Efficient Detection of Skin Cancer Using Deep Learning Techniques and a Comparative Analysis Study

Many skin lesions may result in the wrong diagnosis of skin cancer, leading to delays and ultimately making the cure impossible. Framed within this statement, this article proposes an efficient skin cancer detection model and compares the six pre-trained models, used for transfer learning in ISIC 2019 dataset. Three most common types of skin cancer—melanoma, nevus, and basal cell carcinoma—are classified by using the transfer learning on the pre-trained models of the ISIC 2019 dataset, to conclude the most accurate detection results with training and test accuracy of 99.73% and 93.79%, respectively

Towards Machine Learning-Based FPGA Backend Flow: Challenges and Opportunities

Field-Programmable Gate Array (FPGA) is at the core of System on Chip (SoC) design across various Industry 5.0 digital systems—healthcare devices, farming equipment, autonomous vehicles and aerospace gear to name a few. Given that pre-silicon verification using Computer Aided Design (CAD) accounts for about 70% of the time and money spent on the design of modern digital systems, this paper summarizes the machine learning (ML)-oriented efforts in different FPGA CAD design steps. With the recent breakthrough of machine learning, FPGA CAD tasks—high-level synthesis (HLS), logic synthesis, placement and routing—are seeing a renewed interest in their respective decision-making steps. We focus on machine learning-based CAD tasks to suggest some pertinent research areas requiring more focus in CAD design. The development of open-source benchmarks optimized for an end-to-end machine learning experience, intra-FPGA optimization, domain-specific accelerators, lack of explainability and federated learning are the issues reviewed to identify important research spots requiring significant focus. The potential of the new cloud-based architectures to understand the application of the right ML algorithms in FPGA CAD decision-making steps is discussed, together with visualizing the scenario of incorporating more intelligence in the cloud platform, with the help of relatively newer technologies such as CAD as Adaptive OpenPlatform Service (CAOS). Altogether, this research explores several research opportunities linked with modern FPGA CAD flow design, which will serve as a single point of reference for modern FPGA CAD flow design

Design of a Framework for the Aggregator using Demand Reduction Bid (DRB)

Demand side management (DSM) in smart grid paradigm is an energy management strategy of the grid using advanced data communication and networking. The aggregator, a third party entity, is appearing as a key player in managing the demand during the peak hours between the utility and the consumer. In this work, a general framework is discussed and focuses on the interactional issues between the utility, the aggregator and the consumers. The paper also discusses the role of communication in the context of interaction among the three players. In addition, it also presents the model of the framework which can enable the consumer to effectively participate in the DSM. The proposed model considers the direct load control (DLC) program which uses the concept of demand reduction bid (DRB) in aggregated demand response. Keywords: Aggregator, Demand reduction bid (DRB), Direct load control (DLC), Framewor

Chatbot Design Challenges and the Effect on User Behavior

Chatbots are efficient artificial intelligence tools employed frequently across various industries such as healthcare, tourism, entertainment, and education, to assist in performing repetitive activities requiring a conversation, thereby facilitating humans to focus on more innovative tasks. This chapter reviews the design challenges of two types of chatbots classified based on their interaction modes: dyadic chatbots interacting with one individual at a time; and polyadic chatbots interacting with multiple individuals simultaneously. Further, the chapter identified the associated challenges in the chatbots, namely: engagement, trust, and human likeliness based on personality types - at a higher level in the chatbot design, together with the impact of each challenge on the user behavior. The authors review the literature in the relevant areas to pinpoint the research gaps requiring more focus within each area of challenge. The research community can address these identified research areas, which will eventually promote a more efficient human-machine collaboration

How to Design and Deliver Courses for Higher Education in the AI Era: Insights from Exam Data Analysis

