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This research applies deep neural networks (DNN) and convolutional neural networks (CNN) to the modeling and prediction of driving behavior in autonomous vehicles within the Smart City context. Developed, trained, validated, and tested within the Keras framework, the model is optimized to predict the steering angle for self-driving vehicles in a controlled simulated environment. Utilizing a training dataset comprised of image data paired with steering angles, the model achieves autonomous navigation along a designated track. Key innovations in the model’s architecture, including parameter fine-tuning and structural optimization, contribute to its computational efficiency and high responsiveness. The integration of convolutional layers facilitates advanced spatial feature extraction, while the inclusion of repeated layers mitigates information loss, with implications for potential future enhancements. Clustering algorithms, including K-Means, DBSCAN, Gaussian Mixture Model, Mean-Shift, and Hierarchical Clustering, further augment the model by providing insights into driving environment segmentation, obstacle detection, and driving pattern analysis, thereby enhancing complex decision-making capabilities amid real- world noise and uncertainty. Empirical results demonstrate the efficacy of Gaussian Mixture and DBSCAN algorithms in addressing environmental uncertainties, with DBSCAN displaying robust noise tolerance and anomaly detection capabilities. Additionally, the CNN model exhibits superior performance, with lower loss values on both training and validation datasets compared to an RNN model, underscoring CNN’s suitability for visually driven tasks within autonomous systems. The study advances the field of autonomous vehicle behavior prediction through a novel integration of neural networks and clustering algorithms to support sophisticated decision-making in autonomous driving. The findings contribute to the development of intelligent systems within the Smart City framework, emphasizing model precision and computational efficiency.

Abstract Since the outbreak of the COVID-19 pandemic in 2020, tens of thousands of scientific articles have been published. Researchers are enthusiastic to uncover the effects of COVID-19. This study aims to critically assess the methods researchers used to analyze the impact of COVID-19 on food security. The PRISMA and Bibliometric Methods were utilized in this study. The results of the PRISMA indicate that most researchers utilize quantitative methods, 61%, compared to 32% for qualitative and 7% for mixed methods. These findings provide important data. Firstly, researchers continue relying on quantitative methods (multiple linear regression and Chi-square). Secondly, 32% of the articles utilized qualitative and only two qualitative methods, phenomenological and case studies, have been identified. No researchers use grounded theory research (GTR) and ethnographic studies (SE). Thirdly, using mixed method among COVID-19 researchers is uncommon; only 3% of researchers employed it. Next, the results of the bibliometric reveal that the USA and China contribute the most to the publication on the impact of COVID-19 on food security. A review of research publications on the impact of COVID-19 on food security shows an alarming increase in food loss and waste due to excessive household food purchases. This trend has the potential to endanger food availability in the future. Recommendations to the government include offering incentives to reduce food loss and waste, improving supply chain coordination, training, and technical breakthroughs and innovations, especially for small-scale farmers. The government should support food banks and farmers' markets to shorten the value chain and connect farmers with consumers.

The research's objective was to examine the factors that directly and indirectly influence the effectiveness of agricultural extension in rice farming in Bantaeng Regency, Indonesia. The sample size included 155 rice farmers, and the Structural Equation Modeling (SEM) was used to examine the rice farmer data. The results indicated that latent variables such as farmer engagement (FER), family resources (FRR), application of product inputs (APR) (β = 3.383), and crop management (CMR, β = −2.712)) all have a significant effect on the effectiveness of agricultural extension (EAR). The findings of this study explained that the FER (β = 0.244), together with the FRR (β = 0.923), exerted a significant influence on the APR, potentially increasing rice production. Meanwhile, the APR (β = 0.777) provided good results on the CMR and EAR. The indirect effect hypothesis shows that the APR and CMR mediated the relationship between FER (β = 0.203), FRR (β = 3.383), and EAR, which emphasizes the importance of APR and CMR. Therefore, in improving the EAR programs, it is recommended that extension agencies and local governments provide support to rice farmers in their participation in agricultural organizations. This support should empower rice farming families, ensure proper allocation of agricultural inputs, and effectively manage rice crops using sustainable management principles. As a result of the findings of this study, individuals responsible for designing and managing agricultural extension programs will also gain important insights and data from the real world. Furthermore, as a consequence, agricultural extension agencies can continue to educate farmers and improve rice farming methods.

