Search results for: statistical index

Authors: D. Hilton

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An analysis of the Australian Diabetes Screening Study estimated undiagnosed diabetes mellitus [DM] prevalence in a high risk general practice based cohort. DM prevalence varied from 9.4% to 18.1% depending upon the diagnostic criteria utilised with age being a highly significant risk factor. Utilising the gold standard oral glucose tolerance test, the prevalence of DM was 22-23% in those aged >= 70 years and <15% in those aged 40-59 years. Opportunistic screening in Australian general practice potentially can identify many persons with undiagnosed type 2 DM. An Australian Bureau of Statistics document published three years ago, reported the highest rate of DM in men aged 65-74 years [19%] whereas the rate for women was highest in those over 75 years [13%]. If you consider that the Australian Bureau of Statistics report in 2007 found that 13% of the population was over 65 years of age and that this will increase to 23-25% by 2056 with a further projected increase to 25-28% by 2101, obviously this information has to be factored into the equation when age related diabetes prevalence predictions are calculated. This 10-15% proportional increase of elderly persons within the population demographics has dramatic implications for the estimated number of elderly persons with DM in these age groupings. Computational methodology showing the age related demographic changes reported in these official statistical documents will be done showing estimates for 2056 and 2101 for different age groups. This has relevance for future diabetes prevalence rates and shows that along with many countries worldwide Australia is facing an increasing pandemic. In contrast Japan is expected to have a decrease in the next twenty years in the number of persons with diabetes.

Keywords: Epidemiological methods, aging, prevalence.

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Authors: H. A. Al-Kahtani, A. A. Abou Arab, M. Asif

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Animal fats (camel, sheep, goat, rabbit and chicken) and vegetable oils (corn, sunflower, palm oil and olive oil) were substituted with different proportions (1, 5, 10 and 20%) of lard. Fatty acid composition in TG and 2-MG were determined using lipase hydrolysis and gas chromatography before and after adulteration. Results indicated that, genuine lard had a high proportion (60.97%) of the total palmitic acid at 2-MG. However, it was 8.70%, 16.40%, 11.38%, 10.57%, 29.97 and 8.97% for camel, beef, sheep, goat, rabbit and chicken, respectively. It could be noticed also the position-2-MG is mostly occupied by unsaturated fatty acids among all tested fats except lard. Vegetable oils (corn, sunflower, palm oil and olive oil) revealed that the levels of palmitic acid esterifies at 2-MG position was 6.84, 1.43, 9.86 and 1.70%, respectively. It could be observed also the studied oils had a higher level of unsaturated fatty acids in the same position, compared with animal fats under investigation. Moreover, palmitic acid esterifies at 2-MG and PAEF increased gradually as the substituted levels increased among all tested fat and oil samples. Statistical analysis showed that the PAEF correlated well with lard level. The detection of lard in some commercial processed foods (5 French fries, 4 Butter fats, 5 processed meat and 6 candy samples) was carried out. Results revealed that 2 samples of French fries and 4 samples of processed meat contained lard due to their higher PAEF, while butter fat and candy were free of lard.

Keywords: Lard, adulteration, PAEF, goat, triglycerides.

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Authors: N. Damenia, E. Kharaishvili, N. Sagareishvili, M. Saghareishvili

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Women's Employment is one of the most important issues in the global economy. The article discusses the stated topic in Georgia, through historical content, Soviet experience, and modern perspectives. The paper discusses segmentation insa terms of employment and related problems. Based on statistical analysis, women's unemployment rate and its factors are analyzed. The level of employment of women in Transcaucasia (Georgia, Armenia, and Azerbaijan) is discussed and is compared with Baltic countries (Lithuania, Latvia, and Estonia). The study analyzes women’s level of development, according to the average age of marriage and migration level. The focus is on Georgia's Association Agreement with the EU in 2014, which includes economic, social, trade and political issues. One part of it is gender equality at workplaces. According to the research, the average monthly remuneration of women managers in the financial and insurance sector equaled to 1044.6 Georgian Lari, while in overall business sector average monthly remuneration equaled to 961.1 GEL. Average salaries are increasing; however, the employment rate remains problematic. For example, in 2017, 74.6% of men and 50.8% of women were employed from a total workforce. It is also interesting that the proportion of men and women at managerial positions is 29% (women) to 71% (men). Based on the results, the main recommendation for government and civil society is to consider women as a part of the country’s economic development. In this aspect, the experience of developed countries should be considered. It is important to create additional jobs in urban or rural areas and help migrant women return and use their working resources properly.

