The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machin...The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.展开更多
Objective:To expound geographical information system (GIS) technology is a very important tool when it was employed to assist to present the distribution by time and place and the model of transmission of infectious d...Objective:To expound geographical information system (GIS) technology is a very important tool when it was employed to assist to present the distribution by time and place and the model of transmission of infectious disease. Methods: We illustrated the assistant decision-making support function of GIS with an example of the spatial decision support system for SARS controlling in Shaanxi province of China which was developed by us. Results: The spatial decision support system established by applying GIS technology fulfilled the needs of real-time collection and management and dissemination SARS information and of surveillance and analysis the epidemic situation of SARS. Conclusion: Occurrence and epidemic of diseases, implement prevention and intervention measures and collocation hygienic resources are all with the characteristic of the variation of time and space, therefore, GIS technology has become a powerful tool for identifying risk factors of diseases, providing clues of causation of diseases , evaluating the effects of intervention measures and drawing a health management plan.展开更多
Most traffic control systems available in major cities in Cameroon are still out dated, make use of theories and models which are very slow to implement, waste resources and their efficiency is very low. Thus the numb...Most traffic control systems available in major cities in Cameroon are still out dated, make use of theories and models which are very slow to implement, waste resources and their efficiency is very low. Thus the number of road accidents encountered on our major highways and inter urban traffic networks has been increasing despite the various efforts made by government and certain NGO to synthesize road users on certain aspects of traffic control and safety road use. Taxis are not left out in the whole show and most of the blame always falls on them. The need to use available Information and Communication Technology ICT to improve on the control of traffic in inter urban cities and major highways is imperative. ITS optimizes the use of resources, reduce pollution, contribute to environmental protection and increases the national economy. . This paper starts by giving a brief situation of the transportation system in Cameroon, its drawbacks and proposes an optimized ITS based system.展开更多
Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the sink.However,many existing data aggregatio...Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the sink.However,many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater environments.Additionally,conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink,commonly known as the energy hole issue.Moreover,cluster-based aggregation methods face significant challenges such as cluster head(CH)failures and collisions within clusters that degrade overall network performance.To address these limitations,this paper introduces an innovative framework,the Cluster-based Data Aggregation using Fuzzy Decision Model(CDAFDM),tailored for mobile UWSNs.The proposed method has four main phases:clustering,CH selection,data aggregation,and re-clustering.During CH selection,a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy,distance to the sink,and data delivery likelihood,enhancing network stability and energy efficiency.In the aggregation phase,CHs transmit a single,consolidated set of non-redundant data to the base station(BS),thereby reducing data duplication and saving energy.To adapt to the changing network topology,the re-clustering phase periodically updates cluster formations and reselects CHs.Simulation results show that CDAFDM outperforms current protocols such as CAPTAIN(Collection Algorithm for underwater oPTical-AcoustIc sensor Networks),EDDG(Event-Driven Data Gathering),and DCBMEC(Data Collection Based on Mobile Edge Computing)with a packet delivery ratio increase of up to 4%,an energy consumption reduction of 18%,and a data collection latency reduction of 52%.These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.展开更多
The integration of the Internet of Things(IoT)into healthcare systems improves patient care,boosts operational efficiency,and contributes to cost-effective healthcare delivery.However,overcoming several associated cha...The integration of the Internet of Things(IoT)into healthcare systems improves patient care,boosts operational efficiency,and contributes to cost-effective healthcare delivery.However,overcoming several associated challenges,such as data security,interoperability,and ethical concerns,is crucial to realizing the full potential of IoT in healthcare.Real-time anomaly detection plays a key role in protecting patient data and maintaining device integrity amidst the additional security risks posed by interconnected systems.In this context,this paper presents a novelmethod for healthcare data privacy analysis.The technique is based on the identification of anomalies in cloud-based Internet of Things(IoT)networks,and it is optimized using explainable artificial intelligence.For anomaly detection,the Radial Boltzmann Gaussian Temporal Fuzzy Network(RBGTFN)is used in the process of doing information privacy analysis for healthcare data.Remora Colony SwarmOptimization is then used to carry out the optimization of the network.The performance of the model in identifying anomalies across a variety of healthcare data is evaluated by an experimental study.This evaluation suggested that themodel measures the accuracy,precision,latency,Quality of Service(QoS),and scalability of themodel.A remarkable 95%precision,93%latency,89%quality of service,98%detection accuracy,and 96%scalability were obtained by the suggested model,as shown by the subsequent findings.展开更多