In this position paper, we advocate for the idea that courses and exams in the AI era have to be designed based on two factors: (1) the strengths and limitations of AI, and (2) the pedagogical educational objectives. Based on insights from the Delors report on education [1], we first address the role of education and recall the main objectives that educational institutes must strive to achieve independently of any technology. We then explore the strengths and limitations of AI, based on current advances in AI. We explain how courses and exams can be designed based on these strengths and limitations of AI, providing different examples in the IT, English, and Art domains. We show how we adopted a pedagogical approach that is inspired from the Socratic teaching method from January 2023 to May 2023. Then, we present the data analysis results of seven ChatGPT-authorized exams conducted between December 2022 and March 2023. Our exam data results show that there is no correlation between students' grades and whether or not they use ChatGPT to answer their exam questions. Finally, we present a new exam system that allows us to apply our pedagogical approach in the AI era

Smart Relay Selection Scheme Based on Fuzzy Logic with Optimal Power Allocation and Adaptive Data Rate Assignment

In this paper fuzzy logic-based algorithm with improved process of relay selection is presented which not only allocate optimal power for transmission but also help in choosing adaptive data rate. This algorithm utilizes channel gain, cooperative gain and signal to noise ratio with two cases considered in this paper: In case-I nodes do not have their geographical location information while in case-II nodes are having their geographical location information. From Monte Carlo simulations, it can be observed that both cases improve the selection process along with data rate assignment and power allocation, but case-II is the most reliable with almost zero probability of error at the cost of computational complexity which is 10 times more than case-I

Randomized controlled trial of standard versus double dose cotrimoxazole for childhood pneumonia in Pakistan

Objective: Increasing concern over bacterial resistance to cotrimoxazole, which is recommended by WHO as a first-line drug for treating non-severe pneumonia, led to the suggestion that this might not be optimal therapy. However, changing to alternative antimicrobial agents, such as amoxicillin, is costly. We compared the clinical efficacy of twice-daily cotrimoxazole in standard versus double dosage for treating non-severe pneumonia in children.Methods: A randomized controlled multicentre trial was implemented in seven hospital outpatient departments and two community health programmes. A total of 1143 children aged 2-59 months with non-severe pneumonia were randomly allocated to receive 4 mg trimethoprim plus 20 mg sulfamethoxazole/kg of body weight or 8 mg trimethoprim plus 40 mg sulfamethoxazole/kg of body weight orally twice-daily for 5 days Treatment failure occurred when a child required a change of therapy, died or was lost to follow-up. Children required a change of therapy if their condition worsened (they developed chest indrawing or danger signs) or if at 48 hours after enrollment, their clinical condition was the same (defined as having a respiratory rate that was 5 breaths/minute higher or lower than at the time of enrollment).Findings: The results of 1134 children were analysed: 578 were assigned to the standard dose of cotrimoxazole and 556 to the double dose. Treatment failed in 112 children (19.4%) in the standard group and 118 (21.2%) in the double-dose group (relative risk 1.10; 95% confidence interval = 0.87-1.37). Using multivariate analysis we found that treatment was more likely to fail in children who were not given the medicine correctly (P = 0.001), in those younger than 12 months (P = 0.004), those who had used antibiotics previously (P = 0.002), those whose respiratory rate was \u3e or =20 breaths/minute above the age-specific cut-off point (P = 0.006), and those from urban areas (P = 0.042).Conclusion: Both standard and double strength cotrimoxazole were equally effective in treating non-severe pneumonia. Close follow-up of patients is essential to prevent worsening of disease. Definitions of clinical failure need to be more specific. Surveillance in both rural and urban areas is essential in the development of treatment policies that are based on clinical outcomes

Resistance of Asian Cryptococcus neoformans Serotype A Is Confined to Few Microsatellite Genotypes