Keywords: Employment of women, segregation in terms of employment, women's employment level in Transcaucasia, migration level.

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Authors: U. Tumaini, J. Msuya

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Food insecurity is a worrying challenge worldwide with sub-Saharan Africa including Tanzania being the most affected. Although factors that influence household food access security status and ways of coping with such factors have been examined, little has been reported on how these coping strategies vary along the urban-rural continuum especially in medium-sized towns. The purpose of this study was to identify food insecurity coping strategies employed by households and assess whether they are similar along the urban-rural continuum. The study was cross-sectional in design whereby a random sample of 279 households was interviewed using structured questionnaire. Data were analysed using Statistical Package for Social Sciences (SPSS) Version 20 software. It was revealed that the proportion of households relying on less preferred and quality foods, eating fewer meals per day, undertaking work for food or money, performing farm and off-farm activities, and selling fall back assets was higher in rural settings compared to urban and peri-urban areas. Similarly, more households in urban and peri-urban areas cope with food access insecurity by having strict food budgets compared to those in rural households (p ≤ 0.001). The study concludes that food insecurity coping strategies vary significantly from one spatial entity to another. It is thereby recommended that poor, particularly rural households should be supported to diversify their income-generating activities not only for food security purposes during times of food shortage but also as businesses aimed at increasing their household incomes.

Keywords: Food coping strategies, household food insecurity, medium-sized towns, urban-rural continuum.

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Authors: Jihad S. Daba (Jean-Pierre Dubois), Philip Jreije

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Speckled images arise when coherent microwave, optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted by speckle noise is complicated by the nature of the noise and is not as straightforward as detection and estimation in additive noise. In this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series of Laguerre weighted exponential functions, resulting in a doubly stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form. It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.

Keywords: Doubly stochastic filtered process, Poisson point process, segmentation, speckle, ultrasound

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Authors: D. Ščeulovs, E. Gaile-Sarkane

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Fast development of technologies, economic globalization and many other external circumstances stimulate company’s competitiveness. One of the major trends in today’s business is the shift to the exploitation of the Internet and electronic environment for entrepreneurial needs. Latest researches confirm that e-environment provides a range of possibilities and opportunities for companies, especially for micro-, small- and medium-sized companies, which have limited resources. The usage of e-tools raises the effectiveness and the profitability of an organization, as well as its competitiveness. In the electronic market, as in the classic one, there are factors, such as globalization, development of new technology, price sensitive consumers, Internet, new distribution and communication channels that influence entrepreneurship. As a result of eenvironment development, e-commerce and e-marketing grow as well.

Objective of the paper: To describe and identify factors influencing company’s competitiveness in e-environment.

Research methodology: The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistics method, factor analysis in SPSS 20 environment, etc. The theoretical and methodological background of the research is formed by using scientific researches and publications, such as that from mass media and professional literature; statistical information from legal institutions as well as information collected by the authors during the surveying process. Research result: The authors detected and classified factors influencing competitiveness in e-environment. 

In this paper, the authors presented their findings based on theoretical, scientific, and field research. Authors have conducted a research on e-environment utilization among Latvian enterprises. 

Keywords: Competitiveness, e-environment, factors, factor analysis.