Over the past five years, rice production in Bantaeng Regency has averaged 5.2 tons per hectare, considerably below Bantaeng Regency's 2020 goal of 10.0 tons. Low rice yield internationally and domestically has prompted many studies to assess the effect of farmer and farm characteristics, and input factors on rice production. These include education, agricultural income, farmer cooperatives, production inputs, and financing. In response to this issue, the present study examined determinants of rice production in Bantaeng Regency, Indonesia. A representative sample of 185 rice farmers was randomly selected for structured interviews. The data analysis was carried out by employing the Binary Logistics Regression Analysis (BLRA). We used the BLRA to regress thirteen independent variables (land area, seed application, urea fertilizer, NPK fertilizer, insecticides, herbicides, farm labor, education length, education level, farmer age, experience in farming, landowner status, and farming distance) to examine their effects on rice production. As a result, all independent variables simultaneously had a statistically significant effect on rice yield. Then, the partial testing of thirteen variables revealed that five variables—urea fertilizer, NPK fertilizer, pesticide, labor, and farmer age—had a positive and significant impact on rice production. In contrast, the seed application variable has a statistically negative effect on rice yield, while the other variables do not. Based on the results of this study, we recommend five innovative rice farm management strategies to enhance rice production in the future. Firstly, the farmer should expand their cropped area and increase the use of urea fertilizer, insecticides, and herbicides, labor and seed reduction is expected to boost rice yield immediately. Secondly, governments must ensure farmers' access to urea and NPK fertilizers, pesticides, and certified seeds in the future. Thirdly, policymakers must regulate the high costs and limited availability of chemical fertilizers and pesticides, including insecticides and herbicides. The policymaker would guarantee farmers adequate access to these resources. Fourthly, the farmers should use certified seeds with great output potential and apply the right amount. Fifthly, the rural labor replacement policy regulates rural wages and pay to handle the expected farm labor shortage.

Maize is a significant food crop in Indonesia’s agricultural development endeavors. In South Sulawesi Province, Bantaeng Regency is one of the regencies that developed corn farming with a large land area. This study aimed to examine the impact of input application on maize yield and assess the degree of efficiency and inefficiency in maize farming. The study was conducted in Bantaeng Regency, utilizing a sample size of 180 households engaged in maize farming as the primary data collection method. The data collected was analyzed using the Stochastic Frontier Cobb-Douglas Model, Technical Efficiency Analysis, Allocative Efficiency Analysis, Economic Efficiency Analysis, and Inefficiency Model. The findings indicated that the variables of land area, seed application, urea fertilizer, insecticide, and herbicide exhibited a significant positive impact on yields of maize. Conversely, the variable of NPK fertilizer had a significant negative impact. In the meantime, it is observed that the labor variable demonstrates a negative impact. The observed values in technical (0.544), allocative (1.840), and economic (1.001) suggest that maize cultivation has not attained technical, allocative, or economic efficiency. Meanwhile, it was also found that the variables significant positive to the technical inefficiency of maize farming are farming experience and education level. Therefore, in a short-term perspective, from a technical-managerial perspective, expanding the area of land under management, increasing the volume of seeds, urea fertilizer, insecticides, and herbicides to the optimum use is the right choice and an effective way for farmers to increase maize production. On the local government side, reviewing the price of certified seeds, subsidizing the price of maize seeds, ensuring the availability of urea and NPK fertilizers, insecticides, and herbicides, and intensifying extension activities and technical guidance on maize cultivation are alternative agricultural policies that the government can implement to support the efficiency and effectiveness of maize farming management.

