bluuebunny/crossref_metadata_2025_split huggingface dataset:
Big Five Personality on Life Satisfaction: Job Satisfaction and Job Stress as Mediators (Study on Small Enterprises in Garut Regency)
Authors: Kosasih Kosasih , Yuliaty Farida , Paramarta Vip , Kania Dewi , Fitriana Fitriana 
Published: March 2024

Objective: The purpose of this study is to investigate the relationship between personality traits and life satisfaction, as well as the impact of job satisfaction on life satisfaction and work stress. While investigating the function of job stress and job satisfaction in mediating the link between these variables.Methodology: This specific field of study adopts a quantitative research methodology and survey research techniques. A multivariate statistical method is used in the statistical tool that uses SmartPls 4 v.4.0.9.4 to compare exogenous and endogenous factors. The number of micro-enterprises in Garut Regency reached 150.557 (Garut Cooperative and SMEs Office, 2019), absorbing a total workforce of 2953 people. So, the population is the SME workforce who are still actively working. Sampling using incidental sampling and Purposive or Judgment sampling, namely sampling based on the number of respondents who filled out the instrument and must follow the sample proportions required in the SEM-SmartPlsmodel. So, the minimum sample is 120 employee respondents. Incidental sampling can likely achieve more than 130.Findings: According to the findings of hypothesis testing using Smart PLS, the first hypothesis (H1) is accepted, implying that personality significantly affects work stress. Since the second hypothesis (H2) is confirmed, personality affects life satisfaction. The third hypothesis (H3) is accepted which means that there is a significant relationship between job satisfaction and work stress. The fourth hypothesis (H4) is not accepted, proving that there is no discernible relationship between job happiness and life satisfaction. The fifth hypothesis (H5) is accepted which suggests that life satisfaction is significantly impacted by work stress. H9 is rejected, although H6, H7, and H8 are accepted.Conclusion: The capacity to forecast life satisfaction which falls into the moderate group can be attributed to the Big Five personality, job contentment, and work stress. Employees of SMEs in the Garut Regency can become more satisfied at work and in general by changing their personalities. Employees of SMEs experience both distress and eustress because job satisfaction has a favorable and important effect on work stress. It has not been demonstrated that life satisfaction is significantly influenced by job satisfaction. Life satisfaction is significantly impacted by job stress, suggesting that this stress is pleasant (eustress), such as self-motivation and stimulation to achieve personal goals in the work and life domains. According to mediation tests, the effect of personality on work stress is mediated by job satisfaction.
Influence of Fertilizer and Weed Management Practices on Yield, Economics and Post-Harvest Soil Properties of Onion (Allium Cepa L.) in North Central Plateau Zone of Odisha
Authors: Mishra N. , Sahoo K. C. , Ray M. , Prusty M. , Panda N. , Mohanty K. K. , Dhal P. 
Published: March 2024

To evaluate the nutrient and weed management practices on performance of onion, a field experiment was carried out during rabi 2017-18 and 2018-19 at the experimental plot of RRTTS, OUAT, Keonjhar, Odisha taking fifteen treatments in a split plot design. Among all the treatments, the maximum plant height was recorded in N3W4 (56.29 cm) which was closely followed by N3W3 (55.97 cm), number of leaves plant -1 was higher in N3W3 (12.47) significantly which was closely followed by N2W4 (12.33) and N2W3 (12.00) and maximum neck thickness was recorded in N1W2 (1.39cm). Among yield parameters, the average bulb weight of onion ranges from 33.56 g (N1W2) to 87.6 g (N2W3) while, the highest bulb yields of onion (17.37 and 20.40 t ha-1) was recorded for the treatment which to be exact was applied with pre-emergence application of pendimethalin @ 0.8 l ha-1 supplement with one hand weeding at 25 DAT with B:C ratio of 1.84 and 1.76 for the year 2017-18 and 2018-19 respectively. Similarly, the treatment combination of N2W3 i.e. application of 50% STBFR along with 50% FYM based on N requirement and pre-emergence application of pendimethalin @ 0.8 l ha-1 + one hand weeding at 25 DAT) was recorded the highest. The available nutrients like nitrogen, phosphorus, potash and sulphur content (284.67 kg ha-1, 14.83 kg ha-1 , 97.43 kg ha-1 & 11.40 kg ha-1) in the post harvest soil was recorded highest with the treatment N2W3.
Pengaruh E-Learning Terhadap Hasil Belajar Mahasiswa Pendidikan Agama Islam
Authors: Hasriadi Hasriadi 
Published: March 2024