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Authors: V. H. Mankar, T. S. Das, S. K. Sarkar

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In this paper, we have proposed a novel blind watermarking architecture towards its hardware implementation in VLSI. In order to facilitate this hardware realization, cellular automata (CA) concept is introduced. The CA has been already accepted as an attractive structure for VLSI implementation because of its modularity, parallelism, high performance and reliability. The hardware realizable multiresolution spread spectrum watermarking techniques are very few in numbers in spite of their best ever resiliency against signal impairments. This is because of the computational cost and complexity associated with their different filter banks and lifting techniques. The concept of cellular automata theory in order to form a new transform domain technique i.e. Cellular Automata Transform (CAT) have been incorporated. Since CA provides spreading sequences having very low cross-correlation properties, the CA based pseudorandom sequence generator is considered in the present work. Considering the watermarking technique as a digital communication process, an error control coding (ECC) must be incorporated in the data hiding schemes. Besides the hardware implementation of entire CA based data hiding technique, the individual blocks of the algorithm using CA provide the best result than that of some other methods irrespective of the hardware and software technique. The Cellular Automata Transform, CA based PN sequence generator, and CA ECC are the requisite blocks that are developed not only to meet the reliable hardware requirements but also for the basic spread spectrum watermarking features. The proposed algorithm shows statistical invisibility and resiliency against various common signal-processing operations. This algorithmic design utilizes the existing allocated bandwidth in the data transmission channel in a more efficient manner.

Keywords: Cellular automata, watermarking, error control coding, PN sequence, VLSI.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: Yanju Zhang, Joost M. Woltering, Fons J. Verbeek

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It has been established that microRNAs (miRNAs) play an important role in gene expression by post-transcriptional regulation of messengerRNAs (mRNAs). However, the precise relationships between microRNAs and their target genes in sense of numbers, types and biological relevance remain largely unclear. Dissecting the miRNA-target relationships will render more insights for miRNA targets identification and validation therefore promote the understanding of miRNA function. In miRBase, miRanda is the key algorithm used for target prediction for Zebrafish. This algorithm is high-throughput but brings lots of false positives (noise). Since validation of a large scale of targets through laboratory experiments is very time consuming, several computational methods for miRNA targets validation should be developed. In this paper, we present an integrative method to investigate several aspects of the relationships between miRNAs and their targets with the final purpose of extracting high confident targets from miRanda predicted targets pool. This is achieved by using the techniques ranging from statistical tests to clustering and association rules. Our research focuses on Zebrafish. It was found that validated targets do not necessarily associate with the highest sequence matching. Besides, for some miRNA families, the frequency of their predicted targets is significantly higher in the genomic region nearby their own physical location. Finally, in a case study of dre-miR-10 and dre-miR-196, it was found that the predicted target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR- 10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar characteristics as validated target genes and therefore represent high confidence target candidates.

Keywords: MicroRNA targets validation, microRNA-target relationships, dre-miR-10, dre-miR-196.

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Authors: Dwitya Elvira, Eryati Darwin

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Background: Graves’ disease (GD) is an autoimmune thyroid disease. Imbalance of Th1/Th2 cells and T-regulatory (Treg)/Th17 cells was thought to play pivotal role in the pathogenesis of GD. Treg FoxP3 produced TGF-β to maintain regulatory function, and Th17 cells produced IL-17 as cytokines that were thought in mediating several autoimmune diseases. The aim of this study is to assess the role of IL-17 and TGF-β in the pathogenesis of GD and to investigate its correlation with Thyroid Stimulating Hormone Receptor Antibody (TRAb) and Treg FoxP3 expression. Method: 30 GD patients and 27 age and sex-matched controls were enrolled in this study. Diagnosis of GD was based on clinical and biochemical of GD. Serum IL-17, TGF-β, TRAb, and FoxP3 were measured by enzyme-linked immunosorbent assay (ELISA). Data were analyzed by using SPSS 21.0 (SPSS Inc.). Spearman rank correlation test was used for assessment of correlation. The statistical significance was accepted as P<0.05. Result: There was no significant correlation between IL-17 and TGF-β serum with expression of FoxP3 level in GD, but there was significant correlation between TGF-β and TRAb serum level (P<0.05). Serum levels of IL-17 and TGF-β were found to be elevated in patient group compared to control, where mean values of IL-17 were 14.43±2.15 pg/mL and TGF-β were 10.44±3.19 pg/mL in patients group; and in control group, level of IL-17 were 7.1±1.45 pg/mL and TGF-β were 4.95±1.35 pg/mL. Conclusion: Serum Il-17 and TGF-β were elevated in GD patients that reflect the role of inflammatory and regulatory cytokines activation in pathogenesis of GD. There was significant correlation between TGF-β and TRAb, revealing that Treg cytokines may play a role in pathogenesis of GD.