This study delved into the impact of input factor allocation on maize production, seeking to identify strategies for enhancing productivity. The primary data for this study were collected from maize farmer households and analyzed using the binary logistic regression model (BLRM). Consequently, the simultaneous examination of the twelve independent variables using the BLRM yielded a noteworthy impact on maize production. Meanwhile, five of the twelve variables examined in part revealed a significant and positive impact on maize production. The variables that demonstrated statistically significant positive relationships consisted of land area, labor, urea fertilizers, insecticides, herbicides, and labor. Then, seed application and NPK fertilizer variables had a negative and significant influence, whereas the other variables did not. The results of this study indicate that some production factors employed by farmers significantly affected maize yield. This information may be used to develop a practical strategy for enhancing productivity in maize farming. Some practical implications in immediately oriented recommended: the expansion of maize farming area managed by farmers and the increase in the volume of application of urea fertilizers, insecticides, and herbicides, as well as the increase in the number of workers in maize farming, are expected to encourage an increase in maize production. The results of this research also contribute to the existing knowledge by providing empirical evidence that clarifies the positive and significant impact of various production inputs, which include land area, urea fertilizers, insecticides, herbicides, and labor, on maize production and productivity. It also supports the objective of promoting more efficient farming practices.

The aim of this study was to identify key factors influencing the adoption of technological innovation in urban farming (ITUF) in Makassar City, South Sulawesi Province, Indonesia. Employing a quantitative approach for data analysis, primary data was gathered through a structured survey of 334 individuals randomly selected from 14 sub-districts. The survey instrument, based on Rogers's framework, included eight parameters and 22 research variables, analyzed through Binary Logistic Regression to explore their impacts on ITUF adoption. The study revealed eight significant variables influencing the adoption rate: knowledge and experience in farming, education, involvement in Urban Farming organizations, continuity of ITUF information dissemination, belief in the role of urban farming in job transition, availability of resources for ITUF implementation, environmental support, and observation of urban farming technology. The research affirmed that six out of the eight parameters from Rogers's Framework significantly affected ITUF Adoption. The influential parameters included personal characteristics, communication behavior, relative advantage, complexity, trialability, and observability. In contrast, socio-economic factors and compatibility did not significantly impact ITUF Adoption in this study. The study's findings led to four key recommendations for enhancing the sustainability of urban farming. These recommendations encompass strengthening diverse training and education initiatives, providing incentives for urban farming organizations, implementing informational campaigns, and facilitating vocational training in urban agriculture. Additionally, the city's government should ensure accessibility to urban farming resources, endorse resource-efficient methodologies, and utilize media channels for disseminating successful urban farming narratives, fostering increased public awareness and engagement.

The research examined how input allocation affects potato production, efficiency, and technical inefficiency in potato farming. The results of the Stochastic Frontier Model explained that land area, manure, matador insecticide, and victory fungicide significantly enhanced potato production. The study also discovered that potato farms and farmer characteristics affected potato farming inefficiency, and the farmers did not achieve economic efficiency. Based on these findings, in promoting sustainable farming practices, the government should assist farmers in expanding potato farming, obtaining readily available manure, and receiving comprehensive guidance from agricultural extension workers on the proper use of insecticides and fungicides.

The response of a probe with varying applied potential was studied at various operating pressures and the effect of magnetic field strength on the characteristics of argon plasma was investigated. Using a single Langmuir probe, the temperature and density of electrons were measured in both the presence and absence of a magnetic field. Sheath thickness was determined and the fluctuation of the density of ion current with working pressure was also examined. The results show that the electron temperature and sheath thickness vary inversely with the gas pressure and magnetic field strength, but the values of electron density increase with increasing pressure and magnetic field. In addition to that, when a magnetic field is applied, two groups of electrons are observed. Here, the values of the ion current density in the absence of magnetic field are greater than the ion current density in the presence of an applied magnetic field. [ABSTRACT FROM AUTHOR]

