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This paper analyzes the bit error rate (BER) of multicarrier index keying—orthogonal frequency division multiplexing (MCIK-OFDM) with selection combining (SC) diversity reception. Particularly, we propose a generalized framework to derive the BER for both the low-complexity greedy detector (GD) and maximum likelihood (ML) detector. Based on this, closed-form expressions for the BERs of MCIK-OFDM with the SC using either the ML or the GD are derived in presence of the channel state information (CSI) imperfection. The asymptotic analysis is presented to gain helpful insights into effects of different CSI conditions on the BERs of these two detectors. More importantly, we theoretically provide opportunities for using the GD instead of the ML under each specific CSI uncertainty, which depend on the number of receiver antennas and the M-ary modulation size. Finally, extensive simulation results are provided in order to validate our theoretical expressions and analysis.

This paper proposes a novel spread spectrum and sub-carrier index modulation (SS-SIM) scheme, which is integrated to orthogonal frequency division multiplexing (OFDM) framework to enhance the diversity over the conventional IM schemes. Particularly, the resulting scheme, called SS-SIM-OFDM, jointly employs both spread spectrum and sub-carrier index modulations to form a precoding vector which is then used to spread an M-ary complex symbol across all active sub-carriers. As a result, the proposed scheme enables a novel transmission of three signal domains: SS and sub-carrier indices, and a single M-ary symbol. For practical implementations, two reduced-complexity near-optimal detectors are proposed, which have complexities less depending on the M-ary modulation size. Then, the bit error probability and its upper bound are analyzed to gain an insight into the diversity gain, which is shown to be strongly affected by the order of sub-carrier indices. Based on this observation, we propose two novel sub-carrier index mapping methods, which significantly increase the diversity gain of SS-SIM-OFDM. Finally, simulation results show that our scheme achieves better error performance than the benchmarks at the cost of lower spectral efficiency compared to classical OFDM and OFDM-IM, which can carry multiple M-ary symbols.

In this paper, a low-complexity linear precoding algorithm based on the principal component analysis technique in combination with the conventional linear precoders, called Principal Component Analysis Linear Precoder (PCA-LP), is proposed for massive MIMO systems. The proposed precoder consists of two components: the first one minimizes the interferences among neighboring users and the second one improves the system performance by utilizing the Principal Component Analysis (PCA) technique. Numerical and simulation results show that the proposed precoder has remarkably lower computational complexity than its low-complexity lattice reduction-aided regularized block diagonalization using zero forcing precoding (LC-RBD-LR-ZF) and lower computational complexity than the PCA-aided Minimum Mean Square Error combination with Block Diagonalization (PCA-MMSE-BD) counterparts while its bit error rate (BER) performance is comparable to those of the LC-RBD-LR-ZF and PCA-MMSE-BD ones.

Taguchi and post-heat treatment methods have been used in this study to optimize the metal inert gas (MIG) welding joints between SUS304 austenite stainless steel and plain carbon SS400 steel using AWS ER 308L filler wire. The dissimilar welding joints’ microstructure and tensile strength have been examined. The findings show that the fast cooling of the weld joint and the ferrite-forming element of the filler wire cause the dendrites’ δ-ferrite phase to emerge on both the weld bead and the heat-affected zone (HAZ) of the SUS304 side. The stickout parameter has the largest impact on the ultimate tensile strength (UTS), next to the welding speed, welding voltage, and welding current, due to the strong impact of the heat distribution. The optimal welding parameters are a welding current of 105 A, a welding voltage of 14.5 V, a stickout of 12 mm, and a welding speed of 420 mm/min, producing the UTS value of 445.3 MPa, which is close to the predicted value of 469.2 ± 53.6 MPa. Post-heat treatment with an annealing temperature that is lower than 700 °C could improve the optimized weld joints’ strength by up to 5%. The findings may provide a more realistic understanding of the dissimilar welding technology.

In this paper, a parallel group detection (PGD) algorithm is proposed in order to address the degradation in the bit error rate (BER) performance of linear detectors when they are used in high-load massive MIMO systems. The algorithm is constructed by converting the equivalent extended massive MIMO system into two subsystems, which can be simultaneously detected by the classical detection procedures. Then, using the PGD and the classical ZF as well as the QR-decomposition- (QRD-) based detectors, we proposed two new detectors, called ZF-based PGD (ZF-PGD) and QRD-based PGD (QRD-PGD). The PGD is further combined with the sorted longest basis (SLB) algorithm to make the signal recovery more accurate, thereby resulting in two new detectors, namely, the ZF-PGD-SLB and the QRD-PGD-SLB. Various complexity evaluations and simulations prove that the proposed detectors can significantly improve the BER performance compared to their classical linear and QRD counterparts with the practical complexity levels. Hence, our proposed detectors can be used as efficient means of estimating the transmitted signals in high-load massive MIMO systems.