Penelitian ini bertujuan untuk mengetahui pengaruh e-learning terhadap hasil belajar mahasiswa pada mata kuliah pengetahuan komputer program studi pendidikan agama islam iain palopo. Penelitian ini merupakan penelitian quasi experiment dalam bentuk Pretest-posttest control group design dengan jumlah populasi 60 orang digunakan sebagai sampel. Data penelitian diperoleh dengan teknik dokumentasi dan tes pengetahuan. Teknik dokumentasi digunakan untuk memperoleh data dan informasi berupa jumlah dan hasil belajar mahasiswa, serta tes pengetahuan diberikan pada awal (pre tes) dan akhir (post tes) pertemuan. Data yang terkumpul dianalisis dengan menggunakan statistik deskriptif. hasil analisis statistik deskriptif menunjukkan bahwa rata-rata hasil belajar mahasiswa untuk pre test kelas eksperimen sebesar 77,87, dengan standar deviasi 7,18. Rata-rata hasil belajar mahasiswa pre tes untuk kelas kontrol sebesar 74,27dengan standar deviasi 7,02. Untuk post tes rata-rata hasil belajar mahasiswa kelas eksperimen sebesar 84, 67 dengan standar deviasi 7,51 dan rata-rata hasil belajar mahasiswa kelas kontrol sebesar 80,93 dengan standar deviasi 5,43. Terdapat perbedaan yang signifikan hasil belajar mahasiswa pada mata kuliah pengetahuan komputer antara kelompok yang diberi perlakuan menggunakan metode konvensional dengan kelompok mahasiswa yang diberi perlakuan dengan menggunakan E-Learning pada program studi pendidikan agama islam IAIN Palopo.
Development of Science Module Based on Scientific Approach to Improve Science Process Skills of Elementary School Students
Authors: Anggraini Dini Puji , Riskyka Riskyka 
Published: March 2024

This research aims to develop a science module based on a scientific approach to improve science process skills. This research is research and development. This research usesÂ ADDIE development model which has 5 stages, namely analysis, design, development, implementation, and evaluation. This research only reached the implementation stage. The research was carried out at Hamas IT Elementary School. The research subjects were 18 class VI students. The object in this research is VIscience module based on a scientific approach.Â Data collection techniques are observation, interviews, questionnaires, tests. Data analysis in research is: (a) feasibility analysisÂ science module based on a scientific approachÂ and (b) effectiveness analysisÂ science module based on a scientific approach. Based onÂ the validation results for the product developed, namely a science module based on a scientific approach, show that the material expert validation results are 94.56%, including the very feasible category. Meanwhile, the results of media expert validation, namelyÂ 88.70%Â included in the very worthy category. The results of the pretest that were carried out showed that only 1 student completed it and 17 students did not complete it with a percentage of 44%. Meanwhile, the results of the posttest that had been carried out showed that 18 students completed the test with a percentage of 78%.Â Based on the explanation above,Â it can be concluded that the scientific approach based science module developed is suitable and effective for use by sixth grade studentsÂ at Hamas IT Elementary School.
Module Development Based on Communicative Approach to Indonesian Language Learning to Improve Speaking Skills of Elementary School Students
Authors: Pratiwi Siti Habsari , Faridah Eva , Bukit Nurdin , Surya Edy 
Published: March 2024