Contains fulltext : 109375.pdf (publisher's version ) (Open Access)BACKGROUND: Cryptococcus neoformans is a pathogenic yeast that causes cryptococcosis, a life threatening disease. The prevalence of cryptococcosis in Asia has been rising after the onset of the AIDS epidemic and estimates indicate more than 120 cases per 1,000 HIV-infected individuals per year. Almost all cryptococcal disease cases in both immunocompromised and immunocompetent patients in Asia are caused by C. neoformans var. grubii. Epidemiological studies on C. neoformans in pan-Asia have not been reported. The present work studies the genetic diversity of the fungus by microsatellite typing and susceptibility analysis of approximately 500 isolates from seven Asian countries. METHODOLOGY/PRINCIPAL FINDINGS: Genetic diversity of Asian isolates of C. neoformans was determined using microsatellite analysis with nine microsatellite markers. The analysis revealed eight microsatellite complexes (MCs) which showed different distributions among geographically defined populations. A correlation between MCs and HIV-status was observed. Microsatellite complex 2 was mainly associated with isolates from HIV-negative patients, whereas MC8 was associated with those from HIV-positive patients. Most isolates were susceptible to amphotericin B, itraconazole, voriconazole, posaconazole, and isavuconazole, but 17 (3.4%) and 10 (2%) were found to be resistant to 5-flucytosine and fluconazole, respectively. Importantly, five Indonesian isolates (approximately 12.5% from all Indonesian isolates investigated and 1% from the total studied isolates) were resistant to both antifungals. The majority of 5-flucytosine resistant isolates belonged to MC17. CONCLUSIONS: The findings showed a different distribution of genotypes of C. neoformans var. grubii isolates from various countries in Asia, as well as a correlation of the microsatellite genotypes with the original source of the strains and resistance to 5-flucytosine

Effects of a high-dose 24-h infusion of tranexamic acid on death and thromboembolic events in patients with acute gastrointestinal bleeding (HALT-IT): an international randomised, double-blind, placebo-controlled trial

Background: Tranexamic acid reduces surgical bleeding and reduces death due to bleeding in patients with trauma. Meta-analyses of small trials show that tranexamic acid might decrease deaths from gastrointestinal bleeding. We aimed to assess the effects of tranexamic acid in patients with gastrointestinal bleeding. Methods: We did an international, multicentre, randomised, placebo-controlled trial in 164 hospitals in 15 countries. Patients were enrolled if the responsible clinician was uncertain whether to use tranexamic acid, were aged above the minimum age considered an adult in their country (either aged 16 years and older or aged 18 years and older), and had significant (defined as at risk of bleeding to death) upper or lower gastrointestinal bleeding. Patients were randomly assigned by selection of a numbered treatment pack from a box containing eight packs that were identical apart from the pack number. Patients received either a loading dose of 1 g tranexamic acid, which was added to 100 mL infusion bag of 0·9% sodium chloride and infused by slow intravenous injection over 10 min, followed by a maintenance dose of 3 g tranexamic acid added to 1 L of any isotonic intravenous solution and infused at 125 mg/h for 24 h, or placebo (sodium chloride 0·9%). Patients, caregivers, and those assessing outcomes were masked to allocation. The primary outcome was death due to bleeding within 5 days of randomisation; analysis excluded patients who received neither dose of the allocated treatment and those for whom outcome data on death were unavailable. This trial was registered with Current Controlled Trials, ISRCTN11225767, and ClinicalTrials.gov, NCT01658124. Findings: Between July 4, 2013, and June 21, 2019, we randomly allocated 12 009 patients to receive tranexamic acid (5994, 49·9%) or matching placebo (6015, 50·1%), of whom 11 952 (99·5%) received the first dose of the allocated treatment. Death due to bleeding within 5 days of randomisation occurred in 222 (4%) of 5956 patients in the tranexamic acid group and in 226 (4%) of 5981 patients in the placebo group (risk ratio [RR] 0·99, 95% CI 0·82–1·18). Arterial thromboembolic events (myocardial infarction or stroke) were similar in the tranexamic acid group and placebo group (42 [0·7%] of 5952 vs 46 [0·8%] of 5977; 0·92; 0·60 to 1·39). Venous thromboembolic events (deep vein thrombosis or pulmonary embolism) were higher in tranexamic acid group than in the placebo group (48 [0·8%] of 5952 vs 26 [0·4%] of 5977; RR 1·85; 95% CI 1·15 to 2·98). Interpretation: We found that tranexamic acid did not reduce death from gastrointestinal bleeding. On the basis of our results, tranexamic acid should not be used for the treatment of gastrointestinal bleeding outside the context of a randomised trial