Keywords: IL-17, TGF-β, FoxP3, Graves’ disease.

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Authors: K. A. Ghazaryan, H. S. Movsesyan, N. P. Ghazaryan

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The present study was aimed in assessing the heavy metal pollution of the soils around Agarak copper-molybdenum mine complex and related environmental risks. This mine complex is located in the south-east part of Armenia, and the present study was conducted in 2013. The soils of the five riskiest sites of this region were studied: surroundings of the open mine, the sites adjacent to processing plant of Agarak copper-molybdenum mine complex, surroundings of Darazam active tailing dump, the recultivated tailing dump of “ravine - 2”, and the recultivated tailing dump of “ravine - 3”. The mountain cambisol was the main soil type in the study sites. The level of soil contamination by heavy metals was assessed by Contamination factors (Cf), Degree of contamination (Cd), Geoaccumulation index (I-geo) and Enrichment factor (EF). The distribution pattern of trace metals in the soil profile according to Cf, Cd, I-geo and EF values shows that the soil is much polluted. Almost in all studied sites, Cu, Mo, Pb, and Cd were the main polluting heavy metals, and this was conditioned by Agarak copper-molybdenum mine complex activity. It is necessary to state that the pollution problem becomes pressing as some parts of these highly polluted region are inhabited by population, and agriculture is highly developed there; therefore, heavy metals can be transferred into human bodies through food chains and have direct influence on public health. Since the induced pollution can pose serious threats to public health, further investigations on soil and vegetation pollution are recommended. Finally, Cf calculating based on distance from the pollution source and the wind direction can provide more reasonable results.

Keywords: Agarak copper-molybdenum mine complex, heavy metals, soil contamination, enrichment factor, Armenia.

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: CNC milling, CNC turning, surface roughness, Taguchi analysis.

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Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m². 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal breast cancer, hormone sensitivity, Iraq, risk factors.

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Authors: H. M. Haytham, E. A. Azza, E.S. Mohamed, E. G. Nesreen

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Thoracotomy is a great surgery that has serious pulmonary complications, so purpose of this study was to determine the response of diaphragmatic excursion to inspiratory muscle trainer post thoracotomy. Thirty patients of both sexes (16 men and 14 women) with age ranged from 20 to 40 years old had done thoracotomy participated in this study. The practical work was done in cardiothoracic department, Kasr-El-Aini hospital at faculty of medicine for individuals 3 days Post operatively. Patients were assigned into two groups: group A (study group) included 15 patients (8 men and 7 women) who received inspiratory muscle training by using inspiratory muscle trainer for 20 minutes and routine chest physiotherapy (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Group B (control group) included 15 patients (8 men and 7 women) who received the routine chest physiotherapy only (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Ultrasonography was used to evaluate the changes in diaphragmatic excursion before and after training program. Statistical analysis revealed a significant increase in diaphragmatic excursion in the study group (59.52%) more than control group (18.66%) after using inspiratory muscle trainer post operatively in patients post thoracotomy. It was concluded that the inspiratory muscle training device increases diaphragmatic excursion in patients post thoracotomy through improving inspiratory muscle strength and improving mechanics of breathing and using of inspiratory muscle trainer as a method of physical therapy rehabilitation to reduce post-operative pulmonary complications post thoracotomy.

Keywords: Diaphragmatic excursion, inspiratory muscle trainer, ultrasonography, thoracotomy.