This research aims to improve students' speaking skills. This research is research and development, using the Four D development model, which consists of the define, design, develop, disseminate stages. This research has reached the development stage. The research was carried out at MIN 3 Langsa. The subjects in the research were 25 class III students consisting of 13 female students and 12 male students. The object in the research ismodule based on a communicative approach to Indonesian language lessons. The collection techniques used are observation, tests and questionnaires. Based on the results of validation by experts carried out on modules based on communicative approaches in Indonesian language lessons, the results of validation by language experts are in percentagesÂ 94.10% is categorized as very feasible,Â material expert validation with a percentage of 80.00% is categorized as feasible, and media expert validation results with a percentageÂ 90.70%Â categorized as very feasible, and validated by media experts with percentagesÂ 93.45%Â categorized as very feasible. Based on this description, it is concluded thata module based on a communicative approach to Indonesian language lessons is suitable for use at MIN 3 Langsa. The results of the pretest were 4 students who completed and 21 students who did not complete with a percentage of 46%. Meanwhile, 23 students completed the posttest and 2 students did not complete the test with a percentage of 70%. Based on this explanation, it was concluded that using a communicative approach based module in Indonesian language lessons was said to be effective for class III students at MIN 3 Langsa. Based on the results and discussion in this research, it is known that the communicative approach based module in Indonesian language lessons is said to be very feasible and effective for use with class III students at MIN 3 Langsa.
Development of E-Modules Based on the Socrates Method to Improve Learning Outcomes of Madrasah Ibtidaiyah Students in Mathematics Subjects
Authors: Pratama Anggili , Faridah Eva , Bukit Nurdin , Surya Edy 
Published: March 2024

This research aims to developÂ e-module based on the Socratic method. This research is research and development. This research uses the ADDIE development model, including analyze, design, develop, implement, and evaluate. This research only reached the implementation stage. The research was carried out inMIS AL Hidayah Sidomulyo.The research subjects were 20 class V students, consisting of 9 male students and 11 female students. The research object is an e-module based on the Socratic method to improve student learning outcomes. Data collection techniques are observation, tests and questionnaires. The data analysis techniques used are: (a) e-module analysis based on the Socratic method; (b) the effectiveness of e-modules based on the Socratic method. Based on validation results by media experts with a percentage of 94.85%, it is categorized as very feasible. The results of validation by material with a percentage of 94.65% are categorized as very feasible. Meanwhile, validation results by language with a percentage of 89.75% are categorized as very feasible. The results of the pretest trial were with a percentage of 45% with 3 students who completed it and 17 students who did not complete it. Meanwhile, the posttest trial had a percentage of 83.5% with 19 students who completed and 1 student who did not complete.It can be concluded that the e-module based on the Socratic method is feasible and effective to use.
Abnormalities detected on digital rectal examinations in dogs are common and influence diagnostic and treatment plans
Authors: Andrews Camille , Hess Rebecka S. , Drobatz Kenneth , Buriko Yekaterina 
Published: March 2024

Abstract

OBJECTIVE
To determine the frequency of abnormal findings on digital rectal examination (DRE) performed during physical examinations at a tertiary referral veterinary hospital, to establish what abnormal findings are most common and whether they impact diagnostic and treatment plans, and to assess whether patient signalment or admitting service influences the frequency of abnormalities.

ANIMALS
Client-owned dogs (n = 440).

METHODS
Veterinarians performed DREs on dogs as part of a physical examination. Patient signalment and DRE findings were recorded in a standardized survey. Findings were deemed normal or abnormal and described. Whether the findings changed the diagnostic or treatment plan was also recorded.

RESULTS
Abnormalities were detected on DRE in 160 of 440 (36%) dogs. Changes to the diagnostic plan occurred in 41 of 160 (26%) cases when an abnormality was found. Changes to the treatment plan occurred in 20 of 160 (12.5%) cases when an abnormality was found. Age (P = .2), sex (P = .9), and breed (P = 1) did not significantly influence the frequency of abnormal findings. Abnormal findings were significantly more common in dogs presenting to the emergency service than elective services (P = .005).

