Multiple Square Research Articles

Influence of square jets in Oxygen transfer in an Open Channel

Plunging jets are popular for aeration in wastewater treatment plants due to low energy needs. In the present study, square jets were evaluated to determine their effectiveness in providing aeration efficiency by plunging jets in an open channel flow. The study seeks to add to the existing knowledge and provide insight into the performance of single and multiple square plunging jets in wastewater treatment plants. Passing a water sample from the pool through an open channel, via square water jet(s), has shown that variables such as a higher number of jets, and discharge have a significant impact on aeration efficiency (E20). The findings demonstrate that the increase in E20 was found to be 85.22% to 117.6% with Nj=64 over the single jet when discharge was varied from 3.41L/s to 4.75L/s, further affirming the remarkable effectiveness of plunging jets in promoting aeration in open channel flows. Furthermore, it was observed that Fr. No. is the parameter that has the most impact on calculating E20 with correlation of 0.95311.

The Effect of ESG Disclosure, Manager Qualification and Workplace Safety on Firm Value with Firm Size and Financial Leverage as Control Variables In Manufacturing Companies Listed on the Indonesia Stock Exchange year 2020-2022

The purpose of this study, which was designed with firm size and financial leverage acting as control variables, was to ascertain the impact of management qualification, workplace safety, and ESG disclosure on firm value as estimated by Tobin's Q. Manufacturers (mining, metal, and cement) that are listed on the IDX in 2020–2022 make up the study's community. This study employed multiple linear regression-ordinary least squares along with hypothesis testing, where the regression coefficient is tested using the t test. The findings show that Manager Qualification (MQ) has a significant positive impact on Firm Value (FV), Financial Leverage (FL) has a substantial negative impact on Firm Value (FV). While ESG disclosure, Workplace Safety (WS) and Firm Size (FS) have no substantial influence on Firm Value (FV). The variable that has the highest significant level (0.008 < 0.005) but the coefficient is negative is Financial Leverage (FL) due to the calculated t value of -2.71, followed by the Manager Qualification (MQ) variable with a significant level (0.023 < 0.05) with a positive coefficient. And followed by the Firm Size (FS) variable, the Workplace Safety (WS) variable, and ESG disclosure does not have a substantial impact because the coefficient value obtained is 0.116; 0.196; and 0.451, respectively, where the coefficient value is higher than 0.05. The outcomes demonstrated that Firm Value (FV) increases along with the increase in Manager Qualification (MQ) and Financial Leverage (FL) has a substantial negative impact on Firm Value (FV). While Firm Size (FS), Workplace Safety (WS), and ESG disclosure variables have no significant effect.

Force convective heat transfer simulation in a rectangular channel with multiple square obstacles via finite element method

This study investigated fluid flow and forced convective heat transfer in rectangular microchannels with square barriers, as illustrated in Fig. 1 . In the first situation, three obstacles were positioned along the microchannel’s top wall. In the second scenario, obstacles were positioned along the microchannel’s bottom wall. In the final example, three square obstacles are placed symmetrically on either side of the microchannel wall. With the help of the Finite Element Method (FEM), we investigate the physicochemical behavior of the microchannel. The development of computer code within COMSOL multiphysics made it possible to simulate heat transport and fluid flow. The results include the implications of the rarefaction effect on fluid flow and heat transmission and decisions regarding the location of barriers and the shape of obstacles in squares. In addition, with the lowest value in skin friction and a lower Nusselt number, the third example, which has barriers on both sides, provides a valuable method for reducing the fluid temperature at the exit of the microchannel. This is because it has barriers on both sides. In the section under “Results and Discussion,” we provide an in-depth analysis of the numerical data derived from the microchannel. • Objective: This study aims to numerically investigate forced convective heat transfer in a rectangular channel featuring multiple square obstacles. The simulation employs the FEM to model fluid flow and temperature distribution. • Geometry and complexity: The channel geometry incorporates square obstacles, introducing geometric complexity. The FEM is chosen for its capability to handle intricate geometries accurately.

