A sustainable approach for demand side management considering demand response and renewable energy in smart grids

The development of smart grids has revolutionized modern energy markets, enabling users to participate in demand response (DR) programs and maintain a balance between power generation and demand. However, users’ decreased awareness poses a challenge in responding to signals from DR programs. To address this issue, energy management controllers (EMCs) have emerged as automated solutions for energy management problems using DR signals. This study introduces a novel hybrid algorithm called the hybrid genetic bacteria foraging optimization algorithm (HGBFOA), which combines the desirable features of the genetic algorithm (GA) and bacteria foraging optimization algorithm (BFOA) in its design and implementation. The proposed HGBFOA-based EMC effectively solves energy management problems for four categories of residential loads: time elastic, power elastic, critical, and hybrid. By leveraging the characteristics of GA and BFOA, the HGBFOA algorithm achieves an efficient appliance scheduling mechanism, reduced energy consumption, minimized peak-to-average ratio (PAR), cost optimization, and improved user comfort level. To evaluate the performance of HGBFOA, comparisons were made with other well-known algorithms, including the particle swarm optimization algorithm (PSO), GA, BFOA, and hybrid genetic particle optimization algorithm (HGPO). The results demonstrate that the HGBFOA algorithm outperforms existing algorithms in terms of scheduling, energy consumption, power costs, PAR, and user comfort

The Difference in Cervical Vertebral Skeletal Maturation between Cleft Lip/Palate and Non-Cleft Lip/Palate Orthodontic Patients

Objective. The aim was to evaluate differences in the cervical vertebral skeletal maturity of unilateral cleft lip and palate (UCLP) and non-cleft lip/palate (non-CLP) Saudi male orthodontic patients. Method. This cross-sectional multicenter study took place at the dental school, King Saud University and King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia, between October 2014 and September 2015. The records of Saudi male orthodontic patients with UCLP n=69 were collected. Cervical vertebral maturation was assessed using their cephalometric radiographs. The records of 138 age-matched non-CLP Saudi male orthodontic patients served as controls. Results. There was a significant difference in skeletal maturity between the UCLP and non-CLP groups, as evident in the delayed skeletal development among the UCLP participants. Moreover, pubertal growth spurt onset was significantly earlier in the non-cleft participants in comparison with the UCLP participants p=0.009. Conclusions. There is delayed skeletal maturity among the UCLP Saudi male population in comparison with their non-CLP age-matched peers

An Enhanced intelligent intrusion detection system to secure E-commerce communication systems

Information and communication technologies are spreading rapidly due to their fast proliferation in many fields. The number of Internet users has led to a spike in cyber-attack incidents. E-commerce applications, such as online banking, marketing, trading, and other online businesses, play an integral role in our lives. Network Intrusion Detection System (NIDS) is essential to protect the network from unauthorized access and against other cyber-attacks. The existing NIDS systems are based on the Backward Oracle Matching (BOM) algorithm, which minimizes the false alarm rate and causes of high packet drop ratio. This paper discussed the existing NIDS systems and different used pattern-matching techniques regarding their weaknesses and limitations. To address the existing system issues, this paper proposes an enhanced version of the BOM algorithm by using multiple pattern-matching methods for the NIDS system to improve the network performance. The proposed solution is tested in simulation with existing solutions using the Snort and NSL-KDD datasets. The experimental results indicated that the proposed solution performed better than the existing solutions and achieved a 5.17% detection rate and a 0.22% lower false alarm rate than the existing solution</p

Assessment of Saudi Society’s Knowledge Regarding Hypothyroidism and Its Neuropsychiatric Clinical Manifestations

Background: This study was conducted to assess the level of knowledge and awareness of hypothyroidism and its neuropsychiatric clinical manifestations among the Saudi population. Methods: This was a cross-sectional study employing a convenient sampling technique, conducted between February and May 2022. A questionnaire was distributed online to all participants in all five regions. Results: In this survey, a total of 2016 Saudi citizens participated. When asked about depression, more than half of the participants (59.6%) correctly identified depression as one of the neuropsychiatric clinical symptoms of hypothyroidism. Nearly half of the participants (47.5%) were unaware that anxiety was not a neuropsychiatric manifestation of hypothyroidism. With a percentage of 91.0%, the majority of participants exhibited poor knowledge. The regression analysis showed that males have significantly reduced knowledge about hypothyroidism than females (coefficient −3.686, p-value p-value p-value 0.0001), and healthcare practitioners provides four times more information as compared to family and friends (p-value 0.0001). Conclusion: Due to a lack of knowledge about hypothyroidism and its complications, symptoms, risk factors, and treatment, the most viable solution to these misconceptions would be to implement a variety of educational programs to increase public awareness of this issue

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population