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Authors: Abdulfatah Al-Jaradi, Marzoq Ali Odhah, Abdulnasser A. Haza’a

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Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of Antenatal Care (ANC) include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding ANC. Methodology: A descriptive knowledge, attitude, and practice (KAP) study was conducted in public hospitals in Sana'a City, Yemen. The study population included all pregnant women that intended to the prenatal department and clinical outpatient department; the final sample size was 371 pregnant women. A self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women had correct answers in total knowledge regarding ANC, and about two-thirds (67%) of pregnant women had performance practice regarding ANC and two-third (68%) of pregnant women had a positive attitude. Conclusions: More than three quarter of pregnant women had good knowledge level, most of pregnant women had moderate practice level, and more than two-thirds of pregnant women had a positive attitude regarding antenatal care. There was a statistically significant association between overall knowledge and practice level toward ANC and demographic characteristics of pregnant women, at P-value ≤ 0.05. Recommendations: we recommended more education and training courses, lecturers, and education sessions in clinical facilitators focused on ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.

Keywords: Antenatal care, knowledge, practice, attitude, pregnant women.

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Authors: Ákos Wolf, Richard P. Ray

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Due to the introduction of Eurocode 8, the structural design for seismic and dynamic effects has become more significant in Hungary. This has emphasized the need for more effort to describe the behavior of structures under these conditions. Soil conditions have a significant effect on the response of structures by modifying the stiffness and damping of the soil-structural system and by modifying the seismic action as it reaches the ground surface. Shear modulus (G) and shear wave velocity (v_s), which are often measured in the field, are the fundamental dynamic soil properties for foundation vibration problems, liquefaction potential and earthquake site response analysis. There are several laboratory and in-situ measurement techniques to evaluate dynamic soil properties, but unfortunately, they are often too expensive for general design practice. However, a significant number of correlations have been proposed to determine shear wave velocity or shear modulus from Cone Penetration Tests (CPT), which are used more and more in geotechnical design practice in Hungary. This allows the designer to analyze and compare CPT and seismic test result in order to select the best correlation equations for Hungarian soils and to improve the recommendations for the Hungarian geologic conditions. Based on a literature review, as well as research experience in Hungary, the influence of various parameters on the accuracy of results will be shown. This study can serve as a basis for selecting and modifying correlation equations for Hungarian soils. Test data are taken from seven locations in Hungary with similar geologic conditions. The shear wave velocity values were measured by seismic CPT. Several factors are analyzed including soil type, behavior index, measurement depth, geologic age etc. for their effect on the accuracy of predictions. The final results show an improved prediction method for Hungarian soils

Keywords: CPT correlation, dynamic soil properties, seismic CPT, shear wave velocity.

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: Iris recognition, contrast stretching, gradient features, texture features, Euclidean metric.

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Authors: Ademuyiwa, M. O., Sanni, S. A.

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The importance of maternal nutritional practices during pregnancy cannot be overemphasized. This paper assessed the consumption pattern and dietary practices of 50 pregnant women selected using purposive sampling technique from three health care centres (Primary Health Care Centre, Obantoko; Primary Health Care Centre Alabata; and the General Hospital, Odeda) in Odeda Local Government Area of Ogun State, Nigeria. Structured questionnaire was used to elicit information on socioeconomic status, consumption pattern and dietary practices. Data were analyzed using the Statistical Package for Social Sciences (SPSS, 17). The results indicated that about 58% of the pregnant women were below the age of 30 while 42% were ages 28-40 years. Only 16% had tertiary education while (38%) had secondary education, 52% earn income through petty trading. On food intake, 52% got their energy source from rice on a daily basis, followed by pap (38%) and eko (34%). For protein intake, 36% consumed bean cake on a daily basis while 66% consumed moinmoin 2-3 times a week. Orange (48%) and Green Leafy vegetable (40%) accounted for the mostly consumed fruit and vegetable on daily basis. In terms of animal origin, fish (76%), meat (58%) and eggs (30%) were consumed daily, while chicken and snail were consumed occasionally by 54% and 42%, respectively. Forty-six percent (46%) of the pregnant women eat more than three times daily; while 60% of the women eat outside their homes with 42% respondents eat out lunch and only two percent least eaten out dinner. It is important to increase in awareness campaign to sensitize the pregnant women on the importance of good nutrition especially fruits, vegetables and dairy products. 

