Factors That Influence Rural Entrepreneurship: Case-Study Evidence from Torbat-E Heydarie, Kadkan District

Entrepreneurship is an important instrument in planning and realizing rural community development. Owing to current problems in societies, focusing on the rural entrepreneurship is of utmost importance. Entrepreneurship by creating new opportunities for employment and income plays an important role in improving socioeconomic conditions of villages. The aim of this study is to assess the factors influencing the development of rural entrepreneurship in a case study of villages in Torbat-e Heydarieh, Kadkan district. The research method was descriptive-analytic, and the data collection method was library and field studies. For data analysis, One-sample t-test with principal component analysis was used. The statistical population of the study was the villagers of Kadkan district of Torbat-e Heydarieh, from which 240 people were asked to complete a questionnaire. The validity of the questionnaire was evaluated using the Content and face validity with expert judgement. Reliability of the questionnaire was examined by Cronbach's alpha coefficient which for all studied domains was above 0.75 which indicated that questionnaire was satisfactory. The results indicated that economic factor was the most influential issue in the rural entrepreneurship. The results also showed that rural entrepreneurship provides a good context for creating jobs in agricultural and non-agricultural sectors and it is an important factor for achieving sustainable rural development

Effect of operational parameters and internal recycle on rhenium solvent extraction from leach liquors using a mixer-settler

AbstractThe extraction of rhenium from molybdenite roasting dust leach solution was performed using a mixer-settler extractor by tributyl phosphate (TBP) diluted in kerosene as the extractant. In the single-stage extraction experiments, effect of the aqueous to organic phase ratios, Qa/Qo, and the number of extraction stages, N, on the rhenium extraction was studied. It was found that using the phase ratio of 1:1 in a two-stage extraction, 87.5% depletion of rhenium was obtained. The comparison of experimental results with the continuous co-current extraction showed a good agreement. The effect of internal recycle of organic phase was investigated in the phase ratio of 1:1 by changing the flow rate ratio of recycle-to-fresh organic phase, Qro/Qfo. The optimum performance was achieved in the phase ratio, Qro/Qfo, equal to 3:7. It was found that improvement in the performance of the mixer-settler for the rhenium-TBP system can be obtained in the phase ratio of 1:1when Qro/Qfo = 3:7

Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar

In this paper, we use a low-cost low-power mm-wave frequency modulated continuous wave (FMCW) radar for the in-vehicle occupant detection. We propose an algorithm using Capon filter for the joint range-azimuth estimation. Then, the minimum necessary features are extracted to train machine learning classifiers to have reasonable computational complexity while achieving high accuracy. In addition, experiments were carried out in a minivan to detect occupancy of each row using support vector machine (SVM). Finally, our proposed system achieved 97.8% accuracy on average in finding the defined scenarios. Moreover, the system can correctly identify if the vehicle is occupied or not with 100% accuracy

Prediction of fracture dip using artificial neural networks

Fracture characterization and fracture dip prediction can provide the desirable information about the fractured reservoirs. Fractured reservoirs are complicated and recent technology sometimes takes time and cost to provide all the desired information about these types of reservoirs. Core recovery has hardly been well in a highly fractured zone, hence, fracture dip measured from core sample is often not specific. Data prediction technology using Artificial Neural Networks (ANNs) can be very useful in these cases. The data related to undrilled depth can be predicted in order to achieve a better drilling operation, or maybe sometimes a group of data is missed then the missed data can be predicted using the other data. Consequently, this study was conducted to introduce the application of ANNs for fracture dip data prediction in fracture characterization technology. ANNs are among the best available tools to generate linear and nonlinear models and they are computational devices consisting of groups of highly interconnected processing elements called neurons, inspired by the scientists' interpretation of the architecture and functioning of the human brain. A feed forward Back Propagation Neural Network was run to predict the fractures dip angle for the third well using the image logs data of other two wells nearby. The predicted fracture dip data was compared with the fracture dip data from image logs of the third well to verify the usefulness of the ANNs. According to the obtained results, it is concluded that the ANN can be used successfully for modeling fracture dip data of the three studied wells. High correlation coefficients and low prediction errors obtained confirm the good predictive ability of ANN model, which the correlation coefficients of training and test sets for the ANN model were 0.95 and 0.91, respectively. Significantly, a non-linear approach based on ANNs allows to improve the performance of the fracture characterization technology

