| 1. |
- Ahmad, Waqas, et al.
(författare)
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Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework
- 2019
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Ingår i: IEEE Access. - 2169-3536. ; 7, s. 143002-143014
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Tidskriftsartikel (refereegranskat)abstract
- The acquisition of the spatial and angular information of a scene using light eld (LF) technologies supplement a wide range of post-processing applications, such as scene reconstruction, refocusing, virtual view synthesis, and so forth. The additional angular information possessed by LF data increases the size of the overall data captured while offering the same spatial resolution. The main contributor to the size of captured data (i.e., angular information) contains a high correlation that is exploited by state-of-the-art video encoders by treating the LF as a pseudo video sequence (PVS). The interpretation of LF as a single PVS restricts the encoding scheme to only utilize a single-dimensional angular correlation present in the LF data. In this paper, we present an LF compression framework that efciently exploits the spatial and angular correlation using a multiview extension of high-efciency video coding (MV-HEVC). The input LF views are converted into multiple PVSs and are organized hierarchically. The rate-allocation scheme takes into account the assigned organization of frames and distributes quality/bits among them accordingly. Subsequently, the reference picture selection scheme prioritizes the reference frames based on the assigned quality. The proposed compression scheme is evaluated by following the common test conditions set by JPEG Pleno. The proposed scheme performs 0.75 dB better compared to state-of-the-art compression schemes and 2.5 dB better compared to the x265-based JPEG Pleno anchor scheme. Moreover, an optimized motionsearch scheme is proposed in the framework that reduces the computational complexity (in terms of the sum of absolute difference [SAD] computations) of motion estimation by up to 87% with a negligible loss in visual quality (approximately 0.05 dB).
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| 2. |
- Ahmed Waqas, Hafiz, et al.
(författare)
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Performance Prediction of Hybrid Bamboo-Reinforced Concrete Beams Using Gene Expression Programming for Sustainable Construction
- 2023
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Ingår i: Materials. - : MDPI. - 1996-1944. ; 16:20
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Tidskriftsartikel (refereegranskat)abstract
- The building and construction industry’s demand for steel reinforcement bars has increased with the rapid growth and development in the world. However, steel production contributes to harmful waste and emissions that cause environmental pollution and climate change-related problems. In light of sustainable construction practices, bamboo, a readily accessible and ecofriendly building material, is suggested as a viable replacement for steel rebars. Its cost-effectiveness, environmental sustainability, and considerable tensile strength make it a promising option. In this research, hybrid beams underwent analysis through the use of thoroughly validated finite element models (FEMs), wherein the replacement of steel rebars with bamboo was explored as an alternative reinforcement material. The standard-size beams were subjected to three-point loading using FEMs to study parameters such as the load–deflection response, energy absorption, maximum capacity, and failure patterns. Then, gene expression programming was integrated to aid in developing a more straightforward equation for predicting the flexural strength of bamboo-reinforced concrete beams. The results of this study support the conclusion that the replacement of a portion of flexural steel with bamboo in reinforced concrete beams does not have a detrimental impact on the overall load-bearing capacity and energy absorption of the structure. Furthermore, it may offer a cost-effective and feasible alternative.
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| 3. |
- Hassan, A., et al.
(författare)
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High Efficiency Video Coding (HEVC)–Based Surgical Telementoring System Using Shallow Convolutional Neural Network
- 2019
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Ingår i: Journal of digital imaging. - : Springer Science and Business Media LLC. - 0897-1889 .- 1618-727X. ; 32:6, s. 1027-1043
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Tidskriftsartikel (refereegranskat)abstract
- Surgical telementoring systems have gained lots of interest, especially in remote locations. However, bandwidth constraint has been the primary bottleneck for efficient telementoring systems. This study aims to establish an efficient surgical telementoring system, where the qualified surgeon (mentor) provides real-time guidance and technical assistance for surgical procedures to the on-spot physician (surgeon). High Efficiency Video Coding (HEVC/H.265)–based video compression has shown promising results for telementoring applications. However, there is a trade-off between the bandwidth resources required for video transmission and quality of video received by the remote surgeon. In order to efficiently compress and transmit real-time surgical videos, a hybrid lossless-lossy approach is proposed where surgical incision region is coded in high quality whereas the background region is coded in low quality based on distance from the surgical incision region. For surgical incision region extraction, state-of-the-art deep learning (DL) architectures for semantic segmentation can be used. However, the computational complexity of these architectures is high resulting in large training and inference times. For telementoring systems, encoding time is crucial; therefore, very deep architectures are not suitable for surgical incision extraction. In this study, we propose a shallow convolutional neural network (S-CNN)–based segmentation approach that consists of encoder network only for surgical region extraction. The segmentation performance of S-CNN is compared with one of the state-of-the-art image segmentation networks (SegNet), and results demonstrate the effectiveness of the proposed network. The proposed telementoring system is efficient and explicitly considers the physiological nature of the human visual system to encode the video by providing good overall visual impact in the location of surgery. The results of the proposed S-CNN-based segmentation demonstrated a pixel accuracy of 97% and a mean intersection over union accuracy of 79%. Similarly, HEVC experimental results showed that the proposed surgical region–based encoding scheme achieved an average bitrate reduction of 88.8% at high-quality settings in comparison with default full-frame HEVC encoding. The average gain in encoding performance (signal-to-noise) of the proposed algorithm is 11.5 dB in the surgical region. The bitrate saving and visual quality of the proposed optimal bit allocation scheme are compared with the mean shift segmentation–based coding scheme for fair comparison. The results show that the proposed scheme maintains high visual quality in surgical incision region along with achieving good bitrate saving. Based on comparison and results, the proposed encoding algorithm can be considered as an efficient and effective solution for surgical telementoring systems for low-bandwidth networks.