Maintaining software reliability is the key idea for conducting quality research.This can be done by having less complex applications.While developers and other experts have made signicant efforts in this context,the ...Maintaining software reliability is the key idea for conducting quality research.This can be done by having less complex applications.While developers and other experts have made signicant efforts in this context,the level of reliability is not the same as it should be.Therefore,further research into the most detailed mechanisms for evaluating and increasing software reliability is essential.A signicant aspect of growing the degree of reliable applications is the quantitative assessment of reliability.There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software.However,none of these mechanisms are useful for all kinds of failure datasets and applications.Hence nding the most optimal model for reliability prediction is an important concern.This paper suggests a novel method to substantially pick the best model of reliability prediction.This method is the combination of analytic hierarchy method(AHP),hesitant fuzzy(HF)sets and technique for order of preference by similarity to ideal solution(TOPSIS).In addition,using the different iterations of the process,procedural sensitivity was also performed to validate the ndings.The ndings of the software reliability prediction models prioritization will help the developers to estimate reliability prediction based on the software type.展开更多
Ever since its outbreak inWuhan,COVID-19 has cloaked the entireworld in a pall of despondency and uncertainty.The present study describes the exploratory analysis of all COVID cases in Saudi Arabia.Besides,the study h...Ever since its outbreak inWuhan,COVID-19 has cloaked the entireworld in a pall of despondency and uncertainty.The present study describes the exploratory analysis of all COVID cases in Saudi Arabia.Besides,the study has executed the forecastingmodel for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period.Towards this intent,the study analyzed different age groups of patients(child,adult,elderly)who were affected by COVID-19.The analysis was done city-wise and also included the number of recoveries recorded in different cities.Furthermore,the study also discusses the impact of COVID-19 on the economy.For conducting the stated analysis,the authors have created a list of factors that are known to cause the spread of COVID-19.As an effective countermeasure to contain the spread of Coronavirus in Saudi Arabia,this study also proposes to identify the most effective Computer Science technique that can be used by healthcare professionals.For this,the study employs the Fuzzy-Analytic Hierarchy Process integrated with the Technique for Order Performance by Similar to Ideal Solution(F.AHP.TOPSIS).After prioritizing the various Computer Science techniques,the ranking order that was obtained for the different techniques/tools to contain COVID-19 was:A4>A1>A2>A5>A3.Since the Blockchain technique obtained the highest priority,the study recommends that it must be used extensively as an efficacious and accurate means to combat COVID-19.展开更多
The present study examines the various techniques being used to maintain the integrity of the medical devices,and develops a quantitative framework to list these in the sequence of priority.To achieve the intended obj...The present study examines the various techniques being used to maintain the integrity of the medical devices,and develops a quantitative framework to list these in the sequence of priority.To achieve the intended objective,the study employs the combined procedure of Fuzzy Analytic Network Process(ANP)and Fuzzy Technical for Order Preference by Similarities to Ideal Solution(TOPSIS).We selected fuzzy based decision making techniques for assessing the integrity of medical devices.The suggested methodology was then used for classifying the suitable techniques used to evaluate the integrity of medical devices.Different techniques or the procedures of integrity assessment were ranked according to their satisfaction weights.The rating of the options determined the order of priority for the procedures.As per the findings of the study,among all the options,A1 was assessed to be the most likely option.This means that the integrity of medical devices of A2 is the highest amongst all the chosen alternatives.This analysis will be a corroborative guideline for manufacturers and developers to quantitatively test the integrity of medical devices in order to engineer efficacious devices.The evaluations undertaken with the assistance of the planned procedure are accurate and conclusive.Hence instead of conducting a manual valuation,this experimental study is a better and reliable option for assessing the integrity of the medical devices.展开更多