Factores que influyen en el espíritu empresarial rural: evidencia de estudios de caso de Torbat-E Heydarie, distrito de Kadkan

Entrepreneurship is an important instrument in planning and realizing rural community development. Owing to current problems in societies, focusing on the rural entrepreneurship is of utmost importance. Entrepreneurship by creating new opportunities for employment and income plays an important role in improving socioeconomic conditions of villages. The aim of this study is to assess the factors influencing the development of rural entrepreneurship in a case study of villages in Torbat-e Heydarieh, Kadkan district. The research method was descriptive-analytic, and the data collection method was library and field studies. For data analysis, One-sample t-test with principal component analysis was used. The statistical population of the study was the villagers of Kadkan district of Torbat-e Heydarieh, from which 240 people were asked to complete a questionnaire. The validity of the questionnaire was evaluated using the Content and face validity with expert judgement. Reliability of the questionnaire was examined by Cronbach's alpha coefficient which for all studied domains was above 0.75 which indicated that questionnaire was satisfactory. The results indicated that economic factor was the most influential issue in the rural entrepreneurship. The results also showed that rural entrepreneurship provides a good context for creating jobs in agricultural and non-agricultural sectors and it is an important factor for achieving sustainable rural development.El espíritu empresarial es un instrumento importante en la planificación y realización del desarrollo de la comunidad rural. Debido a los problemas actuales de las sociedades, es de suma importancia centrarse en el espíritu empresarial rural. El espíritu empresarial mediante la creación de nuevas oportunidades de empleo e ingresos juega un papel importante en la mejora de las condiciones socioeconómicas de las aldeas. El objetivo de este estudio es evaluar los factores que influyen en el desarrollo del espíritu empresarial rural en un estudio de caso de pueblos de Torbat-e Heydarieh, distrito de Kadkan. El método de investigación fue descriptivo-analítico, y el método de recolección de datos fue biblioteca y estudios de campo. Para el análisis de datos, se utilizó la prueba t de una muestra con análisis de componentes principales. La población estadística del estudio fueron los habitantes del distrito de Kadkan de Torbat-e Heydarieh, de los cuales se pidió a 240 personas que completaran un cuestionario. La validez del cuestionario se evaluó mediante el contenido y la validez aparente con juicio de expertos. La confiabilidad del cuestionario se examinó mediante el coeficiente alfa de Cronbach, que para todos los dominios estudiados fue superior a 0,75, lo que indicó que el cuestionario era satisfactorio. Los resultados indicaron que el factor económico fue el tema más influyente en el emprendimiento rural. Los resultados también mostraron que el espíritu empresarial rural proporciona un buen contexto para la creación de puestos de trabajo en los sectores agrícolas y no agrícolas y es un factor importante para lograr el desarrollo rural sostenible

