80 research outputs found
Bee Colony-Reptile Search Optimization Technique for Blood Cell Cancer Detection
No full textThe biosystem is a crucial system grounded in classification and detection, utilizing Artificial Intelligence (AI) approaches or metaheuristic techniques. Currently, cancer of the blood cells is among the deadliest cancers in the world. Acute lymphoblastic leukemia (ALL) is a cancer of blood cells that causes excessive proliferation of lymphocytes. It is extremely time-consuming and expensive to conduct diagnostic calculations. The number of platelets in a patient's blood is computed by a platelet count. A lacking number of platelets can indicate cancer, infection, or other health problems. A patient with too many platelets is at risk for blood strokes. A single drop of blood includes tens of thousands of platelets. The main goal of this paper is how to detect the features of blood cells and classify with predicting cancer type based on platelets analysis by using Bee Colony followed by Reptile Search Optimization (BCRSO) technique. According to the results, BCRSO algorithm performed better in terms of classification efficacy and accuracy rate than other algorithms. Based on simulation results, the proposed method is more effective than previously published research for classification optimization
Design of receiver RF front end for mm-Wave 5G applications
No full textRecently, the research emphasis has shifted towards 5G due to its potential to accommodate the increasing demand for data traffic, extensive interconnectivity of devices, and the emergence of numerous novel applications. Given the inadequacy of speed provided by spectrum resources in the lower frequency bands of 5G, a novel sub-generation utilizing millimeter wave frequencies has been introduced. The new sub-generation is called mm-wave 5G and provides higher bandwidth for faster speed and higher capacity. RF system architecture, circuits, and antenna innovation will be required to provide the requisite speed and capacity. In this paper the design challenges and trade-offs in RF front-end circuits and receiver sub-systems are discussed. Moreover, the massive multiple-input multiple-output (MIMO) techniques are examined. In addition, design, and simulation of key components in 5G mm-wave receiver, including the design of linear phased array antenna receiver and an analog-to-digital converter (ADC) is presented. Sigma-Delta (ΣΔM) Converters are a type of ADC with a technique that involves oversampling and shaping quantization noise to achieve a higher resolution which make it a best choice to be used in the design of the mm wave 5G communication applications. The proposed ΣΔM uses multistage architecture to provide high-order noise shaping and high resolution. The simulation results shows that the designed Cascade 2-2 MASH ΣΔ achieve a signal to noise ratio of 110(resolution of 16 bits)
Drought Monitor Creation using SMAP L4 Soil Moisture Data
No full textThe socioeconomic and ecological consequences of drought are substantial. Vigilance in soil moisture surveillance is instrumental for effectual drought governance. The manuscript delineates a novel stratagem to devise a drought surveillance mechanism deploying granular SMAP L4 soil moisture datasets. This technique introduces the computation of a Standardized Soil Moisture Index (SSMI) that segregates drought into quintuple classifications. Periodic, hebdomadal modifications reflect the dynamism in pedosphere aridity. Comparative analyses corroborate the congruence with extant aridity indicators, endorsing its utility in strategic drought response endeavours. The method's adaptability is noteworthy, as it permits employment in regions bereft of com-prehensive terrestrial monitoring systems
Techno-economic and Environmental Analysis of a Hybrid Renewable Energy System for Residential Homes
No full textHybrid renewable energy systems (HRESs) are becoming more prevalent as they are viewed as economic off-grid sources of clean energy that could help reduce rural electrification and global warming problems. This thesis aims to provide a techno-economic feasibility and environmental analysis of a HRES to be designed for meeting a daily load requirement of 389.4 kWh/day with a peak load of 82.71 kW, represented by the energy demand of thirty houses located in Al-Qurayyat city (near the Technical College for Boys), Al Jouf Province, KSA. Thus, the aim of this thesis coincides with the 2030 and 2060 visions of KSA, which promote sustainable energy solutions and net zero CO2 emissions, respectively. Moreover, the objectives of the research could be divided over two stages. First, a HRES consisting of PV, WT, a DG, converter and lead-acid BSS is considered. Simulation of the system is