Hierarchical classification of liver tumor from CT images based on difference-of-features (DOF)

This manuscript presents an automated classification approach to classifying lesions into four categories of liver diseases, based on Computer Tomography (CT) images. The four diseases types are Cyst, Hemangioma, Hepatocellular carcinoma (HCC), and Metastasis. The novelty of the proposed approach is attributed to utilising the difference of features (DOF) between the lesion area and the surrounding normal liver tissue. The DOF (texture and intensity) is used as the new feature vector that feeds the classifier. The classification system consists of two phases. The first phase differentiates between Benign and Malignant lesions, using a Support Vector Machine (SVM) classifier. The second phase further classifies the Benign into Hemangioma or Cyst and the Malignant into Metastasis or HCC, using a Naïve Bayes (NB) classifier. The experimental results show promising improvements to classify the liver lesion diseases. Furthermore, the proposed approach can overcome the problems of varying intensity ranges, textures between patients, demographics, and imaging devices and settings

EFFECT OF RELATIVE HUMIDITY AND TEMPERATURE CONTROL ON IN-CABIN THERMAL COMFORT STATE

This dissertation discusses the effect of manipulating the relative humidity RH levels inside vehicular cabins on the thermal comfort and human occupants\u27 thermal sensation. Three different techniques are used to investigate this effect. Firstly, thermodynamic and psychometric analyses are used to incorporate the effect of changing RH along with the dry bulb temperature on the human comfort window. Specifically, the study computes the effect of changing the relative humidity on the amount of heat rejected from the passenger compartment and the effect on occupants comfort zone. A practical system implementation is also discussed in terms of an evaporative cooler design. Secondly, a 3-D finite difference simulation is used to predict the RH effects on the thermal sensation metrics. The study uses the Berkeley and the Fanger models to investigate the human comfort using four specific perspectives; (i) the effect on other environmental conditions, (ii) the effect on the body segments temperature variation within the cabin, (iii) the cabin local sensation (LS) and comfort (LC) for the different body segments; in addition to the overall sensation (OS) and overall comfort (OC), (iv) the human sensation is also measured by the Predicted Mean Value (PMV) and the Predicted Percentage Dissatisfied (PPD) indices during the summer and the winter periods following the Fanger model calculations. Thirdly, the analysis and modeling of the vehicular thermal comfort parameters is conducted using a set of designed experiments aided by thermography measurements. The experiments employed a full size climatic chamber to host the test vehicle, to accurately assess the transient and steady state temperature distributions of the test vehicle cabins. The experimental and simulation work show that controlling the RH levels along with the Dry Bulb Temperature helps the A/C system achieve the human comfort zone faster than the case if the RH value is not controlled. Also, the results show that changing the RH along with Dry Bulb Temperature inside vehicular cabins can improve the air conditioning efficiency by reducing the amount of heat removed. Finally, this work has developed the passenger thermal-comfort psychometric zones during summer and winter periods using Berkeley and Fanger models

Solar Cooling Technologies

This chapter describes different available technologies to provide the cooling effect by utilizing solar energy for both thermal and photovoltaic ways. Moreover, this chapter highlights the following points: (i) the main attributes for different solar cooling technologies to recognize the main advantages, challenges, disadvantages, and feasibility analysis; (ii) the need for further research to reduce solar cooling chiller manufacture costs and improve its performance; (iii) it provides useful information for decision-makers to select the proper solar cooling technology for specific application. Furthermore, some references, which include investigation results, will be included. A conclusion about the main gained investigation results will summarize the investigation results and the perspectives of such technologies

Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications

Computer-aided classification of liver lesions using contrasting features difference

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate. This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings

Experimental and numerical study to develop TRANSYS model for an active flat plate solar collector with an internally serpentine tube receiver

Flat solar collectors are extensively utilized in various domestic and industrial applications to reduce energy consumption. In this study, an-active flat plate solar collector (FPSC) with an internal absorber tube receiver was fabricated and tested in Al-Samawa city, Iraq (latitude 31.19°N and longitude 45.17°E). The ambient temperature and incident solar radiation at the experimental location were reached 39 °C and 840 W/m2, respectively. In this study, the number of riser tubes connected to headers that are covered with a glass sheet in a conventional FPSC were replaced with a single serpentine-shaped collector tube covered with a plastic sheet. The proposed solar collector used a smooth copper tube with internal and exterior diameters of 9.5 and 12 mm, respectively, and a total length of 1000 mm. A TRNSYS model of a flat plate collector integrated with an absorber tube was developed, simulated, and validated using the experimental data. Temperature and flow rate data were obtained concurrently throughout the experiments to evaluate the performance of the fabricated solar collector. The temperature at the solar collector input stayed relatively constant at 37.7 °C, and the water flow rate remained constant at 0.75 L/min. The results indicated that the temperature at the solar collector output ranged from 52 to 61 °C, with an average of 58 °C. The efficiency of the proposed solar collector ranges from approximately 45% to 67%, with an average of 58%. Overall, the simulation results of the TRNSYS model are in excellent agreement with experimental data. The average discrepancy between the tests and simulations for temperature differential and collector efficiency is approximately 1%

3rd International Conference on Engineering and Science

The growing population and human activities of the world have significantly increased the demand for energy worldwide. Currently, fossil fuels serve as the main source of energy, however, their use contributes to environmental pollution due to greenhouse gas emissions. Hydrogen, on the other hand, is an energy carrier that can be derived from both renewable and non-renewable sources. In this study, a comprehensive overview of various renewable methods for producing hydrogen, including thermal decomposition, electrical analysis, optical decomposition, vital mechanisms, and thermal and biological chemical processes, is presented. Limitations to the expansion of the hydrogen economy, such as the lack of a clean hydrogen value chain, storage and transfer issues, high production costs, lack of international standards, and investment risks, are also identified. To address these challenges and encourage governments to reduce investment risks, this study offers recommendations based on the latest research in this field. Improving the technical aspects of hydrogen production mechanisms, establishing a clean hydrogen value chain, developing standardized procedures for storage and transfer, and increasing investment in research and development are some of the proposed solutions. These actions can pave the way for a more sustainable and clean energy future

Floating photovoltaics: assessing the potential, advantages, and challenges of harnessing solar energy on water bodies

The worldwide transition to a future with net-zero emissions depends heavily on solar energy. However, when land prices rise, and population density rises, the need for large land expanses to develop solar farms poses difficulties. Floating Photovoltaics (FPV) has come to light as a viable remedy to this problem. FPV, which includes mounting solar panels on bodies of water, is gaining popularity as a practical choice in many nations worldwide. A significant capacity of 404 GWp for producing clean energy might be attained by using FPV to cover only 1% of the world’s reservoirs. This review shows that FPV has several benefits over conventional ground-mounted PV systems. On the other hand, there is a large study void regarding the effects of FPV on water quality and aquatic ecosystems. This review looks at the most recent FPV research, including its advantages, disadvantages, and potential. It looks into the compatibility of various bodies of water, worldwide potential, system effectiveness, and the possibility of integrating different technologies with FPV