Search

The sella turcica is one of the most important landmarks used by orthodontics in analysis of growth and treatment planning. Therefore, the purpose of this retrospective study was to detect whether there is a correlation between the sella turcica's linear dimensions and the vertical growth patterns of the jaws using CBCT in an Egyptian subpopulation. 144 CBCT scans of adult patients (68 males and 76 females) were taken from the archive of the Oral Radiology Department , Faculty of Dentistry, Suez Canal University. CBCT images were divided according to the vertical growth pattern of both maxilla and mandible into three groups; hypodivergent, normodivergent and hyperdivergent. The sella turcica diameter, length and depth were measured individually for each case. There were no statistically significant differences found between sella turcica's length and diameter measurements and vertical growth pattern of the jaws. While significant difference was found regarding the depth only between the three groups where the p-value was found to be 0.001. Conclusion: CBCT could be used as a highly accurate radiographic modality in assessing the linear dimensions of sella turcica .The sellar depth was the only linear measurement found to be affected by the vertical growth pattern of the jaws.

Cell-free massive MIMO communications is an emerging network technology for 5G wireless communications wherein distributed multi-antenna access points (APs) serve many users simultaneously. Most prior work on cell-free massive MIMO systems assume time-division duplexing mode, although frequency-division duplexing (FDD) systems dominate current wireless standards. The key challenges in FDD massive MIMO systems are channel-state information (CSI) acquisition and feedback overhead. To address these challenges, we exploit the so-called angle reciprocity of multipath components in the uplink and downlink, so that the required CSI acquisition overhead scales only with the number of served users, and not the number of AP antennas nor APs. We propose a low complexity multipath component estimation technique and present linear angle-of-arrival (AoA)-based beamforming/combining schemes for FDD-based cell-free massive MIMO systems. We analyze the performance of these schemes by deriving closed-form expressions for the mean-square-error of the estimated multipath components, as well as expressions for the uplink and downlink spectral efficiency. Using semi-definite programming, we solve a max-min power allocation problem that maximizes the minimum user rate under per-user power constraints. Furthermore, we present a user-centric (UC) AP selection scheme in which each user chooses a subset of APs to improve the overall energy efficiency of the system. Simulation results demonstrate that the proposed multipath component estimation technique outperforms conventional subspace-based and gradient-descent based techniques. We also show that the proposed beamforming and combining techniques along with the proposed power control scheme substantially enhance the spectral and energy efficiencies with an adequate number of antennas at the APs.

This paper introduces a reconfigurable intelligent surface (RIS)-assisted grant-free non-orthogonal multiple-access (GF-NOMA) scheme. To ensure the power reception disparity required by the power domain NOMA (PD-NOMA), we propose a joint user clustering and RIS assignment/alignment approach that maximizes the network sum rate by judiciously pairing user equipments (UEs) with distinct channel gains, assigning RISs to proper clusters, and aligning RIS phase shifts to the cluster members yielding the highest cluster sum rate. Once UEs are acknowledged with the cluster index, they are allowed to access their resource blocks (RBs) at any time requiring neither further grant acquisitions from the base station (BS) nor power control as all UEs are requested to transmit at the same power. In this way, the proposed approach performs an implicit over-the-air power control with minimal control signaling between BS and UEs, which has shown to deliver up to 20% higher network sum rate than benchmark GF-NOMA and optimal grant-based PD-NOMA schemes depending on the network parameters. The given numerical results also investigate the impact of UE density, RIS deployment, and RIS hardware specifications on the overall performance of the proposed RIS-aided GF-NOMA scheme.

The objective of this study was to explore the immunological and antioxidant alterations associated with ovine postpartum disorders. Blood samples were collected from 90 adult Barki ewes and allocated into three equal-sized groups (30 ewes each): control group (CG), inflammatory postpartum disorders group (IPG) and non-inflammatory postpartum disorders group (NIPG). PCR-DNA sequencing approach was carried out for TLR4 (256-bp) and SOD (456-bp) genes, and nucleotide sequence variations were noticed to be associated with postpartum disorders resistance/susceptibility. Gene expression profile was also evaluated and levels of IL5, IL6, IL1-s, TNF alpha, TLR4 and Tollip were significantly up-regulated in ewes affected with postpartum disorders than resistant ones, while SOD and CAT genes pattern elicited an opposite trend. Exploring serum profile also showed a significant increase of IL-1α, IL-1β, IL-6, TNF-α, MDA and NO in IPG compared to their correspond values in NIPG and CG. However, serum levels of IL-10, CAT, GSH and GPx were significantly decreased. This study highlights that SNPs in TLR4 and SOD genes could be genetic markers for postpartum disorders resistance/susceptibility in Barki ewes. Gene expression alongside serum profiles of antioxidant markers could also be used to follow-up the immune status of ewes to build up an effective management protocol.