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| 4. |
- Naqvi, Salman Raza, et al.
(författare)
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Pyrolysis of high ash sewage sludge : Kinetics and thermodynamic analysis using Coats-Redfern method
- 2019
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Ingår i: Renewable energy. - : Elsevier Ltd. - 0960-1481 .- 1879-0682. ; 131, s. 854-860
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Tidskriftsartikel (refereegranskat)abstract
- This study aims to investigate the thermo-kinetics of high-ash sewage sludge using thermogravimetric analysis. Sewage sludge was dried, pulverized and heated non-isothermally from 25 to 800 °C at different heating rates (5, 10 and 20 °C/min) in N2 atmosphere. TG and DTG results indicate that the sewage sludge pyrolysis may be divided into three stages. Coats-Redfern integral method was applied in the 2nd and 3rd stage to estimate the activation energy and pre-exponential factor from mass loss data using five major reaction mechanisms. The low-temperature stable components (LTSC) of the sewage sludge degraded in the temperature regime of 250–450 °C while high-temperature stable components (HTSC) decomposed in the temperature range of 450–700 °C. According to the results, first-order reaction model (F1) showed higher Ea with better R2 for all heating rates. D3, N1, and S1 produced higher Ea at higher heating rates for LTSC pyrolysis and lower Ea with the increase of heating rates for HTSC pyrolysis. All models showed positive ΔH except F1.5. Among all models, Diffusion (D1, D2, D3) and phase interfacial models (S1, S2) showed higher ΔG as compared to reaction, nucleation, and power-law models in section I and section II.
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| 5. |
- Tariq, S., et al.
(författare)
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Comparative study of Ce0.80Sm0.20 Ba0.80Y0.20O3-δ (YB-SDC) electrolyte by various chemical synthesis routes
- 2018
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Ingår i: Results in Physics. - : Elsevier B.V.. - 2211-3797. ; 8, s. 780-784
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Tidskriftsartikel (refereegranskat)abstract
- Solid Oxide Fuel Cells is received a significant attention in recent years due to higher efficiency and fuel flexibility. The one of the main challenge for SOFC is to lower the operating temperature of SOFCs. Therefore, different strategies are used in order to enhance the ionic conduction of electrolyte, which can lower the overall SOFC operating temperature. The present work is focused on this strategy to enhance the electrolytic conductivity. Therefore, the ceria based composite electrolytes Ce0.80Sm0.20B0.80Y0.20O3-δ (YBSDC) are synthesized using three different approaches i.e. co-precipitation (YBSDC-1), sol-gel (YBSDC-2) and ball milling (YBSDC-3). Their crystal structures and surface morphologies are characterized through X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) techniques, respectively. The four-probe technique is employed to measure their dc conductivities in the temperature range (300–700) °C under air atmosphere. The open circuit voltage (OCV) and current are recorded with natural gas as fuel {flow rate kept at 100 ml min−1 at 1 atm pressure} over the temperature range (300–600) °C. The electrolyte (YBSDC-1) prepared by co-precipitation technique is shown better results as compare to other two electrolytes (YBSDC-2 and YBSDC-3). The electrolyte (YBSDC-1) having maximum dc conductivity (0.096 S/cm), peak power density 224 mW cm−2 and OCV 0.94 V at 600 °C. These results show that YBSDC-1electrolyte is potential candidate for low temperature SOFCs.
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| 6. |
- Afroz, Laila, et al.
