU) for the specified function validation. Modern ECUs have many functions which need to be tested. This process requires tracking between the test and the specification. The technique discussed in this paper explores the system for automating this process. The paper focuses in its chapter IV on the introduction to the problem in general, then it describes the proposed test system concept and its principle. It looks at how the process of the ECU interface specification file for automated interface testing and test tracking works. In the end, the future possible development of the project is discussed.

Keywords: electronic control unit testing, embedded system, test generate, test automation, process automation, CAN bus, ethernet

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Authors: M. Al-Farttoosi, M. Y. Rafiq, J. Summerscales, C. Williams

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Structures can be subjected to impact loading from various sources like earthquake, tsunami, missiles and explosions. The impact loading can cause different degrees of damage to concrete structures. The demand for strengthening and rehabilitation of damaged structures is increasing. In recent years, Car0bon Fibre Reinforced Polymer (CFRP) matrix composites has gain more attention for strengthening and repairing these structures. To study the impact behaviour of the reinforced concrete (RC) beams strengthened or repaired using CFRP, a heavy impact test machine was designed and manufactured .The machine included a newly designed support system for beams together with various instrumentation. This paper describes the support design configuration of the impact test machine, instrumentation and dynamic analysis of the concrete beams. To evaluate the efficiency of the new impact test machine, experimental impact tests were conducted on simple supported reinforced concrete beam. Different methods were used to determine the impact force and impact response of the RC beams in terms of inertia force, maximum deflection, reaction force and fracture energy. The manufactured impact test machine was successfully used in testing RC beams under impact loading and used successfully to test the reinforced concrete beams strengthened or repaired using CFRP under impact loading.

Keywords: beam, concrete, impact, machine

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Authors: Wondmnew Derebe Yohannis

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Farming irrigation plays a crucial role in rural development strategies, impacting both annual household income and livelihood. This research aims to evaluate the factors influencing irrigation participation and assess the impact of small-scale irrigation on rural households' annual income. The study collected data from 287 farmers in the Dahana district of northern Ethiopia. The research investigates the driving forces behind farmers' decisions to adopt small-scale irrigation and its effect on annual income gain. The findings reveal that several factors positively influence the probability of adoption, including access to credit, cultivated land size, livestock holding, extension contact, and the education level of the household head. Conversely, the distance to local markets and water schemes negatively affects the likelihood of adoption. To understand the differences in annual income between farm households that adopted irrigation and those that did not, a simultaneous equations model with endogenous switching regression is estimated. This accounts for the heterogeneity in the adoption decision and unobservable characteristics of farmers and their farms. The analysis compares the expected income gain under actual and counterfactual scenarios, considering whether the farm household adopted irrigation or not. The study reveals that the group of farm households that adopted irrigation has distinct characteristics compared to those that did not adopt it. Furthermore, the research demonstrates that the adoption of irrigation practices leads to an increase in annual income. Interestingly, the impact of small-scale irrigation on annual income is greater for the farm households that actually adopted irrigation compared to those in the counterfactual scenario where they did not adopt. Based on the findings, the researcher concludes that small-scale irrigation is a practical solution for meeting household financial needs in the study area. It is recommended that investments in small-scale irrigation continue to further improve the livelihoods of rural farming communities by enhancing annual income gains.

Keywords: small-scale irrigation, income, rural farm households, endogenous switching regression, user, non-user

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Authors: Zhan Haiyang, Gu Miao

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This article mainly introduces the control system architecture of space environment simulator, simultaneously also briefly introduce the automation control technology of industrial process and the measurement technology of vacuum and cold black environment. According to the volume of chamber, the space environment simulator is divided into three types of small, medium and large. According to the classification and application of space environment simulator, the control system is divided into the control system of small, medium, large space environment simulator and the centralized control system of multiple space environment simulators.

Keywords: space environment simulator, control system, architecture, automation control technology

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Babatunde Akeem Lawal

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In any organization, the primary aim is to maximize profit, but the major challenges facing them is the increase in cost of operation because of this there is increase in cost of production that could lead to inevitable cost control and cost reduction scheme which make it difficult for most organizations to operate at the cost efficient frontier. The study aims to critically examine and evaluate the application of cost control and cost reduction in organization performance and also to review budget as an effective tool of cost control and cost reduction. A descriptive survey research was adopted. A total number of 40 respondent retrieved were used for the study. The analysis of data collected was undertaken by applying appropriate statistical tools. Regression analysis was used to test the hypothesis with the use of SPSS. Based on the findings; it was evident that cost control has a positive impact on organizational performance and also the style of management has a positive impact on organizational performance.