Objective: To evaluate fluoride release and uptake behaviors of the new bioactive resin modified glass ionomer cement (RMGIC) (activa bioactive glass ionomer) compared to conventional glass ionomer cement(CGIC) (Fuji IX GP). Material and Methods: Forty specimens were prepared (10 mm x 2 mm) from Fuji IX GP glass ionomer and Activa Bioactive RMGI according to manufacturer’s instructions. The specimens stored in deionized water and fluoride release were assessed daily in the first week then weekly till the third week using ion chromatography. The specimens of each material were divided into two equal subgroups according to the recharging agents used ; either0.05% mouth wash (226 ppm sodium fluoride, G.U.M, Sunstar, Germany, GmbH) or 5% sodium fluoride varnish (22.600ppm fluoride, enamel pro varnish Premier Dental, Plymouth Meeting, PA,19462,USA). Fluoride release after recharge was measured and recorded daily for a total of 5 days. Data were analyzed by Two way ANOVA and Duncans test (α = 0.05) using the SPSS software program. Results: CGIC release higher amount of fluoride than RMGIC. Professionally applied fluoride varnish showed better recharging ability than home care fluoride mouth wash and CGIC had greater recharge ability than new RMGIC.

Consumer privacy and consumption confidentiality and integrity are the main security concerns for smart grid connection with the residential electricity consumers. This paper proposes a lightweight privacy-preserving electricity consumption aggregation scheme that exploits lightweight lattice-based homomorphic cryptosystem. In the proposed scheme, smart household appliances aggregate their readings without involving the smart meter. Although smart meters or the intermediate base station cannot decrypt this aggregated consumption, they can validate the message’s authenticity. The proposed scheme also investigates the impact of different types of smart appliances on the home area network’s overhead. The total communication and computation load for the proposed scheme is trivial and tolerable by different parties in the connection, i.e., smart appliances, smart meters, and the base station. In addition, the deployed cryptosystem, which depends on simple arithmetic operations, can further reduce the computation duty for smart appliances. Simulation results and security analysis show that our proposed scheme guarantees consumers privacy, and messages authenticity and integrity, with lightweight communication and computation complexity.

Information security and customers’ privacy in smart grid are significant concerns. Existing security and privacy preserving schemes consider that the consumption reports for electricity consumption aggregation and billing purposes are sent periodically. These periodic messages increase the computation and communication burden on restricted-capabilities smart meters. In this paper, we propose a lightweight security and privacy preserving scheme that is based on forecasting the electricity demand for a cluster of houses in the same residential area; it limits the cluster’s connection with electricity utility only when the cluster needs to adjust its total demand. The scheme efficiently satisfies the security and privacy requirements in customer-side networks, i.e., communication between customers and power utility. At the same time, it significantly reduces the communication and computation overhead. Moreover, the proposed scheme utilizes NTRU cryptosystem to further reduce the computation complexity.

Vehicle-to-grid (V2G) connection allows a two-way electricity transmission between electric vehicles (EVs) and the power grid for achieving many known benefits. However, V2G connections suffer from certain security threats, such as to the EV's privacy and in authenticating the EV to the grid. In this paper, we propose a lightweight secure and privacy-preserving V2G connection scheme in which the power grid assures the confidentiality and integrity of exchanged information during (dis)charging electricity sessions and overcomes the EVs' authentication problem. The proposed scheme guarantees the financial profits of the grid and prevents EVs from acting maliciously. Meanwhile, EVs preserve their private information by generating their own pseudonym identities. In addition, the scheme maintains accountability for the electricity exchange trade. Furthermore, the proposed scheme provides these security requirements by lightweight overhead, as it diminishes the number of exchanged messages during (dis)charging sessions. Simulation results demonstrate that the proposed scheme significantly reduces the total communication and computation load for V2G connection, particularly for EVs.

In this paper, we study the uplink achievable rate by a massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of 1-bit analog-to-digital converters (ADCs). We propose a linear minimum mean-squared error (MMSE)-based detector that accounts for the non-linearity effects of the 1-bit quantization as well as for channel estimation error. An analytical framework that derives the achievable rate of the MMSE-based detector in a massive MIMO configuration under the assumption of 1-bit quantized ADCs and channel estimation error is presented. We compare the achievable rates of a massive MIMO system using a 1-bit ADC and a linear detector against a conventional MIMO system with higher-order modulation and near maximum likelihood (ML) detection. We show that in the low signal-to-noise ratio (SNR) regime with channel estimation error, the quantized massive MIMO system can outperform the conventional large MIMO system; however for high SNR, the conventional MIMO system with a near ML detector can outperform the quantized massive MIMO system.