This study has focused on the natural dye extraction from a combination of Caesalpinia sappan L. (CSL) bark and Curcuma longa (CL) bulbs and evaluation of the physicochemical characteristics and performance (color intensity and fastness). To enrich the shades, the CSL-CL extracts were prepared by water solvent extraction using three dye compositions (75% CSL/25% CL; 50% CSL/50% CL and 25% CSL/75% CL) and three fixers (iron (II) sulfate, alum, and calcium oxide). To optimize the interactions between fabric and dye to produce high intensity and fastness, two preparation stages were performed before dyeing, i.e. washing using turkey red oil (TRO) and mordanting using alum and soda ash. UV spectral analysis shows variations in the maximum adsorption wavelength triggered by differences in dye composition. In line with this, the dyeing results also show the shades variation resulting from different types of fixers. From the CieLab coordinate, CL dye which is applied with calcium oxide fixer has produced the brightest color (highest L*) with the appearance of the least reddish (highest a*) and most yellowish (highest b*) color compared to other compositions and fixers. [ABSTRACT FROM AUTHOR]

Multiple cropping farming systems affect farmers' income and have become a serious determinant in agricultural development. The diversity of information received by the farmers including multiple cropping can provide new knowledge, which will in turn influence productivity and income. Therefore, this study aims to evaluate the benefits of multiple cropping and its economic impact on cocoa farmers' income. It was conducted using the Ordinary Least Square Method to estimate parameters and RC Ratio for income comparison from the farming systems. The results showed that the choice of farmers in cropping patterns and types of crops is aimed at avoiding crop failure. The advantage of multiple cropping is that the use of soil nutrients is more effective because plants grow together on the same land. It also provides a higher income compared to monocropping and tends to reduce operational costs. Among the five factors evaluated, only three influenced farmers' income through extension activities. They are information on credit amount obtained, level of heterogeneity, and agricultural production. These factors are important aspects of communication activities that can increase knowledge in a heterogeneous environment of multiple cropping systems, which will, in turn, improve farmers' income.

Background & Aims: Although Peptic ulcer is a benign lesion of the gastrointestinal tract often caused by the secretion of gastric acid and/or the multiplication of Helicobacter pylori, but its rupture (perforated peptic ulcer (PPU)) is a surgical emergency and requires immediate action. PPU could cause ECG changes leading to masking the patient's main disease and wrong treatment. In this study we evaluated the prevalence of changes in the ECG of patients with perforated peptic ulcer in Firouzabadi Hospital. Materials and Methods: In this cross-sectional study, demographic data of all patients with PPU in Firouzabadi Hospital were extracted from the archives and electrographs were earned by cardiologists and internal medicine specialists while visiting. Statistical analyses were fulfilled by SPSS V.22 software with significance level of 0.05. Results: 119 patients (86 males and 33 females) with PPU with mean age of 48.99 ± 16.18 were included in this study. Among 66 patients (55.5%) with band changes, 41 patients had one, 16 had two, 4 had three, and 5 had four pathological changes in their ECG. The most common pathological finding was T wave inversion which was observed in 29 patients (24.5%). more in male patients. There was no significant relationship between ECG findings with factors likeage, smoking, alcohol consumption, and a history of diseases such as diabetes, hypertension, and ischemic heart disease (P> 0.05). Conclusion: More than half of patients with PPU have at least one preoperative electrocardiographic change. Gender is an influential factor in PPU and electrocardiographic changes. Although the frequency of these changes was more common among populations with hypertension, diabetes, and ischemic vascular disease, but there was no statistically connections between them.

Over the last two decades, the growth of the fisheries sector in Indonesia has shown an increasing trend; however, behind the rapid development of this sector, the role of small-scale fisheries as one of the main actors supporting the whole industry is often neglected. They remain poor and continue to conduct fishing activities traditionally. Therefore, this study aims to describe the real situation of small-scale fishers, analyzing the fishers’ ownership of the boat they use, analyzing their income level to reveal their poverty status, and analyzing the factors affecting their income. The regression analysis results indicate that boat category, sea fish catch, fish selling price, fixed costs, and variable costs have significant effects on fishers’ net incomes.