(författare)
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Nanocomposite Catalyst (1 – x)NiO-xCuO/yGDC for Biogas Fueled Solid Oxide Fuel Cells
- 2023
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Ingår i: ACS Applied Energy Materials. - : American Chemical Society (ACS). - 2574-0962. ; 6:21, s. 10918-10928
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Tidskriftsartikel (refereegranskat)abstract
- The composites of Ni–Cu oxides with gadolinium doped ceria (GDC) are emerging as highly proficient anode catalysts, owing to their remarkable performance for solid oxide fuel cells operated with biogas. In this context, the nanocomposite catalysts (1 – x)NiO-xCuO/yGDC (x = 0.2–0.8; y = 1,1.3) are synthesized using a solid-state reaction route. The cubic and monoclinic structures are observed for NiO and CuO phases, respectively, while CeO2 showed cubic fluorite structure. The scanning electron microscopic images revealed a rise in the particle size with an increase in the copper and GDC concentration. The optical band gap values are calculated in the range 2.82–2.33 eV from UV–visible analysis. The Raman spectra confirmed the presence of vibration modes of CeO2 and NiO. The electrical conductivity of the nanocomposite anodes is increased as the concentration of copper and GDC increased and reached at 9.48 S cm–1 for 0.2NiO-0.8CuO/1.3GDC composition at 650 °C. The electrochemical performance of (1 – x)NiO-xCuO/yGDC (x = 0.2–0.8; y = 1,1.3)-based fuel cells is investigated with biogas fuel at 650 °C. Among all of the as-synthesized anodes, the fuel cell with composition 0.2NiO-0.8CuO/1.3GDC showed the best performance, such as an open circuit voltage of 0.84 V and peak power density of 72 mW cm–2. However, from these findings, it can be inferred that among all other compositions, the 0.2NiO-0.8CuO/1.3GDC anode is a superior combination for the high electrochemical performance of solid oxide fuel cells fueled with biogas.
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| 7. |
- Arslan, Muhammad, et al.
(författare)
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Impact of Varying Load Conditions and Cooling Energy Comparison of a Double-Inlet Pulse Tube Refrigerator
- 2020
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Ingår i: Processes. - : MDPI. - 2227-9717. ; 8:3
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Tidskriftsartikel (refereegranskat)abstract
- Modeling and optimization of a double-inlet pulse tube refrigerator (DIPTR) is very difficult due to its geometry and nature. The objective of this paper was to optimize-DIPTR through experiments with the cold heat exchanger (CHX) along the comparison of cooling load with experimental data using different boundary conditions. To predict its performance, a detailed two-dimensional DIPTR model was developed. A double-drop pulse pipe cooler was used for solving continuity, dynamic and power calculations. External conditions for applicable boundaries include sinusoidal pressure from an end of the tube from a user-defined function and constant temperature or limitations of thermal flux within the outer walls of exchanger walls under colder conditions. The results of the system's cooling behavior were reported, along with the connection between the mass flow rates, heat distribution along pulse tube and cold-end pressure, the cooler load's wall temp profile and cooler loads with varied boundary conditions i.e. opening of 20% double-inlet and 40-60% orifice valves, respectively. Different loading conditions of 1 and 5W were applied on the CHX. At 150 K temperature of the cold-end heat exchanger, a maximum load of 3.7 W was achieved. The results also reveal a strong correlation between computational fluid dynamics modeling results and experimental results of the DIPTR.
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| 8. |
- Aziz, Maria, et al.
(författare)
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Efficient Removal of Lead and Chromium From Aqueous Media Using Selenium Based Nanocomposite Supported by Orange Peel
- 2022
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Ingår i: Frontiers in Environmental Science. - : Frontiers Media S.A.. - 2296-665X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- This study presents the synthesis of activated orange peel, derived from bio-waste (orange peel) and its doping with selenium nano-particles to enhance the adsorption capacity. The synthesized nanocomposite orange peel/Selenium (OP/Se) was applied as adsorbents for the removal of Lead (Pb) and Chromium (Cr) from synthetic waste water as an economical water cleaning technology. Orange peel/Selenium nanocomposite was characterized by X-Ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR) and Scanning electron microscopy (SEM). Scanning electron microscopy results showed the porous structure of OP/Se nanocomposite and distinct peaks observed in XRD and FTIR spectra depicted the successful synthesis of nanocomposite. Batch experiments were conducted to figure out the effect of different parameters on adsorption of Pb and Cr by using Atomic Absorption Spectroscopy. The maximum adsorption capacity of 99.9% was achieved for both lead and chromium at acidic pH. While at temperature of 60°C the maximum adsorption of 98.3 and 95.9% was found for Pb and Cr respectively. Furthermore the experimental data was examined with Pseudo-first order, first-order and Pseudo-second order kinetic model, as well as Morris Intraparticle diffusion model where the pseudo second order was best fitted which indicated the chemisorption mechanism in adsorption process. The adsorption process followed the Langmuir isotherm model verified that OP/Se nanocomposite was found to be favorable for the process of adsorption. The adsorption thermodynamics indicate that adsorption of heavy metals ions is spontaneous (ΔG° < 0) and the adsorption increases with increase in temperature which means that reaction was endothermic in nature. This study revealed that the synthesized bio-activated nanocomposite was an efficient adsorbent material for the removal of heavy metals from waste water.
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