Device-to-Device (D2D) communications underlaying cellular networks is a viable network technology that can potentially increase spectral utilization and improve power efficiency for proximitybased wireless applications and services. However, a major challenge in such deployment scenarios is the interference caused by D2D links when sharing the same resources with cellular users. In this work, we propose a channel allocation (CA) scheme together with a set of three power control (PC) schemes to mitigate interference in a D2D underlaid cellular system modeled as a random network using the mathematical tool of stochastic geometry. The novel aspect of the proposed CA scheme is that it enables D2D links to share resources with multiple cellular users as opposed to one as previously considered in the literature. Moreover, the accompanying distributed PC schemes further manage interference during link establishment and maintenance. The first two PC schemes compensate for large-scale path-loss effects and maximize the D2D sum rate by employing distance-dependent pathloss parameters of the D2D link and the base station, including an error estimation margin. The third scheme is an adaptive PC scheme based on a variable target signal-to-interference-plus-noise ratio, which limits the interference caused by D2D users and provides sufficient coverage probability for cellular users. Closed-form expressions for the coverage probability of cellular links, D2D links, and sum rate of D2D links are derived in terms of the allocated power, density of D2D links, and path-loss exponent. The impact of these key system parameters on network performance is analyzed and compared with previous work. Simulation results demonstrate an enhancement in cellular and D2D coverage probabilities, and an increase in spectral and power efficiency., 35 pages

The main security concern for Power Control System and State Estimation process is FDI attacks that based on adding fabricated readings in the measurements vector for state estimation process, i.e., sensors and measurements units’ readings about grid status and consumers requirements, to mislead CC to make wrong decisions, such as redistributing electricity according to that wrong injected information, and consequently cause huge damage to power system, such as large blackout, which has negative economic and financial impacts.

Smart grid technology has to consider many concerns due to network performance and security requirements. The security concerns for smart grid are varied according to the applications.

V2G networks face various types of attacks, which can threaten the vehicle owners’ privacy and the integrity of exchanged messages, such as impersonating EVs, illegally modifying their messages, or threatening the owner’s privacy.

Smart grid can be defined as the incorporation between the communication and information technology and the traditional power grid to connect generation, transmission, distribution, and consumption subsystems in the electricity grid together.

Device-to-Device (D2D) communication is a promising technology that can potentially enhance the spectral and energy efficiency of cellular networks. To exploit this benefit in D2D-underlaid cellular networks, the co-channel interference between D2D and cellular users should be properly managed. In this paper, we propose a distributed power control scheme to mitigate interference in a D2D underlaid cellular system modeled as a random network using the mathematical tool of stochastic geometry. The proposed PC scheme compensates for large-scale path-loss effects by employing distance-dependent path-loss parameters of the D2D link and the base station, including an estimation error margin. Closed-form expressions for the coverage probability of cellular links, D2D links, and the sum rate of D2D links are derived in terms of the allocated power, density of D2D links, and path-loss exponent. The coverage performance of both cellular and D2D users is analyzed, and the analytical results are validated through simulations. Experimental results demonstrate the efficacy and advantages of our proposed scheme over other schemes by an enhancement of 20%-30% for the cellular and D2D coverage probabilities, and an increase in spectral efficiency by 60%.

False data injection (FDI) attack is one of the severe attacks that threatens the smart grid's efficiency and reliability. Power grid's status is monitored by many measurement units spread all over the grid; these units periodically send their measurements to the grid's control center (CC), which utilizes them to make the right decisions for the grid. FDI attack inserts fake measurements among the correct ones to mislead CC to make wrong decisions and consequently impact on the grid's performance. Several works are proposed to only detect FDI attack utilizing various estimation tests and optimization techniques. In our paper, we propose an FDI attack prevention technique that is based on protecting the integrity of the measurements at measurement units and during their transmission to the CC, even with the presence of compromised units. So, the proposed scheme alleviates the negative impacts of FDI attack on grid's performance. Security analysis and performance evaluation show that our scheme guarantees the integrity and availability of the measurements with lightweight overhead, especially on the restricted-capabilities measurement units.

Security and privacy concerns are significant challenges in the smart grid, especially in regards to the privacy of the electricity customers, as customers' daily habits and personal information can be revealed from their consumption patterns. The current security and privacy-preserving schemes depend on periodic reports for customers' consumption; these reports increase the computation and communication overheads on the limited-resources smart meters. This paper proposes a security and privacy-preserving scheme in the building area network (BAN), which is a cluster of home area networks (HAN). The proposed scheme is based on forecasting the future electricity demand for the whole BAN; thus, the BAN connects to the electricity provider only if the total demand of the cluster is changed. The proposed scheme employs the lattice-based public key NTRU cryptosystem to guarantee the confidentiality and authenticity of the exchanged messages and to further reduce the computation and communication load. The security analysis shows that our proposed scheme can achieve the privacy and security requirements. In addition, it efficiently reduces the communication and computation overhead.

Vehicle-to-grid (V2G) connection allows electricity exchange between electric vehicles (EVs) and grid, i.e., EVs are used as temporary storage for extra generated power. However, V2G connections suffer from certain security threats, such as EV's privacy and authenticating it to grid. In this paper, we propose a lightweight secure and privacy-preserving V2G connection scheme, in which the power grid assures the confidentiality and integrity of exchanged information during (dis)charging electricity sessions and overcomes EVs' authentication problem. The proposed scheme guarantees the financial profits of the grid and prevents EVs from acting maliciously. Meanwhile, EVs preserve their private information by generating their own pseudonym identities. In addition, the scheme keeps the accountability for the electricity-exchange trade. The simulation results show that the proposed scheme significantly reduces the total communication and computation load for V2G connection especially for EVs.