An efficient cuckoo-inspired meta-heuristic algorithm for multiobjective short-term hydrothermal scheduling

This paper proposes an efficient Cuckoo-Inspired Meta-Heuristic Algorithm (CIMHA) for solving multi-objective short-term hydrothermal scheduling (ST-HTS) problem. The objective is to simultaneously minimize the total cost and emission of thermal units while all constraints such as power balance, water discharge, and generation limitations must be satisfied. The proposed CIMHA is a newly developed meta-heuristic algorithm inspired by the intelligent reproduction strategy of the cuckoo bird. It is efficient for solving optimization problems with complicated objective and constraints because the method has few control parameters. The proposed method has been tested on different systems with various numbers of objective functions, and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is more efficient than many other methods for the test systems in terms of total cost, total emission, and computational time. Therefore, the proposed CIMHA can be a favorable method for solving the multi-objective ST-HTS problems

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance

Throughput Optimization for NOMA Energy Harvesting Cognitive Radio with Multi-UAV-Assisted Relaying under Security Constraints

This paper investigates the throughput of a non-orthogonal multiple access (NOMA)-based cognitive radio (CR) system with multiple unmanned aerial vehicle (UAV)-assisted relays under system performance and security constraints. We propose a communication protocol that includes an energy harvesting (EH) phase and multiple communication phases. In the EH phase, the multiple UAV relays (URs) harvest energy from a power beacon. In the first communication phase, a secondary transmitter (ST) uses the collected energy to send confidential signals to the first UR using NOMA. Simultaneously, a ground base station communicates with a primary receiver (PR) under interference from the ST. In the subsequent communication phases, the next URs apply the decode-and-forward technique to transmit the signals. In the last communication phase, the Internet of Things destinations (IDs) receive their signals in the presence of an eavesdropper (EAV). Accordingly, the outage probability of the primary network, the throughput of the secondary network, and the leakage probability at the EAV are analyzed. On this basis, we propose a hybrid search method combining particle swarm optimization (PSO) and continuous genetic algorithm (CGA) to optimize the UR configurations and the NOMA power allocation to maximize the throughput of the secondary network under performance and security constraints

A New Technique of Two Iliac Cortical Bone Blocks Sandwich Technique for Secondary Alveolar Bone Grafting in Cleft Lip and Palate Patients

Alveolar cleft bone graft in the second stage of surgery was a crucial part of the cleft palate treatment protocol with many advantages: reconstructing bone for tooth eruption, supporting the periodontal structure for the teeth adjacent to the cleft, supporting and lifting the arch and preventing from collapsing of maxillary arch. Grafting technique and material are selected based on the treatment purpose that for orthodontic moving tooth into the arch or for dental implant rehabilitation. Cancellous material provides rapid vascularization and healing facilitating for tooth moving into the cleft site but easy to resorb that unsuitable for dental implant placement. While dense material is difficult to move teeth into the cleft but increase initial stability. Therefore, we offered a method that limit bone resorption, easily obtain the implant initial stability, quick osseointegration called two iliac cortical bone blocks sandwich technique for a purposes of dental implant rehabilitation. Treatment protocol started with orthodontic treatment prior alveolar bone grafting to create proper space for implant restoration. Our clinical experience with 32 cleft sites using two iliac cortical bone blocks sandwich had shown potential clinical application in follow-up time up to 96 months. Evaluation criteria of bone grafting for alveolar cleft included soft tissue condition of graft area, nasal fistula closure, bone grafting outcome, success in osseointegration and implant prosthesis. This chapter described in detail treatment procedure and outcomes of a new technique of two iliac cortical bone blocks sandwich for alveolar cleft in patients with unilateral cleft palate

SECURITY CAPABILITY ANALYSIS OF COGNITIVE RADIO NETWORK WITH SECONDARY USER CAPABLE OF JAMMING AND SELF-POWERING

This paper investigates a cognitive radio network where a secondary sender assists a primarytransmitter in relaying primary information to a primary receiver and also transmits its own information toa secondary recipient. This sender is capable of jamming to protect secondary and/or primary informationagainst an eavesdropper and self-powering by harvesting radio frequency energy of primary signals.Security capability of both secondary and primary networks are analyzed in terms of secrecy outageprobability. Numerous results corroborate the proposed analysis which serves as a design guidelineto quickly assess and optimize security performance. More importantly, security capability trade-offbetween secondary and primary networks can be totally controlled with appropriate selection of systemparameters

Host Transcription Profile in Nasal Epithelium and Whole Blood of Hospitalized Children Under 2 Years of Age With Respiratory Syncytial Virus Infection.