CLINICAL RELEVANCE
Among dogs presenting to a tertiary veterinary hospital, abnormalities found on DRE are common and change the diagnostic plan in 1 out of 4 dogs and treatment plan in 1 out of 8 dogs. This study supports the continued practice of DREs in dogs, especially in emergency settings, regardless of signalment.
On analytic functions related with q-generalized bounded Mocanu variation
Authors: Noor Khalida Inayat , Noor Muhammad Aslam 
Published: March 2024

Abstract
Let 𝒜 be the class of normalized functions which are analytic in the open unit disc. Jakson q-derivative represented by convolution operator

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{D_q}f\left( z \right) = {1 \over z}\left\{ {f\left( z \right)\star{z \over {\left( {1 - qz} \right)\left( {1z} \right)}}} \right\},\,\,\,\,f \in \mathcal{A},\,\,\,q \in \left( {0,1} \right)

is used to introduce a unified class Mq
(α, β, γ), α ≥ 0, β, γ ∈ [0, 1) and its various mapping properties are studied. For q → 1−1, β = γ = 0 and α = 1, this class reduces to the class K of close-to-convex univalent functions. A number of interesting results such as q-Bernardi integral operator and inclusion relations are included as part of this study. Applications are also pointed out as consequences of the main results.
Recent Advances in PCG Signal Analysis using AI: A Review
Authors: Roy Tanmay Sinha , Roy Joyanta Kumar , Mandal Nirupama , Mukhopadhyay Subhas Chandra 
Published: March 2024

Abstract
The paper reviews the milestones and various modern-day approaches in developing phonocardiogram (PCG) signal analysis. It also explains the different phases and methods of the Heart Sound signal analysis. Many physicians depend heavily on ECG experts, inviting healthcare costs and ignorance of stethoscope skills. Hence, auscultation is not a simple solution for the detection of valvular heart disease; therefore, doctors prefer clinical evaluation using Doppler Echo-cardiogram and another pathological test. However, the benefits of auscultation and other clinical evaluation can be associated with computer-aided diagnosis methods that can help considerably in measuring and analyzing various Heart Sounds. This review covers the most recent research for segmenting valvular Heart Sound during preprocessing stages, like adaptive fuzzy system, Shannon energy, time-frequency representation, and discrete wavelet distribution for analyzing and diagnosing various heart-related diseases. Different Convolutional Neural Network (CNN) based deep-learning models are discussed for valvular Heart Sound analysis, like LeNet-5, AlexNet, VGG16, VGG19, DenseNet121, Inception Net, Residual Net, Google Net, Mobile Net, Squeeze Net, and Xception Net. Among all deep-learning methods, the Xception Net claimed the highest accuracy of 99.43 + 0.03% and sensitivity of 98.58 + 0.06%. The review also provides the recent advances in the feature extraction and classification techniques of Cardiac Sound, which helps researchers and readers to a great extent.
Leveraging High Resolution Remote Sensing Images for Vehicle Classification using Sea Lion Optimization with Deep Learning Model
Authors: Ageed Zainab Salih , Yasin Hajar M. , Rashid Zryan Najat , Zeebaree Subhi R. M. 
Published: March 2024

Abstract
High-resolution remote sensing data renders worldwide images faster than traditional data collection strategies. Hence small objects such as cars are easily detected. Vehicle recognition on aerial remote sensing images (RSIs) in the complicated background of urban zones has always gained a lot of interest in the remote sensing field. The automatic vehicles enumeration research domain plays a significant role in several applications, including traffic management and monitoring. Target detection technology will be a crucial part of computer vision (CV) technology, and target detection techniques were enforced in several domains. Therefore, this study develops a new Vehicle Recognition and Classification using Sea Lion Optimization with Deep Learning (VRC-SLODL) model on RSI. In the presented VRC-SLODL technique, the major intention lies in recognising and classifying vehicles present in the images. The bilateral filtering (BF) technique can initially improve the RSI quality. The VRC-SLODL technique employs a modified residual network (ResNet) model to produce a set of feature vectors. Finally, the SLO algorithm with long short-term memory (LSTM) model is employed for vehicle classification, where the SLO algorithm acts as a hyperparameter optimizer. The experiments were performed on a benchmark dataset to examine the better performance of the VRC-SLODL technique. The obtained values reported the improved classification performance of the VRC-SLODL technique over other models.
Snake Optimization with deep learning enabled disease detection model for colorectal cancer
Authors: AL-Attabi Kassem 
Published: March 2024