Keywords: organization, cost reduction, cost control, performance, budget, profit

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: H. Naderpour, R. C. Barros, S. M. Khatami

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Seismic excitation is naturally caused large horizontal relative displacements, which is able to provide collisions between two adjacent buildings due to insufficient separation distance and severe damages are occurred due to impact especially in tall buildings. In this paper, an impact is numerically simulated and two needed parameters are calculated, including impact force and energy absorption. In order to calculate mentioned parameters, mathematical study needs to model an unreal link element, which is logically assumed to be spring and dashpot to determine lateral displacement and damping ratio of impact. For the determination of dynamic response of impact, a new equation of motion is theoretically suggested to evaluate impact force and energy dissipation. In order to confirm the rendered equation, a series of parametric study are performed and the accuracy of formula is confirmed.

Keywords: pounding, impact, dissipated energy, coefficient of restitution

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Authors: Saima Akbar

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The global financial crisis severely and adversely impacted the Pakistanis’ financial setups with far-reaching consequences for its victims. This study aimed to analyze the various determinants of the banks’ financial performance in Pakistan. The stepwise multiple regression analysis and pre-post analysis were carried out in this regard by using SPSS ver 22. The study found that the assets quality is the most influential determinant of return over assets followed by bank size and solvency. Advances, liquidity, investments, and size have positive while poor assets quality and deposits have a negative impact on the return over assets. The comparison of the pre-crisis and post-crisis coefficient values of the independent variables revealed that the global financial crisis had exerted a significant impact on the relative ability of the financial performance determinants to explain variations in return over assets.

Keywords: pre-crisis, post-crisis, coefficient values, determinants

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Authors: Mehmet Alpaslan Köroğlu, Musa Hakan Arslan, Muslu Kazım Körez

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Basic objective of this study is to create a regression analysis method that can estimate the length of a plastic hinge which is an important design parameter, by making use of the outcomes of (lateral load-lateral displacement hysteretic curves) the experimental studies conducted for the reinforced square concrete columns. For this aim, 170 different square reinforced concrete column tests results have been collected from the existing literature. The parameters which are thought affecting the plastic hinge length such as cross-section properties, features of material used, axial loading level, confinement of the column, longitudinal reinforcement bars in the columns etc. have been obtained from these 170 different square reinforced concrete column tests. In the study, when determining the length of plastic hinge, using the experimental test results, a regression analysis have been separately tested and compared with each other. In addition, the outcome of mentioned methods on determination of plastic hinge length of the reinforced concrete columns has been compared to other methods available in the literature.

Keywords: columns, plastic hinge length, regression analysis, reinforced concrete

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Authors: Ju-Hyung Kim, Dae-Ho Mun, Hong-Gun Park

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When an impact is applied to a floating floor, noise and vibration response of high-frequency range is reduced effectively, while amplifies the response at low-frequency range. This means floating floor can make worse noise condition when heavy-weight impact is applied. The amplified response is the result of interaction between finishing layer (mortar plate) and concrete slab. Because an impact force is not directly delivered to concrete slab, the impact force waveform or spectrum can be changed. In this paper, the changed impact spectrum was derived from several floating floor vibration tests. Based on the measured data, numerical modeling can describe the floating floor response, especially at low-frequency range. As a result, heavy-weight impact noise can be predicted using modified impact spectrum.

Keywords: floating floor, heavy-weight impact, prediction, vibration

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Authors: Nadilla Saskia, Octoria Nur, Assegaf Zareeva

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Mass transport infrastructures are essential to enhance the connectivity between regions and regional equity in Indonesia. Indonesia’s capital city, Jakarta, ranked the 10th highest congestion rate in the world based on the 2019 traffic index, contributing to air pollution and energy consumption. Other than that, the World Air Quality Report in 2019 depicted Jakarta’s air pollutant concentration at 49.4 mg, the 5th highest in the world. Issues of severe traffic congestion, lack of sufficient urban infrastructure in Jakarta, and greenhouse gas emissions have to be addressed through mass transportation. Indonesia’s government is currently constructing The Greater Jakarta LRT (Light Rapid Transit) as convenient, efficient, and environmentally friendly transportation connecting Jakarta with Bekasi and Cibubur areas and plans to serve the passengers in August 2023. Greater Jakarta LRT is operated with Grade of Automation (GoA) No.3, Driverless Train Operation (DTO). Hence, the automated technology used in rail infrastructure is anticipated to address these issues with greater results. The paper will be validated and establish the extent to which the automation system would increase energy efficiency, help reduce carbon emissions, and benefit the environment. Based on the calculated CO2 emissions and fuel consumption for the existing condition (2015) during the feasibility study of the LRT Project and the predicted condition in 2030, it is obtained that Greater Jakarta LRT with GoA3 operation will reduce the CO2 emissions and fuel consumption by more than 50% in 2030. In the bigger picture, Greater Jakarta LRT supports the government's goal of achieving Jakarta Net-Zero Emissions (NZE) 2050.