Who receives most? Gendered consequences of divorce on public pension income in West Germany and Sweden

Abstract Sweden and West Germany have had persistently high divorce rates in recent decades, but these two welfare states were differently equipped to mitigate the economic consequences of divorce for individual security in old age: Sweden followed a gender-equal policy approach to enable women and men to achieve economic autonomy, while West Germany, following the male-breadwinner model, introduced the system of ‘divorce-splitting’ to account for differences in women's and men's income. Against this background, this study uses large-scale register data from the German Public Pension Fund and the Swedish population registers to examine how divorce is related to the monthly public old-age pension income of women and men. The main comparison groups are divorced and (re)married individuals who entered retirement between 2013 and 2018. We descriptively show annual income histories from ages 20 to 65, and calculate monthly public old-age pension income with respect to lifetime income and pension regulations, such as the supplements/deductions for ‘divorce-splitting’. Multiple ordinary least square regression models further examine how family status relates to monthly public old-age pension income by gender. The results reveal that women and men in Sweden experience similar working histories, although women's incomes are lower. This is also reflected in women still having lower pension incomes than men. However, divorced and married women show comparable pension incomes, while divorced men receive approximately 26 per cent less pension income than married men. In West Germany, divorced women have significantly higher pension incomes than married women. The system of ‘divorce-splitting’ increases women's and decreases men's pension incomes, which seems to equalise their pension incomes. However, both stay below a married man's pension income. The findings indicate economic inequality in public old-age pension income by family status in Sweden and West Germany.

Impact of calibrating a low-cost capacitance-based soil moisture sensor on AquaCrop model performance

Sensor data and agro-hydrological modeling have been combined to improve irrigation management. Crop water models simulating crop growth and production in response to the soil-water environment need to be parsimonious in terms of structure, inputs and parameters to be applied in data scarce regions. Irrigation management using soil moisture sensors requires them to be site-calibrated, low-cost, and maintainable. Therefore, there is a need for parsimonious crop modeling combined with low-cost soil moisture sensing without losing predictive capability.This study calibrated the low-cost capacitance-based Spectrum Inc. SM100 soil moisture sensor using multiple least squares and machine learning models, with both laboratory and field data. The best calibration technique, field-based piece-wise linear regression (calibration r2 = 0.76, RMSE = 3.13 %, validation r2 = 0.67, RMSE = 4.57 %), was used to study the effect of sensor calibration on the performance of the FAO AquaCrop Open Source (AquaCrop-OS) model by calibrating its soil hydraulic parameters.This approach was tested during the wheat cropping season in 2018, in Kanpur (India), in the Indo-Gangetic plains, resulting in some best practices regarding sensor calibration being recommended. The soil moisture sensor was calibrated best in field conditions against a secondary standard sensor (UGT GmbH. SMT100) taken as a reference (r2 = 0.67, RMSE = 4.57 %), followed by laboratory calibration against gravimetric soil moisture using the dry-down (r2 = 0.66, RMSE = 5.26 %) and wet-up curves respectively (r2 = 0.62, RMSE = 6.29 %). Moreover, model overfitting with machine learning algorithms led to poor field validation performance. The soil moisture simulation of AquaCrop-OS improved significantly by incorporating raw reference sensor and calibrated low-cost sensor data. There were non-significant impacts on biomass simulation, but water productivity improved significantly. Notably, using raw low-cost sensor data to calibrate AquaCrop led to poorer performances than using the literature. Hence using literature values could save sensor costs without compromising model performance if sensor calibration was not possible. The results suggest the essentiality of calibrating low-cost soil moisture sensors for crop modeling calibration to improve crop water productivity.

Causal Artificial Intelligence Models of Food Quality Data.

Causal Artificial Intelligence Models of Food Quality Data.

Public Expenditure and Economic Growth in Nigeria (2001 - 2021)

The study attempts to establish the relationship between government spending and GDP in Nigeria from 2001 to 2021. The multiple regression analysis's ordinary least squares (OLS) method was employed. The econometric research shows that the independent variables (recurrent spending, capital expenditure, domestic debt, foreign debt, and exchange rate) have a positive connection with the dependent variable GDP. The OLS findings also show that the overall model accounts for over 94.98% of the changes in the dependent variable (R2 = 0.9498). This means that the variable will have a considerable impact on the GPD. The study suggests that there is an urgent need to instill fiscal discipline in government expenditure by initiating effective internal control measures and more proactive economic management coordination and implementation, as well as discouraging all known productive activities and expenditures at all levels of government. There is also a need for the government to ensure that its expenditures are channeled appropriately to sectors such as infrastructure development in order to boost investment and output, with the expected outcome of price stabilization.