Keywords: Consumption Pattern, Dietary Practices, Pregnant, Women, Nigeria.

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: Data availability, Iraq, road safety.

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Authors: A. Camões, M. Ferreira Dias, M. Amorim

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In recent years, the social economy is increasingly seen as a viable means to address social problems. Social enterprises, as well as public projects and initiatives targeted to meet social purposes, offer organizational models that assume heterogeneity, flexibility and adaptability to the ‘real world and real problems’. Despite the growing popularity of social initiatives, decision makers still face a paucity in what concerns the available models and tools to adequately assess its sustainability, and its impacts, notably the nature of its contribution to economic growth. This study was carried out at the local level, by analyzing the social impact initiatives and projects promoted by the Municipality of Albergaria-a-Velha (Câmara Municipal de Albergaria-a-Velha -CMA), a municipality of 25,000 inhabitants in the central region of Portugal. This work focuses on the challenges related to the qualifications and employability of citizens, which stands out as one of the key concerns in the Portuguese economy, particularly expressive in the context of small-scale cities and inland territories. The study offers a characterization of the Municipality, its socio-economic structure and challenges, followed by an exploratory analysis of multiple sourced data, collected from the CMA's documental sources as well as from privileged informants. The purpose is to conduct detailed analysis of the CMA's social projects, aimed at characterizing its potential impact for the model of qualifications and employability of the citizens of the Municipality. The study encompasses a discussion of the socio-economic profile of the municipality, notably its asymmetries, the analysis of the social projects and initiatives, as well as of data derived from inquiry actors involved in the implementation of the social projects and its beneficiaries. Finally, the results obtained with the Better Life Index will be included. This study makes it possible to ascertain if what is implicit in the literature goes to the encounter of what one experiences in reality.

Keywords: Measurement, municipalities, social economy, social impact.

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Authors: Ahmad Aljaafreh

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This paper proposes a hierarchical hidden Markov model (HHMM) to model the detection of M vehicles in a wireless sensor network (WSN). The HHMM model contains an extra level of hidden Markov model to model the temporal transitions of each state of the first HMM. By modeling the temporal transitions, only those hypothesis with nonzero transition probabilities needs to be tested. Thus, this method efficiently reduces the computation load, which is preferable in WSN applications.This paper integrates several techniques to optimize the detection performance. The output of the states of the first HMM is modeled as Gaussian Mixture Model (GMM), where the number of states and the number of Gaussians are experimentally determined, while the other parameters are estimated using Expectation Maximization (EM). HHMM is used to model the sequence of the local decisions which are based on multiple hypothesis testing with maximum likelihood approach. The states in the HHMM represent various combinations of vehicles of different types. Due to the statistical advantages of multisensor data fusion, we propose a heuristic based on fuzzy weighted majority voting to enhance cooperative classification of moving vehicles within a region that is monitored by a wireless sensor network. A fuzzy inference system weighs each local decision based on the signal to noise ratio of the acoustic signal for target detection and the signal to noise ratio of the radio signal for sensor communication. The spatial correlation among the observations of neighboring sensor nodes is efficiently utilized as well as the temporal correlation. Simulation results demonstrate the efficiency of this scheme.

Keywords: Classification, decision fusion, fuzzy logic, hidden Markov model

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Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: Education, Information Technologies, IDT, awareness.