achieved by HOMER software to obtain the optimum configuration. After considering six arrangements, the results reveal that the ideal arrangement is indeed the PV/WT/DG/Converter/BSS with an optimized NPC and COE of 0.166/kWh while attaining a RF percentage of 92.8%. An alternative configuration, consisting of PV/WT/Converter/BSS would yield a 100% RF but with a NPC of 0.22/kWh. The technical results show that the proposed HRES produces a total annual energy of 285,750 kWh/year with the PV, WT, and DG contributing 91.2%, 5.21%, and 3.58%, correspondingly. Regarding the environmental assessment, the optimized hybrid system saves a total of 206,678 kg of greenhouse gases each year. In the second stage, the proposed HRES will be compared with another HRES comprised of CPV, WT, DG and BSS. The objective is to determine the effectiveness of utilizing CPVs in hybrid systems over regular PVs in order to determine the more economic solar technology to be incorporated in the HRES, and this is where the novelty of the study lies. The CPV-HRES has a NPC and COE of 0.406/kWh, correspondingly with an annual energy generation of 434,731 kWh/year. Hence, the PV technology is the more economic choice even though it has a lower energy yield than CPV
Electrical Energy Consumption Forecasting Analysis Based on Conventional and Artificial Intelligence Methods: A Comparison
No full textArtificial intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review the classical techniques and the emerging new techniques based on AI of the building electrical energy consumption forecasting. The advantages of AI-based techniques over the classical are that AI methods can handle a large amount of data yet gives accurate results, the results can be found very quickly, in addition to AI having the ability to solve complex nonlinear patterns of raw data. This paper will discuss several studies using different models of forecasting based on AI and compare them. It will also discuss several studies using different models of forecasting based on AI and compare between them, coming up with the conclusion that the model that achieved the lowest MAPE is ANN with 0.928\%
Wideband Spectrum Sensing for Cognitive Radio Using Under-sampled Successive Approximation ADC
No full textThe radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling frequency is required with primarily complex and energy inefficient designs. In this paper, a wideband spectrum sensing design is proposed utilizing Compressive Sensing, which enables sampling far below the Nyquist rate and thus drastically reduces power consumption, complexity and cost of the system. The proposed design is an 8-bit Under-sampled Successive Approximation Register (SAR) ADC. The core blocks of an SAR ADC design are the SAR Logic Block and the comparator, both of which were designed and simulated in Cadence software. The design was implemented in targeted technology of 65 nm standard CMOS technology. An optimization method suitable for VLSI implementation, termed Orthogonal Matching Pursuit (OMP), was utilized for spectrum recovery. Following comparative analyses with previously published studies, we demonstrate significant improvements in terms of speed and chip area of the SAR ADC design proposed herein
Intelligent Energy Management Mechanisms for Electric Vehicles: A Review
No full textThis paper investigates intelligent methods used for energy management (EM) in Electric Vehicles (EV). The key role of EM in EVs to increase the performance of the vehicle and reduce Fuel Consumption (FC) thus producing less greenhouse effect. However, the used tactics had limitations. An introduced model of Intelligent Energy Management System (IEMS) for Plug-in hybrid electric vehicles (PHEVs) was efficient for FC reduction. Whereas for IEMS Based on Kalman Filtering showed a low percentage of error. While EM using Tags Threshold Admission And Greedy Scheduling improves EV’s performance, but it can only manage energy per one EV. Another model of IEMS for hybrid electric vehicles HEV had high reliability since it was performed using various models. Additionally, EMS based on global optimization has reduced FC through Linear programming and Dynamic Programming. Moreover, Particle Swarm Optimization gave less FC by 10.26\% when tested and compared to Torque Efficiency Optimization. However, Artificial Neural Networks (ANN) produced low error since it’s self-learning. ANN works better than Coulomb Counting and Extended Kalman Filter. EM using deep learning with ANN model is useful; it can save a percentage of energy each time it’s tested. Furthermore, Simulation outputs of Deep Reinforcement Learning based EMS had better performance than the rule-based EMS in FC
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