In recent decades, the speed of construction, expansion, and development of smart cities by humans has been increasing faster, thanks to new technologies. However, alongside the fantastic development of new technologies also comes negative impacts such as climate change. One of the characteristics of climate change is the changing thermal comfort of humans living in the city. Heat stress is a feature of the urban heat island phenomenon. Congestion of airflows within the urban area causes localized hot areas, causing a temperature difference of 2-3 degrees between the areas inside the city and the suburbs. This study presents a method for determining surface temperature and the location of heat islands based on Google's cloud computing platform. The platform uses a combination of satellite imagery, Earth observation data, and machine learning algorithms to allow users to identify and measure changes in land use, ecosystems, and climate patterns at a global scale. Google Earth Engine enables researchers and organizations to process enormous amounts of data with short turnaround times. The method described in the article allows the analysis and retrieval of data in the large dataset of the Landsat 8 satellite. By determining the location of heat islands, the government, policymakers, and planners can develop plans to cope with the urban heat island phenomenon and improve the quality of life for residents.

The expansion of construction zones, transportation, and utilities for industry and high-tech areas due to human activities has caused the deterioration of the natural ecological environment. As cities face problems related to the surface urban heat island (SUHI) effect and environmental pollution, there is an urgent need to develop new methods for the ecological–microclimatic assessment and structural–functional planning of urban areas. The main goal of this study was to demonstrate the evolution of the surface urban heat island (SUHI) effect in Moscow over a long period and to determine the interaction between SUHIs and urban pollution islands (UPIs) using a geospatial analysis platform while optimizing vegetation classification with machine learning. Additionally, we are creating a digital database for modeling the sustainability of cities on the GEE platform using cloud computing. This study used cloud computing and remote sensing image analysis platforms for a 17-year temporal-series ecological–microclimatic assessment, which provided a sequence of values describing the ongoing process of changes in the ecological conditions of Moscow over time. Combining machine learning with the random forest algorithm (RF) improved vegetation classification accuracy while reducing computation time. The study findings demonstrated how the SUHI affected Moscow’s territory and showed the urban areas significantly impacted by this phenomenon. The locations of surface urban heat islands in Moscow and areas affected by SUHI and UPI were identified using numerical modeling of the urban thermal field variance index (UTFVI). From the findings, we identified the need to develop a new method for obtaining geospatial data for assessing the interaction between UPIs and SUHIs using cloud computing and mathematical data models.

Rapid urbanization causes significant changes on the earth surface directly and internal itself temperature. The transformation of land use purposes crucially affects the surface temperature and exacerbates the effect of the negative heat island. It is necessary to develope a long-term strategy optimize urban cooling. In this study, the determinated object is Hanoi - city - a widen urbanized city in Vietnam. The authors proposed, defined and calculated the concept of cooling efficiency and threshold values. The results show that the surface heat capacity increases in proportion to the reduction of green space. Plots with excess temperature difference of the ground surface of 4.34 ℃ with reduced green space.

Rice husk ash (RHA) obtained from agricultural by-product could be a potential source for partial cement replacement to produce concrete brick. In this study, primary RHA and RHA heat-treated at 500oC were used to substitute cement in raw material mixtures. Preliminary analyses were conducted to evaluate some properties of RHA such as loss of ignition (LOI), morphology, chemical and phase compositions. X-ray Powder Diffraction (XRD) and X-Ray flourescence (XRF) results indicated that silica (SiO2) is the major component of RHA. Transmission Electron Microscopy (TEM) images showed that RHA particles were in polygonal shapes with diameter approximately from 300 nm – 1 μm. Cement was replaced with RHA by weight at 10 %wt. The effects of RHA on the physical and mechanical properties of the aggregate cement bricks were investigated. Results demonstrated that the compressive strength of concrete bricks increased with age at curing and decreased as the percentage of RHA content increased. It is recommended that further studies should be carried out to achive optimum parameters for production of concrete brick in economic aspects.

In this paper, a low-complexity precoding algorithm is proposed to reduce the computational complexity and improve the performance for MU-MIMO systems under exponential spatial correlation channel conditions. The proposed precoders are designed consisting of two components: The first one minimizes the interference among neighboring user groups, while the second one improves the system performance. Numerical and simulation results show that the proposed precoders have remarkably lower computational complexities than their existing LC-RBD-LR-ZF and BD counterparts. Besides, BER performances of the proposed precoders are asymptotic to that of LC-RBD-LR-ZF precoder at the low SNR region and better than that of LC-RBD-LR-ZF precoder at the high SNR region. Simulation results also show that the performance of the proposed algorithms is significantly improved compared to the BD algorithm in an exponential spatial correlation channel.