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: C. A. Oloo, C. Ojwang

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The performances of small and medium enterprises have stagnated in the last two decades. This has mainly been due to the emergence of HIV / Aids. The disease has had a detrimental effect on the general economy of the country leading to morbidity and mortality of the Kenyan workforce in their primary age. The present study sought to establish the economic impact of HIV / Aids on the micro-enterprise development in Obunga slum – Kisumu, in terms of production loss, increasing labor related cost and to establish possible strategies to address the impact of HIV / Aids on microenterprises. The study was necessitated by the observation that most micro-enterprises in the slum are facing severe economic and social crisis due to the impact of HIV / Aids, they get depleted and close down within a short time due to death of skilled and experience workforce. The study was carried out between June 2008 and June 2009 in Obunga slum. Data was subjected to computer aided statistical analysis that included descriptive statistic, chi-squared and ANOVA techniques. Chi-squared analysis on the micro-enterprise owners opinion on the impact of HIV / Aids on depletion of microenterprise compared to other diseases indicated high levels of the negative effects of the disease at significance levels of P<0.01. Analysis of variance on the impact of HIV / Aids on the performance and productivity of micro-enterprises also indicated a negative effect on the general performance of micro-enterprise at significance levels of P<0.01. Therefore reducing the negative impacts of HIV/Aids on micro-enterprise development, there is need to improve the socioeconomic environment, mobilize donors and stake holders in training and funding, and review the current strategies for addressing the disease. Further conclusive research should also be conducted on a bigger scale.

Keywords: Entrepreneurship, HIV-AIDS, Micro-enterprise, Poverty.

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Authors: Mohammad D. AL-Tahat, Shahnaz M. Alkhalil

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International markets driven forces are changing continuously, therefore companies need to gain a competitive edge in such markets. Improving the company's products, processes and practices is no longer auxiliary. Lean production is a production management philosophy that consolidates work tasks with minimum waste resulting in improved productivity. Lean production practices can be mapped into many production areas. One of these is Manufacturing Equipment and Technology (MET). Many lean production practices can be implemented in MET, namely, specific equipment configurations, total preventive maintenance, visual control, new equipment/ technologies, production process reengineering and shared vision of perfection.The purpose of this paper is to investigate the implementation level of these six practices in Jordanian industries. To achieve that a questionnaire survey has been designed according to five-point Likert scale. The questionnaire is validated through pilot study and through experts review. A sample of 350 Jordanian companies were surveyed, the response rate was 83%. The respondents were asked to rate the extent of implementation for each of practices. A relationship conceptual model is developed, hypotheses are proposed, and consequently the essential statistical analyses are then performed. An assessment tool that enables management to monitor the progress and the effectiveness of lean practices implementation is designed and presented. Consequently, the results show that the average implementation level of lean practices in MET is 77%, Jordanian companies are implementing successfully the considered lean production practices, and the presented model has Cronbach-s alpha value of 0.87 which is good evidence on model consistency and results validation.

Keywords: Lean Production, SME applications, Visual Control, New equipment/technologies, Specific equipment configurations, Jordan

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Authors: Mohamed K. Shahin, Ahmed M. Badawi, Mohamed E. M. Rasmy

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Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Keywords: Unimodal, Multi-Modal, Biometric System, NIR Imaging, Dorsal Hand Geometry, Fingerprint, Whole Hands, Feature Extraction, Feature Fusion, Score Fusion

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Authors: Ahmad Attiq Al-Ogaibi, Ahmad Sharieh, Moh’d Belal Al-Zoubi, R. Bremananth

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In pattern clustering, nearest neighborhood point computation is a challenging issue for many applications in the area of research such as Remote Sensing, Computer Vision, Pattern Recognition and Statistical Imaging. Nearest neighborhood computation is an essential computation for providing sufficient classification among the volume of pixels (voxels) in order to localize the active-region-of-interests (AROI). Furthermore, it is needed to compute spatial metric relationships of diverse area of imaging based on the applications of pattern recognition. In this paper, we propose a new methodology for finding the nearest neighbor point, depending on making a virtually grid of a hexagon cells, then locate every point beneath them. An algorithm is suggested for minimizing the computation and increasing the turnaround time of the process. The nearest neighbor query points Φ are fetched by seeking fashion of hexagon holistic. Seeking will be repeated until an AROI Φ is to be expected. If any point Υ is located then searching starts in the nearest hexagons in a circular way. The First hexagon is considered be level 0 (L0) and the surrounded hexagons is level 1 (L1). If Υ is located in L1, then search starts in the next level (L2) to ensure that Υ is the nearest neighbor for Φ. Based on the result and experimental results, we found that the proposed method has an advantage over the traditional methods in terms of minimizing the time complexity required for searching the neighbors, in turn, efficiency of classification will be improved sufficiently.