Machine learning - based shale wettability prediction: Implications for H2, CH4 and CO2 geo-storage

Shale wettability determines shale gas productivities and gas (H2, CH4 and CO2) geo-storage efficiencies. However, shale wettability is a complex parameter which depends on multiple influencing factors, thus very time-consuming and costly to measure experimentally. Herein, we combined the eXtreme gradient boosting (XGBoost) and Shapley additive explanation (SHAP) machine learning methods to accurately predict brine advancing (θA) and receding (θR) contact angles and estimate shale wettability. The XGBoost model demonstrated much higher prediction accuracies than the commonly-used multiple linear regression and partial least squares regression models, e.g., R2 was 0.946–0.999, 0.794–0.821, and 0.635–0.674, respectively for these three models. The SHAP sensitivity analyses showed that total organic carbon content and gas molecular weight (MG) were the two most significant factors influencing shale wettability. In addition, shale hydrophobicity positively correlated with MG, calcite content, pressure and brine ionic strength, while negatively correlated with temperature and quartz content. This work provides an efficient approach for shale wettability estimation, thus aiding in the implementation of improved gas recovery and gas geo-storage processes, to further guarantee energy security and mitigate climate change.

Twisting two-dimensional iron sulfide layers into coincident site superlattices via intercalation chemistry.

Layered van der Waals (vdW) materials are susceptible not only to various stacking polymorphs through translations but also twisted structures due to rotations between layers. Here, we study the influence of such layer-to-layer twisting through the intercalation of ethylenediamine (EDA) molecules into tetragonal iron sulfide (Mackinawite FeS). Selected area electron diffraction patterns of intercalated FeS display reflections corresponding to multiple square lattices with a fixed angle between them, contrary to a single square lattice seen in the unintercalated phase. The observed twist angles of 49.13° and 22.98° result from a superstructure formation well described by the coincident site lattice (CSL) theory. According to the CSL theory, these measured twist angles lead to the formation of larger coincident site supercells. We build these CSL models for FeS using crystallographic group-subgroup transformations and find simulated electron diffraction patterns from the model to agree with the experimentally measured data.

Modeling stabilizing the of orchard managers on the shores of Lake Urmia against late spring frost.

Despite the adverse effects of late spring frost on the ecological and economic impact on agriculture, the management of these events are poorly investigated. Therefore, the grounded theory was used for extracting the livelihood stabilization model of orchardists on the shores of Lake Urmia against late spring frosts. The statistical population of this study in the qualitative part included 22 experts in the field of horticulture. In the quantitative study, they included all orchardists in the villages along with Lake Urmia, comprising 341 people, of which 236 were randomly selected. By carefully examining and linking the concepts and subcategories, the most important subcategories that were included six subcategories. The results of all calculated goodness-of-fit indexes (chi-square [P > 0.01], RMSEA = 0.000, NFI = 0.95, CFI = 0.91, and GFI = 0.92) showed the model provided an excellent fit for the data. Standardized regression coefficients showed that interfering factors had the greatest impact on the livelihood of orchardists against late spring frosts (β = 0.47). Also, the background factors (β = 0.43) and causal factors (β = 0.39) were found to affect the livelihood of the orchardists in encountering late spring frost. The results of multiple square correlations of dependent variables also indicated that about 41% of the livelihood variance of small-scale orchardists was explained by the predictor variables (i.e. causal conditions, background factors and interfering factors). The findings of this study can assist policymakers, planners and relevant managers while paying more attention to orchardists in the region, so as to support decisions in order to achieve sustainable development.

Total edge irregularity strength for special types of square snake graphs

One of the extremely useful branches in graph theory is the labeling of a graph. Graph labeling plays a vital role in many fields such as database management, astronomy, coding theory, X-ray crystallography, communication network addressing and radar. A labeling of a connected simple graph GV,E\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G\\left( {V,E} \\right)$$\\end{document} is a map that assign each element in G\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G$$\\end{document} with a positive integer number. 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In this case, G\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$G$$\\end{document} has total edge irregularity strength (TEIS) if λ-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda^{\\!\\!\\!\\!\\!-}$$\\end{document} is minimum. In this paper, a new family of graphs called square snake graphs is defined and denoted by C4,n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$C_{4,n}$$\\end{document}. Moreover, we define some related graphs of square snake graphs named double square snake graph DC4,n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$D\\left( {C_{4,n} } \\right)$$\\end{document}, triple square snake graph TC4,n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$T\\left( {C_{4,n} } \\right)$$\\end{document} and m\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$m$$\\end{document}-multiple square snake graph MmC4,n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$M_m \\left( {C_{4,n} } \\right)$$\\end{document}. Finally, we determine TEIS for square snake graphs, double square snake graph, triple square snake graph and m\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$m$$\\end{document}-multiple square snake graph, which have many applications in coding theory and physics.

