The fifth-generation(5G)wireless technology is the most recent standardization in communication services of interest across the globe.The concept of Multiple-Input-Multiple-Output antenna(MIMO)systems has recently bee...The fifth-generation(5G)wireless technology is the most recent standardization in communication services of interest across the globe.The concept of Multiple-Input-Multiple-Output antenna(MIMO)systems has recently been incorporated to operate at higher frequencies without limitations.This paper addresses,design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz,respectively for 5G millimeter(mm)-wave applications.The proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53×7.85×0.8 mm^(3).The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance microstrip line.It also has an I-shaped slot and two electromagnetically coupled parasitic slotted components.This design is initially constructed as a single-element structure and proceeded to a six-element MIMO antenna configuration with overall dimensions of 50×35×0.8 mm^(3).The simulated prototype is fabricated and measured for analyzing its performance characteristics,along with MIMO antenna diversity performance factors making the proposed antenna suitable for 5G mm-wave and 5G-operated handheld devices.展开更多
Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were...Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were following ancestral patterns,which could sometimes lead to the wrong selection of crops.In this research work,the feature selection method is adopted to improve the performance of the classification.The most relevant features from the dataset are obtained using a Probabilistic Feature Selection(PFS)approach,and classifi-cation is done using a Neural Fuzzy Classifier(NFC).Scaling Conjugate Gradient(SCG)optimization method is used to update the weights.The data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and rainfall.The proposed method recommends suitable crops for cultivation based on site-specific para-meters.Experimental result shows that the proposed method provides high accu-racy and efficiency as compared to existing methodologies.展开更多
文摘The fifth-generation(5G)wireless technology is the most recent standardization in communication services of interest across the globe.The concept of Multiple-Input-Multiple-Output antenna(MIMO)systems has recently been incorporated to operate at higher frequencies without limitations.This paper addresses,design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz,respectively for 5G millimeter(mm)-wave applications.The proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53×7.85×0.8 mm^(3).The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance microstrip line.It also has an I-shaped slot and two electromagnetically coupled parasitic slotted components.This design is initially constructed as a single-element structure and proceeded to a six-element MIMO antenna configuration with overall dimensions of 50×35×0.8 mm^(3).The simulated prototype is fabricated and measured for analyzing its performance characteristics,along with MIMO antenna diversity performance factors making the proposed antenna suitable for 5G mm-wave and 5G-operated handheld devices.
文摘Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were following ancestral patterns,which could sometimes lead to the wrong selection of crops.In this research work,the feature selection method is adopted to improve the performance of the classification.The most relevant features from the dataset are obtained using a Probabilistic Feature Selection(PFS)approach,and classifi-cation is done using a Neural Fuzzy Classifier(NFC).Scaling Conjugate Gradient(SCG)optimization method is used to update the weights.The data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and rainfall.The proposed method recommends suitable crops for cultivation based on site-specific para-meters.Experimental result shows that the proposed method provides high accu-racy and efficiency as compared to existing methodologies.