Abstract
Colorectal cancer (CC) is prevalently studied carcinoma and it grows in the colon area of huge intestine. Histopathologist Usually Examine the colon biopsy during surgery or colonoscopy. Initial recognition of CC is useful for maintaining the model of accumulated cancerous cells. In medicinal practices, histopathological study of tissue specimens usually occurs in a traditional method but automatic tools which utilize Artificial Intelligence (AI) systems create effectual outcomes in disease detection efficiency. Deep learning (DL)techniques are demonstrated to generate remarkable outcomes on histopathology images in several studies. This study presents a Snake Optimization with Deep Learning Enabled Disease Detection Model for Colorectal Cancer (SODL-DDCC). The presented SODL-DDCC technique concentrates on the identification of CC on histopathological images. In the preliminary stage, the presented SODL-DDCC technique executes bilateral filtering (BF) approach to remove noise. In addition, the presented SODL-DDCC technique exploits Inception v3 as a feature extracting model with SO algorithm as a hyperparameter maximizing process. For CC classification, the graph convolution network (GCN) model is exploited. The investigation outcome evaluation of the SODL-DDCC approach is evaluated on standard dataset and the outputs are evaluated under distinct features. The empirical outputs highlighted the enhancements of the SODL-DDCC over current approaches.
A High-Performance Method Based on Features Fusion of EEG Brain Signal and MRI-Imaging Data for Epilepsy Classification
Authors: Yağmur Fatma Demirezen , Sertbaş Ahmet 
Published: March 2024

Abstract
A 1-dimensional (1D) and 2-dimensional (2D) biomedical signal analysis based on the Discrete Cosine Transform (DCT) feature extraction method was performed to diagnose epilepsy disorders with high accuracy. For this purpose, Electroencephalogram (EEG) data were used for 1D signal analysis and Magnetic Resonance Imaging (MRI) data were used for 2D signal analysis. The feature vectors were obtained by applying 1D DCT together with statistical methods such as mean, variance, standard deviation, kurtosis, and skewness for EEG data and by applying 2D DCT together with the statistical method of mean for MRI data. The most useful features were selected by applying Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Forward Selection and Backward Selection methods to the obtained feature vectors. Using EEG stand-alone features, MRI stand-alone features and EEG-MRI fused features, the classification of healthy and epileptic subjects was performed in the form of two clusters. The result of epilepsy classification in this work is 96% success of 1D EEG data by using the features selected by the PCA method, 94% success of 2D MRI data using the selected features by applying the Forward Method, 100% classification accuracy of 1D EEG and 2D MRI datasets by LDA method using the obtained fused features . The article shows that the fused features of EEG-MRI can be used very effectively for the diagnosis of epilepsy.
Applications of Correlation Analysis in Environmental Problems
Authors: Sampaio Nilo Antônio S. , Mazza Felipe Cury , Siqueira Sílvio Sérgio Silveira de , Miranda Junior João Ercio , Moutinho João Victor de Souza , Pacífico Lucas de Oliveira 
Published: March 2024

Objective: The aim of this work is to show the application of the Correlation Coefficient (Pearson, Spearman) to environmental problems.

Theoretical framework: Although the concepts of correlation and regression are intimately related, they are nevertheless different. Correlation may be described as the degree of association between two variables, whereas regression expresses the form of the relationship between specified values of one (the independent, exogenous, explanatory, regressor, carrier or predictor) variable and the means of all corresponding values of the second (the dependent, outcome, response variable, the variable being explained) variable (Asuero et al., 2006).

Method: Data was taken from 2 case studies in the environmental area and both were analyzed, the first with Pearson's Correlation Coefficient and the second with Spearman's Correlation Coefficient.

Results and conclusion: It was determined that the samples had high Pearson's Correlation Coefficient values in both cases, which showed a very high correlation in both cases. The use of both types of Correlation Coefficient proved satisfactory in both cases.

Implications of the research: The use cases of the Correlation Coefficient in the environmental area are multiplying in the scientific literature and are proving to be highly effective in showing the correlation between environmental variables.

Originality/value: Despite being a well-known statistical tool, the Correlation Coefficient is widely used and can bring innovations in its application in cases of environmental variables.