Geomorphologic controls and anthropogenic impacts on dissolved organic carbon from mountainous rivers: insights from optical properties and carbon isotopes

Abstract. Mountainous rivers are critical in transporting dissolved organic carbon (DOC) from terrestrial environments to downstream ecosystems. However, how geomorphologic factors and anthropogenic impacts control the composition and export of DOC in mountainous rivers remains largely unclear. Here, we explore DOC dynamics in three subtropical mountainous catchments (i.e., the Yinjiang, Shiqian, and Yuqing catchments) in southwest China, which are heavily influenced by anthropogenic activities. Water chemistry, stable and radioactive carbon isotopes of DOC (δ13CDOC and Δ14CDOC), and optical properties (UV absorbance and fluorescence spectra) were employed to assess the biogeochemical processes and controlling factors on riverine DOC. The radiocarbon ages of DOC in the Yinjiang River varied widely from 928 years BP to the present. Stepwise multiple regression analyses and partial least square path models revealed that geomorphology and anthropogenic activities were the major drivers controlling DOC concentrations and DOM characteristics. Catchments with higher catchment slope gradients were characterized by lower DOC concentrations, enriched δ13CDOC and Δ14CDOC, and more aromatic dissolved organic matter (DOM), which were opposite to catchments with gentle catchment slopes. Variabilities in DOC concentrations were also regulated by land use, with higher DOC concentrations in urban and agricultural areas. Furthermore, DOM in catchments with a higher proportion of urban and agricultural land uses was less aromatic, less recently produced, and exhibited a higher degree of humification and more autochthonous humic-like DOM. This research highlights the significance of incorporating geomorphologic controls on DOC sources and anthropogenic impacts on DOM composition into the understanding of DOC dynamics and the quality of DOM in mountainous rivers, which are globally abundant.

A Multipolarized Traveling-Wave Series-Fed Antenna Array Based on Patch

In this paper, a simple broadband multipolarized traveling-wave series-fed antenna array is proposed. The radiation unit cells are multiple squares. The square unit cell will change between circular polarized (CP) and linear polarized (LP) through a reasonable feeding mode. By adjusting the equivalent length of the unit cell, the Q value of the antenna can be reduced, resulting in the increase of the bandwidth of the array. The array consists of seven-unit cells and dual-port feeding. The unit cells which are connected by a microstrip line are arranged in a circular array. A reasonable layout of unit cells can achieve good port isolation of the array. The polarization performance of the array antenna is the same as that of the unit cell. The antenna is fabricated and measured. The measured results are consistent with the simulated results.

Experimental Study of discharge - head Flow Rate Relation through Combined Structure Sharp Crested Rectangular Weir with Multiple Square Orifice

Experimental Study of discharge - head Flow Rate Relation through Combined Structure Sharp Crested Rectangular Weir with Multiple Square Orifice

A multi-functional tunable terahertz graphene metamaterial based on plasmon-induced transparency

A graphene terahertz metamaterial composed of multiple square split ring resonators is proposed to realize the excellent functions of sensing and switching based on plasmon-induced transparency (PIT). The switch, operating at multiple frequencies can be easily achieved by adjusting the Fermi level of graphene, corresponding to a maximum amplitude modulation of 89.5 %. When the device is employed as a sensing platform, the multi-PIT effect can improve the sensitivity due to greater interactions between the metamaterial and analytes, leading to a maximum sensitivity of 380 GHz/RIU. These findings suggest that the proposed metamaterial can serve as a multipurpose device with broad applicability.

Online estimation of PID controllers and plant dynamics via multi‐recursive least squares estimation from closed‐loop I/O data

AbstractThis article proposes an online solution to address the problem of closed‐loop system identification using multiple recursive least squares estimation protocols. Some control systems cannot be analysed in an open‐loop form for stability reasons or the requirement for online control system operation. So, it is necessary to identify plant dynamics and controller parameters based on input–output data from the feedback structure. The presented method identifies real‐time parameters of plant dynamics and controller parameters by utilising a series of recursive least square estimation algorithms that estimate open‐loop data from noisy input–output data measured from the closed‐loop feedback structure. The proposed method can effectively identify abrupt variations in both the controller parameters and plant dynamics. This capability makes it valuable for deployment as a supervisory component, enabling the detection of any faults that may arise in operating systems. Mathematical formulations and theorems are developed, and two numerical case studies are presented to examine the feasibility and performance of the presented closed‐loop system identification protocol.