Keywords: Hexagon cells, k-nearest neighbors, Nearest Neighbor, Pattern recognition, Query pattern, Virtually grid

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Authors: Kim H. K. Choy, Oliva H. K. Chu, W. Y. Keung, B. Lim, Winnie P. Y. Tang

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Background: The prevalence of workplace obesity is rising worldwide; therefore, the workplace is an ideal venue to implement weight control intervention. This pilot randomized controlled trial aimed to develop, implement, and evaluate a nutritional wellness program for obese health care providers working in a hospital. Methods: This hospital-based nutritional wellness program was an 8-week pilot randomized controlled trial for obese health care providers. The primary outcomes were body weight and body mass index (BMI). The secondary outcomes were serum fasting glucose, fasting cholesterol, triglyceride, high-density (HDL) and low-density (LDL) lipoprotein, body fat percentage, and body mass. Participants were randomly assigned to the intervention (n = 20) or control (n = 22) group. Participants in both groups received individual nutrition counselling and nutrition pamphlets, whereas only participants in the intervention group were given mobile phone text messages. Results: 42 participants completed the study. In comparison with the control group, the intervention group showed approximately 0.98 kg weight reduction after two months. Participants in intervention group also demonstrated clinically significant improvement in BMI, serum cholesterol level, and HDL level. There was no improvement of body fat percentage and body mass for both intervention and control groups. Conclusion: The nutritional wellness program for obese health care providers was feasible in hospital settings. Health care providers demonstrated short-term weight loss, decrease in serum fasting cholesterol level, and HDL level after completing the program.

Keywords: Health care provider, hospital, weight management, weight control.

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Authors: Mst. Nilufa Sultana, Shatirah Akib, Muhammad Aqeel Ashraf, Mohamed Roseli Zainal Abidin

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Most people today are aware that global climate change is not just a scientific theory but also a fact with worldwide consequences. Global climate change is due to rapid urbanization, industrialization, high population growth and current vulnerability of the climatic condition. Water is becoming scarce as a result of global climate change. To mitigate the problem arising due to global climate change and its drought effect, harvesting rainwater from green roofs, an environmentally-friendly and versatile technology, is becoming one of the best assessment criteria and gaining attention in Malaysia. This paper addresses the sustainability of green roofs and examines the quality of water harvested from green roofs in comparison to rainwater. The factors that affect the quality of such water, taking into account, for example, roofing materials, climatic conditions, the frequency of rainfall frequency and the first flush. A green roof was installed on the Humid Tropic Centre (HTC) is a place of the study on monitoring program for urban Stormwater Management Manual for Malaysia (MSMA), Eco-Hydrological Project in Kuala Lumpur, and the rainwater was harvested and evaluated on the basis of four parameters i.e., conductivity, dissolved oxygen (DO), pH and temperature. These parameters were found to fall between Class I and Class III of the Interim National Water Quality Standards (INWQS) and the Water Quality Index (WQI). Some preliminary treatment such as disinfection and filtration could likely to improve the value of these parameters to class I. This review paper clearly indicates that there is a need for more research to address other microbiological and chemical quality parameters to ensure that the harvested water is suitable for use potable water for domestic purposes. The change in all physical, chemical and microbiological parameters with respect to storage time will be a major focus of future studies in this field.

Keywords: Green roofs, INWQS, MSMA-SME, Rainwater harvesting.

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Authors: L. Basha, E. Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.

Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.

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