A publicly verifiable key sharing mechanism based on threshold key sharing is provided to explore the security of users' private keys on the blockchain. Participating nodes check the key fragment after receiving i...
详细信息
A previous study [Entropy 25.4 (2023): 590] proposed a quantum secure multi-party summation protocol wherein n participants could obtain the modulo-2 summation result using single photons and single-particle operation...
详细信息
N4-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing to epigenetic regulation. It exists in various genomes, including the Rosaceae family encompassing significant fruit crops like apples,...
详细信息
In bioinformatics, classifying protein sequences into anticancer peptides (ACPs) and non-ACPs is crucial yet challenging due to the inherent uncertainties of biological data. This study introduces a novel fuzzy neural...
详细信息
ISBN:
(数字)9798350352788
ISBN:
(纸本)9798350352795
In bioinformatics, classifying protein sequences into anticancer peptides (ACPs) and non-ACPs is crucial yet challenging due to the inherent uncertainties of biological data. This study introduces a novel fuzzy neural network (FNN) model that integrates fuzzy logic within neural network architectures, enhancing the handling of ambiguity and improving classification accuracy. Our model, tested against several conventional machine learning models and recent studies, demonstrated superior specificity (83.28%) and overall accuracy (79.14%), marking a significant advancement in the identification of therapeutically relevant peptides. The integration of fuzzy logic not only optimized the performance but also increased the interpretability of the results, making it a valuable tool for complex bioinformatic analyses. These findings underscore the potential of fuzzy systems to refine predictive capabilities in computational biology, aligning perfectly with the themes of enhancing fuzzy theory applications in practical and impactful ways.
Smart cities promise a lot of well-being to their users in all areas of life through millions of applications and services. Smart services rely heavily on collecting data and the preferences of users. But on the dark ...
详细信息
Smart cities promise a lot of well-being to their users in all areas of life through millions of applications and services. Smart services rely heavily on collecting data and the preferences of users. But on the dark side, the users' information is posed to threat and penetration during transmission or stored far in the clouds. Depending on encryption only is not sufficient if the attacker has strong resources or if the attacker is the service provider (SP) itself. In addition, changing data before sending is not a practical solution in many systems because of the adverse impact on the quality of a main service. This research presented a new idea to address the issue of protection. The proposed method enhanced the privacy and security of users' data without affecting the accuracy of service. The core of the suggested solution relies on a knowledge base of services that are managed by experts. Also, the solution depends on fog nodes to measure the level of security and privacy of users' queries without delay. Moreover, the fog nodes manage contact with SPs. Finally, the proposed method divided the SP into two, one for user queries and the other for user data. The simulation and analytical discussion on a practical case in smart cities demonstrated the superiority of the proposed approach over previous methods in the level of protection by maintaining the quality of services, and the resistance to attacks.
The development of the internet made new problems within the scope of copyright. The internet is used to download copyrighted content and use it without permission from the creators. The legal protection of copyright ...
详细信息
We developed and validated a deep learning system (termed DeepDR Plus) in a diverse, multiethnic, multi-country dataset to predict personalized risk and time to progression of diabetic retinopathy. We show that DeepDR...
详细信息
We developed and validated a deep learning system (termed DeepDR Plus) in a diverse, multiethnic, multi-country dataset to predict personalized risk and time to progression of diabetic retinopathy. We show that DeepDR Plus can be integrated into the clinical workflow to promote individualized intervention strategies for the management of diabetic retinopathy.
Air pollution makes it worse in populated regions. Indonesia's major cities are also impacted by air pollution. Due to rising traffic, material consumption by vehicles, industrial growth, land burning, and garbage...
详细信息
ISBN:
(纸本)9798350399080
Air pollution makes it worse in populated regions. Indonesia's major cities are also impacted by air pollution. Due to rising traffic, material consumption by vehicles, industrial growth, land burning, and garbage collection, air quality has altered significantly. Accurate measurement and classification of air quality are required. Results of accurate classification aid in forming governmental regulations. To reach the criteria for livable air quality, we intend to manage controls. Some of the characteristics of air pollution include particulate (PM10) or PM25, sulfides (in the form of SO2), carbon monoxide (CO), ozone (O3), and nitrites (NO2). Using the XGBoost algorithm and synthetic minority oversampling (SMOTE) methods based on the Air Pollution Standard Index (ISPU) category, this study seeks to uncover factors that affect air quality. XGBoost, an ensemble machine learning approach built on a decision tree and applying a gradient reinforcement framework, is the classification algorithm in use. Air quality categorization has been tested and shown to work with the XGBoost algorithm. The dataset used in this study is air quality in 2021 which was collected by the Jakarta Environmental Ministry The proposed classification model will be evaluated using the Repeated k-fold cross-validation method for objective results. The results of the study prove that SMOTE and XGBoost have better performance than using only the XGBoost method in predicting air quality, where the overall accuracy value of SMOTE with XGBoost is 99.60%, The overall precision value is 99.60%, the overall recall value is 99.60% and the overall f1-score is 99.60% and the overall ROC AUC value is 99.96%. The overall SMOTE method with the proposed XGBoost has given better performance in air pollution prediction.
This paper proposes a donation mobile app gamified to monitor players’ donation decision. Three main scenarios were simulated to observe which factors affect the donation. First, five categories of donation project w...
详细信息
This paper proposes a donation mobile app gamified to monitor players’ donation decision. Three main scenarios were simulated to observe which factors affect the donation. First, five categories of donation project were available. Second, an expiring donation project was set and was alerted to players. Last, auctions were added to some donation projects to draw more players’ attention. Testing with twelve young players revealed that the most influenced donation factor is the project’s type. Health-related project was the most attentive. Also, the expiring donation project triggered the players’ interest. Unfortunately, auctions rarely increased the amount of donation which may be due to the uninteresting bidding products.
This paper presents a collection of computer use behavior prone to office syndrome by using pressure sensors in conjunction with IoT devices. IoT device was attached with a chair, and sensors were installed on the sea...
详细信息
This paper presents a collection of computer use behavior prone to office syndrome by using pressure sensors in conjunction with IoT devices. IoT device was attached with a chair, and sensors were installed on the seat and the backrest. Another IoT set was linked with sensors installed under the mouse pad. The collected data of seven testers instructed to use computer and move freely revealed different behaviors. Some were sitting constantly with or without using backrest or touching mouse. Also a unique character like standing while using computer was found. To link with office syndrome estimation, we proposed a set of rules including thresholds for pressure values, time criteria and risk scoring. Using these criteria, the testers were found to have low and moderate risks of office syndrome.
暂无评论