BACKGROUND: Most insights into the cascade of immune events after acute respiratory syncytial virus (RSV) infection have been obtained from animal experiments or in vitro models. METHODS: In this study, we investigated host gene expression profiles in nasopharyngeal (NP) swabs and whole blood samples during natural RSV and rhinovirus (hRV) infection (acute versus early recovery phase) in 83 hospitalized patients <2 years old with lower respiratory tract infections. RESULTS: Respiratory syncytial virus infection induced strong and persistent innate immune responses including interferon signaling and pathways related to chemokine/cytokine signaling in both compartments. Interferon-α/β, NOTCH1 signaling pathways and potential biomarkers HIST1H4E, IL7R, ISG15 in NP samples, or BCL6, HIST2H2AC, CCNA1 in blood are leading pathways and hub genes that were associated with both RSV load and severity. The observed RSV-induced gene expression patterns did not differ significantly in NP swab and blood specimens. In contrast, hRV infection did not as strongly induce expression of innate immunity pathways, and significant differences were observed between NP swab and blood specimens. CONCLUSIONS: We conclude that RSV induced strong and persistent innate immune responses and that RSV severity may be related to development of T follicular helper cells and antiviral inflammatory sequelae derived from high activation of BCL6

Multiple-objective optimization applied in extracting multiple-choice tests

Student evaluation is an essential part of education and is usually done through examinations. These examinations generally use tests consisting of several questions as crucial factors to determine the quality of the students. Test-making can be thought of as a multi-constraint optimization problem. However, the test-making process that is done by either manually or randomly picking questions from question banks still consumes much time and effort. Besides, the quality of the tests generated is usually not good enough. The tests may not entirely satisfy the given multiple constraints such as required test durations, number of questions, and question difficulties. In this paper, we propose parallel strategies, in which parallel migration is based on Pareto optimums, and applyan improved genetic algorithm called a genetic algorithm combined with simulated annealing, GASA, which improves diversity and accuracy of the individuals by encoding schemes and a new mutation operator of GA to handle the multiple objectives while generating multiple choice-tests from a large question bank. The proposed algorithms can use the ability to exploit historical information structure in the discovered tests, and use this to construct desired tests later. Experimental results show that the proposed approaches are efficient and effective in generating valuable tests that satisfy specified requirements. In addition, the results, when compared with those from traditional genetic algorithms, are improved in several criteria including execution time, search speed, accuracy, solution diversity, and algorithm stability.Web of Science105art. no. 10443

Multi-swarm optimization for extracting multiple-choice tests from question banks

In this study, a novel method for generating multiple-choice tests is presented, which extracts the required number of tests of the same levels of difficulty in a single attempt and approximates the difficulty level requirement given by users. We propose an approach using parallelism and Pareto optimization for multi-swarm migration in a particle swarm optimization (PSO) algorithm. Multi-PSO is proposed for shortening the computing time. The proposed migration of PSOs increases the diversity of tests and controls the overlap of extracted tests. The experimental results show that the proposed method can generate many tests from question banks satisfying predefined levels of difficulty. Additionally, the developed method is shown to be effective in terms of many criteria when compared with other methods such as manually extracted tests, a simulated annealing algorithm (SA), random methods and PSO-based approaches in terms of the number of successful solutions, accuracy, standard deviation, search speed, and the number of questions overlapping between the exam questions, as well as for changing the search space, changing the number of individuals, changing the number of swarms, and changing the difficulty requirements.Web of Science9321483213

Performance Analysis of Bidirectional Multi-Hop Vehicle-to-Vehicle Visible Light Communication

Vehicular visible light communication (VVLC) has emerged as a promising field of research, garnering considerable attention from scientists and researchers. VVLC offers a potential solution to enable connectivity and communication between travelling vehicles along the road by using their existing headlights (HLs) and taillights (TLs) as wireless transmitters and integrating photodetectors (PDs) within the car front or car-back as wireless receivers. However, VVLC encounters more challenges than indoor VLC, particularly in vehicle-to-vehicle (V2V) communication, where vehicle mobility disrupts the establishment of direct communication links. To address this, we propose a multi-hop relay system wherein intermediate vehicles act as wireless relays to maintain a line-of-sight (LoS) link. In this paper, we investigate the performance of a bidirectional multi-hop relay V2V-VLC system that operates in both the forward and backward directions. Based on realistic ray tracing channel models, we derive a closed-form expression for the full bidirectional communication range. We also analyze how the transceiver&#x2019;s parameters and the number of relays affect the system performance. Our results show that the proposed bidirectional multi-hop relay system can extend the direct transmission range by more than 19 m with only a hop relay