Keywords: LRT, Grade of Automation (GoA), energy efficiency, carbon emissions, railway infrastructure, DKI Jakarta

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Authors: Kartik Mahajan

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DevOps methodologies streamline software development and operations, promoting collaboration and automation. Traditional server management often relies on manual, repetitive tasks, leading to inefficiencies, potential errors, and increased operational costs. Ansible, as a configuration management tool, presents a compelling solution for automating infrastructure management processes. This review paper explores the implementation and testing of Ansible for server management, specifically focusing on automated user account configuration. By replacing manual procedures with Ansible playbooks, we aim to optimize server management, reduce human error, and potentially mitigate operational expenses. This study offers insights into Ansible’s efficacy within a DevOps context, highlighting its potential to transform server administration practices.

Keywords: cloud, Devops, automation, ansible

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Authors: Abdulmajid Mukhtar Afat

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This paper aims at introducing nondeterministic finite automata with ε value which is used to perform some operations on languages. a program is created to implement the algorithm that converts nondeterministic finite automata with ε value (ε-NFA) to deterministic finite automata (DFA).The program is written in c++ programming language. The program inputs are FA 5-tuples from text file and then classifies it into either DFA/NFA or ε -NFA. For DFA, the program will get the string w and decide whether it is accepted or rejected. The tracking path for an accepted string is saved by the program. In case of NFA or ε-NFA automation, the program changes the automation to DFA to enable tracking and to decide if the string w exists in the regular language or not.

Keywords: DFA, NFA, ε-NFA, eclose, finite automata, operations on languages

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Authors: M. Ouassaf, S. Belaid

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A series of quinoline derivatives with antimalarial activity were subjected to two-dimensional quantitative structure-activity relationship (2D-QSAR) studies. Three models were implemented using multiple regression linear MLR, a regression partial least squares (PLS), nonlinear regression (MNLR), to see which descriptors are closely related to the activity biologic. We relied on a principal component analysis (PCA). Based on our results, a comparison of the quality of, MLR, PLS, and MNLR models shows that the MNLR (R = 0.914 and R² = 0.835, RCV= 0.853) models have substantially better predictive capability because the MNLR approach gives better results than MLR (R = 0.835 and R² = 0,752, RCV=0.601)), PLS (R = 0.742 and R² = 0.552, RCV=0.550) The model of MNLR gave statistically significant results and showed good stability to data variation in leave-one-out cross-validation. The obtained results suggested that our proposed model MNLR may be useful to predict the biological activity of derivatives of quinoline.

Keywords: antimalarial, quinoline, QSAR, PCA, MLR , MNLR, MLR

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Authors: Sorayya Kazemi, Hamed Kharrati, Mehdi Abedinpour Fallah

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This paper presents the design and implementation of a novel electric pressure-sensitive toothbrush, capable of measuring the forces applied to the head of the brush. The developed device is used for gum recession measurement. In particular, the percentage of gum recession is measured by a Programmable Automation controller (PAC). Moreover, the brushing forces are measured by a Force Sensing Resistor (FSR) sensor. These forces are analog inputs of PAC. According to the applied forces during patient’s brushing and the patient’s percentage of gum recession, dentist sets the standard force range. The instrument alarms when the patient applies a force over the set range.

Keywords: gum recession, force sensing resistor, controller, toothbrush

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Authors: A. Hayrapetyan, A. Simon, P. Marques, G. Renart

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Business survival is a question of greatest interest for any economy. Firm characteristics that can explain or predict performance and, ultimately, business survival become of the greatest significance, as the sustainable longevity of any business can mean health for the future of the country. Family Firms (FFs) are one of the most ubiquitous forms of business worldwide, as more than half of European firms (60%) are considered as family firms. Therefore, the inherent characteristics of FFs are one of the possible explanatory variables for firm survival because FFs have strategic goals that differentiate them from other types of businesses. Although there is literature on the performance of FFs across generations, there are fewer studies on the factors that impact the survival of family and non-family FFs, as there is a lack of data on failed firms. To address this gap, this paper explores the differential survival of family firms versus non-family firms with a representative sample of companies of the region of Catalonia (Northeast of Spain) that were adhoc classified as family or nonfamily firms, as well as classified as failed or surviving, since no census data for family firms or for failed firms is available in Spain. By using the COX regression model on a representative sample of 629 family and non-family firms, this study investigates to what extent financial ratios, such as Liquidity, Solvency Rate can impact business survival, taking into consideration the socioemotional side of family firms, as well as revealing the differences between family and non-family firms. The findings show that the liquidity rate is significant for non-family firm survival, whereas not for family firms. On the other hand, FFs can benefit while having a higher solvency rate. Ultimately, this paper discovers that FFs increase their chances of survival when they are small, as the growth in size starts negatively impacting the socioemotional objectives of the firm. This study proves the existence of significant differences between family and non-family firms’ survival during economic crises, suggesting that the prioritization of emotional wealth creates distinct conditions for both types of firms.

Keywords: COX regression, economy crises, family firm, non-family firm, survival

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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