Raman spectroscopy-based prediction of ofloxacin concentration in solution using a novel loss function and an improved GA-CNN model

BackgroundA Raman spectroscopy method can quickly and accurately measure the concentration of ofloxacin in solution. This method has the advantages of accuracy and rapidity over traditional detection methods. However, the manual analysis methods for the collected Raman spectral data often ignore the nonlinear characteristics of the data and cannot accurately predict the concentration of the target sample.MethodsTo address this drawback, this paper proposes a novel kernel-Huber loss function that combines the Huber loss function with the Gaussian kernel function. This function is used with an improved genetic algorithm-convolutional neural network (GA-CNN) to model and predict the Raman spectral data of different concentrations of ofloxacin in solution. In addition, the paper introduces recurrent neural networks (RNN), long short-term memory (LSTM), bidirectional long short-term memory (BiLSTM) and gated recurrent units (GRU) models to conduct multiple experiments and use root mean square error (RMSE) and residual predictive deviation (RPD) as evaluation metrics.ResultsThe proposed method achieved an R^2 of 0.9989 on the test set data and improved by 3% over the traditional CNN. Multiple experiments were also conducted using RNN, LSTM, BiLSTM, and GRU models and evaluated their performance using RMSE, RPD, and other metrics. The results showed that the proposed method consistently outperformed these models.ConclusionsThis paper demonstrates the effectiveness of the proposed method for predicting the concentration of ofloxacin in solution based on Raman spectral data, in addition to discussing the advantages and limitations of the proposed method, and the study proposes a solution to the problem of deep learning methods for Raman spectral concentration prediction.

A - 90 Assessment Methods for Anxiety in Epilepsy.

Anxiety is disproportionately common in people with epilepsy, however, the optimal tool to screen for assessment of anxiety in epilepsy has not been definitively established. This study aims to assess if a long questionnaire such as the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) is necessary for identifying and quantifying anxiety symptoms in patients with epilepsy or if the Beck Anxiety Inventory (BAI) will suffice as a screening measure. Retrospective data were analyzed from a neuropsychology registry of patients with epilepsy (N = 317; 136 male, 181 female). As proposed by Kenfack et al, 2022, patients that scored ≥16 on the BAI were cross tabulated with patients identified by the MMPI-2-RF as having T-scores ≥65 on scales EID (emotional/internalizing dysfunction), RC7 (dysfunctional negative emotions), STW (stress/worry), AXY (anxiety), and RC1(somatic complaints). Multiple chi square tests with alpha set at.05 were performed to examine the relationship between BAI and MMPI-2-RF indices in identifying anxiety in patients with epilepsy. As shown in Table 1, scores above the cutoff on the BAI were significantly associated with scores falling above the cutoffs for all of the MMPI-2-RF anxiety indices (EID, RC1, RC7, STW, & AXY). The diagnostic value of the BAI is similar to that of MMPI-2-RF subscales commonly used to assess anxiety. The findings provide support for using the BAI for screening anxiety symptoms in patients with epilepsy undergoing neuropsychological assessment. Keywords: Anxiety, Epilepsy, MMPI-2-RF, BAI.

Toward Universal Substituent Constants: Relating QTAIM Functional Group Descriptors to Substituent Effect Proxies.

Substituents modulate reactions, but their effects are commonly described by using proxies to their functional group properties. Substituent descriptors from the quantum theory of atoms in molecules, which are true functional group properties, are related here to these proxies, which have historically had chemically relevant meaning. Due to the large number of descriptors, multivariate analysis is used to intuit their significance. Multiple linear regression, principal component, and partial least squares regression analyses highlight that these substituent descriptors contain similar information to the proxies while being intrinsic, predictable substituent properties. Sources of error limiting quantitative reproduction of the proxy data include transferability, experimental accuracy, and solvation issues.

Effect of Adopting Agricultural Technology on Farm Income of Commercial Vegetable Growers in Bagamati Province of Nepal

Improved agricultural technologies are being promoted among commercial vegetable growers to improve yield and income in Nepal. However, the rate of adoption of agricultural technologies is low. This study aims to assess the magnitude of the adoption of selected agricultural technologies and their effect on farm income in Bagamati Province, Nepal. We adopted a multi-stage sampling method and surveyed 180 randomly selected households. We used multiple ordinary least square regression model to measure the effect of the adoption of agricultural technology on farm income in the study area. The results indicate that the most adopted technologies in the study area are improved varieties, mini tillers, sprayers, water pumps, and integrated pest management whereas the least adopted are plastic tunnel, drip irrigation, agriculture mobile application, plastic mulching, and rainwater harvesting. Few households have adopted more technologies. The results also revealed that if the number of technology adopted increases by one unit, the farm income increases by 20.6%. This is significant at the 1% level. The result showed that farm size (p=0.008), and membership in farmer’s group/cooperative (p=0.01) also have a significant positive impact on farm income. Promoting broader adoption of appropriate technologies among farmers helps to boost income generation. Policymakers and stakeholders are suggested to encourage technology adoption among commercial vegetable growers through training, access to inputs and technologies, and organizing them in groups or cooperatives.