Remote vital signs monitoring using a mm-wave FMCW radar

A vision on the migration from contact standard health monitoring measurement devices to non-contact measurement technologies has gained a tremendous attention in literature and in industry. A promising method for realizing the remote measurement of vital signs is using electromagnetic radars such as frequency modulated continuous wave (FMCW) radars. However, using these radars has challenges to precisely acquire the respiration and heart rates. A solution for higher accurate measurement of the vital signs can be the use of mm-wave frequencies, which gives a high-resolution sensing of displacements in an environment in the order of sub-mm changes. On the other hand, being in mm-wave bands increases both hardware and signal processing designs and implementations. In this work, a mm-wave radar is used to monitor the breathing and the heart rates as well as their waveforms for further clinical diagnostics. To that end, we established a complete analysis of the FMCW radars principles by considering hardware impairments. The analysis considers the effect of antenna coupling, RF cross-talk, stationary clutters, phase noise, IQ imbalances, and the thermal noise. Also, the effect of the individual hardware imperfections on the phase quality is shown by simulations and experiments. The simulations are carried out with a Matlab Simulink model. For the experiments, Texas Instruments (TI) mm-wave FMCW radars have been used. To earn insight into vital signs monitoring, different experiments are designed. In the experiments, the effect of the thermal instability of the RF parts on the phase is shown. In addition, to mimic the behaviour of the chest vibration due to respiration and the heartbeats, a two-pendulum system is designed and tested. Particularly, the pendulum system performance in terms of vibration frequency estimations of the two pendulums versus distance is then measured. In the simulations, the system performance is obtained for different signal to noise ratios (SNR) and different phase noise levels, as well as different stationary clutters. Finally, to test the TI sensors for different directions to the subjects, Hexoskin smart garment is used as a reference sensor, which is a reliable commercial product. Our results show great system improvement in terms of accuracy of the vital signs detection in comparison to other similar research. For different sleep positions, the accuracy of HR and BR are greater than 94\% and 96\%, respectively. In addition to detecting the vital rates, we have shown that their waveforms can also be reconstructed by using an adaptive optimum filter

Assessing the factors affecting the development of rural entrepreneurship: A case study of villages in Torbat-e Heydarieh, Kadkan district

Entrepreneurship is one of the most important tools for planning and achieving the development of rural communities. Today, due to the problems in these communities, attention and emphasis on rural entrepreneurship is very important; because entrepreneurship can with creation an effective role in improving the economic and living conditions of villages by creating new employment and income opportunities. This article has been written with the aim of evaluating the factors affecting the development of rural entrepreneurship in a case study of villages in Torbat-e Heydarieh, Kadkan district. The research method was descriptive-analytical and the data collection method was library and field. One-sample t-test with principal component analysis was used to analyze the data. The statistical population of the study was the villagers of Kadkan district of Torbat-e Heydarieh, from which 240 people were selected as a sample and they were asked to complete a questionnaire. To assess the validity of the questionnaire, the content and face validity technique was used with the judgment of experts on research questions. The reliability of the research instrument was determined using Cronbach's alpha coefficient, which is above 0.75 for all dimensions and indicates the desirable capability of the questionnaire. The results showed that among the factors affecting entrepreneurship, the economic factor is the most influential factor in the study area. The results also showed that rural entrepreneurship is one of the suitable fields for creating employment in agricultural and non-agricultural sectors and one of the important factors in achieving sustainable development in rural areas.

Fracture modeling in oil and gas reservoirs using image logs data and petrel software

The purpose of modelling the fractures is to create simulation properties with the power to predict the reservoir behaviour. Petrel software is one of the best softwares in the market that can do this task very well, but there is no available educational paper for every researcher. Therefore, in this work, a fracture modelling job was done in one of the most important Iranian fields using Petrel software and image log data. The purpose of this work was to determine the new information of the fractures in Gachsaran field and also to prepare a valuable educational paper for other researchers who are interested to learn about the fracture modelling. This work revealed that in this field, the longitudinal fractures had been parallel to minimum stress (Zagros trend), fracture intensity was the nearest to the major fault and northern flank, fracture porosity was 0-7%, fracture permeability was 0-6000 MD, and more valuable information is provided in this paper

A new technique to predict the fractures DIP using artificial neural networks and image logs data

Fractures provide the place for oil and gas to be reserved and they also can provide the pathway for them to move into the well, so having a proper knowledge of them is essential and every year the companies try to improve the existed softwares in this technology. In this work, the new technique is introduced to be added as a new application to the existed softwares such as Petrel and geoframe softwares. The data used in this work are image logs and the other geological logs data of tree wells located in Gachsaran field, wells number GS-A, GS-B and GS-C. The new technique by using the feed-forward artificial neural networks (ANN) with back-propagation learning rule can predict the fracture dip data of the third well using the data from the other 2 wells. The result obtained showed that the ANN model can simulate the relationship between fractures dips in these 3 wells which the multiple R of training and test sets for the ANN model is 0.95099 and 0.912197, respectively