This study aims to count the transaction costs on farms of hybrid corn of dry seeds and analyze the factors that the transaction costs affect on farms of hybrid corn of dry seeds at through UPJ. This research was conducted in the Gorontalo province with samples in Gorontalo disctrict and Boalemo and using ekononometric equation analysis as a method of analysis. The results showed that the value of the average transaction costs on farm of hybrid corn of dry seed sales amounted to Rp1.545.466,- per transaction on per farming, and the factors that affect significantly the fault tolerance of 5 percent to the transaction cost on farms of hybrid corn of dry seeds sales consist of the total production, regional market prices, technical labor wages, commissions and degradation rate. The conclusions in this study stated that the total transaction costs incurred the hybrid maize of dry seeds farmers on sales is still high enough to reduce farm income and the factors that the transaction cost affect on sales of hybrid corn of dry seeds significantly includes the total production, regional market prices, technical labor wages, commissions and degradation rate. Penelitian ini bertujuan untuk menghitung biaya transaksi usahatani jagung hibrida pipilan kering dan menganalisis faktor-faktor yang mempengaruhi biaya transaksi usahatani jagung hibrida pipilan kering melalui penjualan ke UPJ. Penelitian ini dilakukan di Provinsi Gorontalo dengan sampel kabupaten Gorontalo dan kabupaten Boalemo dengan menggunakan analisis persamaan ekononometrika sebagai metode analisisnya. Hasil penelitian menunjukkan bahwa besaran biaya transaksi ratarata penjualan jagung hibrida pipilan kering sebesar Rp1.545.466,- per transaksi per usahatani, serta terdapat faktor-faktor yang mempengaruhi secara signifikan pada toleransi kesalahan 5 persen terhadap biaya transaksi penjualan jagung pipilan kering yang meliputi total produksi, harga pasar regional, upah tenaga teknis, komisi dan nilai degradasi. Kesimpulan dalam penelitian ini menyatakan bahwa total biaya transaksi yang dikeluarkan petani atas penjualan jagung pipilan kering masih cukup tinggi sehingga memperkecil pendapatan usahatani jagung hibrida, serta faktor-faktor yang mempengaruhi biaya transaksi penjualan jagung hibrida pipilan kering secara signifikan meliputi total produksi, harga pasar regional, upah tenaga teknis, komisi dan nilai degradasi.

The Human Development Index (HDI) of the Selayar Islands Regency experienced an insignificant improvement. The low education index causes the low HDI achievement of the Selayar Islands Regency because the achievement of the education index is lower than the health index and the expenditure index. Therefore, it is essential to improve the education index. This study aims to analyze the factors that influence the education index. This study uses secondary data in panel data, a combination of time-series data from 2014 to 2019, and cross-section data from 11 sub-districts. Panel data to measure the factors that affect the Education Index were analyzed using regression analysis. The results show that the teacher to student ratio at elementary school has a negative effect on the education index, the class to student ratio at elementary school has a positive effect on the education index, while the school to student ratio at elementary school, school to student ratio at junior high school, class to student ratio at junior high school and teacher to student ratio at junior high school do not affect the education index.

In this study, asymmetric polysulfone (PSf)/polyvinylidene fluoride (PVDF) coated membranes were prepared from PSf/NMP/NH4Cl and PVDF/NMP/NH4Cl system via phase inversion induced by immersion precipitation. Effect of stirring time and cast thickness on morphology, mechanical strength, and pure water permeability of the prepared membranes were systematically studied by scanning electron microscopy (SEM), tensile tester and dead-end filtration experiments. The results demonstrated that the elevation in the stirring time resulted in higher porosity and greater formation of smaller pore sizes, which attributed to higher Young's modulus and comparable pure water permeability. The casting with different thicknesses was done in this study. It was shown that pores on the membrane surface become larger in size with an increase of cast thicknesses. At the same time, the porosity of the membranes was gradually reduced. When the 7 hours stirring time and 0.4 mm cast thickness was used in preparation, the membranes exhibited the excellent pure water permeability. In general, PSfPVDF coated membranes have an increased thermal resistance as the stirring time and casting thickness increases. In addition, chemical resistance analysis results showed higher acid resistance and lower alkaline resistance of the prepared membranes. On the whole, adjusting stirring time and cast thicknesses is an effective approach to tailor the mechanical strength, performance, thermal and also chemical resistance of the formed PSf/PVDF coated membranes. [ABSTRACT FROM AUTHOR]