Ever since its outbreak in the Wuhan city of China,COVID-19 pandemic has engulfed more than 211 countries in the world,leaving a trail of unprecedented fatalities.Even more debilitating than the infection itself,were ...Ever since its outbreak in the Wuhan city of China,COVID-19 pandemic has engulfed more than 211 countries in the world,leaving a trail of unprecedented fatalities.Even more debilitating than the infection itself,were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus.Such enforced alienation affected both the mental and social condition of people significantly.Social interactions and congregations are not only integral part of work life but also form the basis of human evolvement.However,COVID-19 brought all such communication to a grinding halt.Digital interactions have failed to enthuse the fervor that one enjoys in face-to-face meets.The pandemic has shoved the entire planet into an unstable state.The main focus and aim of the proposed study is to assess the impact of the pandemic on different aspects of the society in Saudi Arabia.To achieve this objective,the study analyzes two perspectives:the early approach,and the late approach of COVID-19 and the consequent effects on different aspects of the society.We used a Machine Learning based framework for the prediction of the impact of COVID-19 on the key aspects of society.Findings of this research study indicate that financial resources were the worst affected.Several countries are facing economic upheavals due to the pandemic and COVID-19 has had a considerable impact on the lives as well as the livelihoods of people.Yet the damage is not irretrievable and the world’s societies can emerge out of this setback through concerted efforts in all facets of life.展开更多
This study discusses the experimental result of the viscoplastic response and col- lapse of sharp-notched 316L stainless steel tubes with different notched depths subjected to cyclic bending. The tube bending machine ...This study discusses the experimental result of the viscoplastic response and col- lapse of sharp-notched 316L stainless steel tubes with different notched depths subjected to cyclic bending. The tube bending machine and curvature-ovalization measurement apparatus were used for conducting the symmetric curvature-controlled cyclic bending. To highlight the viscoplastic behavior, three different curvature-rates, 0.0035, 0.035 and 0.35 m-1s-1, were controlled. Ob- servations of a certain curvature-rate reveal that five almost parallel lines corresponding to five different notch-depth （0.2, 0.4, 0.6, 0.8 and 1.0 mm） tubes were presented in the experimental relationship between the cyclic controlled curvature and the number of cycles needed to pro- duce buckling on a log-log scale. However, the slopes for the three different curvature-rates are different. An empirical formulation was proposed to simulate the aforementioned relationship. When comparing with the experimental findings, the simulation was in good agreement with the experimental data.展开更多
We study the transmission capacities of two coexisting spread-spectrum wireless networks (a primary network vs. a secondary network) that operate in the same geographic region and share the same spectrum. We defi ne t...We study the transmission capacities of two coexisting spread-spectrum wireless networks (a primary network vs. a secondary network) that operate in the same geographic region and share the same spectrum. We defi ne transmission capacity as the product among the density of transmissions, the transmission rate, and the successful transmission probability. The primary (PR) network has a higher priority to access the spectrum without particular considerations for the secondary (SR) network, while the SR network limits its interference to the PR network by carefully controlling the density ofits transmitters. Considering two types of spread-spectrum transmission schemes (FH-CDMA and DS-CDMA) and the channel inversion power control mechanism, we quantify the transmission capacities for these two networks based on asymptotic analysis. Our results show that if the PR network permits a small increase ofits outage probability, the sum transmission capacities of the two networks (i.e., the overall spectrumefficiency per unit area) will be boosted significantly over that of a single network.展开更多
In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day ...In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day consultancy services are aided by the use of multiple tools and techniques.However,ensuring the security of these tools and techniques is an important concern for the consultants because even a slight malfunction of any tool could alter the results drastically.Consultants usually tackle these functions after establishing the clients’needs and developing the appropriate strategy.Nevertheless,most of the consultants tend to focus more on the intended outcomes only and often ignore the security-specific issues.Our research study is an initiative to recommend the use of a hybrid computational technique based on fuzzy Analytical Hierarchy Process(AHP)and fuzzy Technique for Order Preference by Similarity to Ideal Solutions(TOPSIS)for prioritizing the tools and techniques that are used in consultancy services on the basis of their security features and efficacy.The empirical analysis conducted in this context shows that after implementing the assessment process,the rank of the tools and techniques obtained is:A7>A1>A4>A2>A3>A5>A6>A7,and General Electric McKinsey(GE-McKinsey)Nine-box Matrix(A7)obtained the highest rank.Thus,the outcomes show that this order of selection of the tools and techniques will give the most effective and secure services.The awareness about using the best tools and techniques in consultancy services is as important as selecting the most secure tool for solving a given problem.In this league,the results obtained in this study would be a conclusive and a reliable reference for the consultants.展开更多
Objective: To develop the management information system for SARS surveillance and control in Shaanxi province of China responding to the urgent needs for preventing and curing SARS disease. Methods: Based on geographi...Objective: To develop the management information system for SARS surveillance and control in Shaanxi province of China responding to the urgent needs for preventing and curing SARS disease. Methods: Based on geographic information system technology, the management information system for SARS disease in Shaanxi province of China was established using "SuperMap Objects 3.0" GIS development platform and Delphi 7.0.Results: The following functions were implemented in the system: the real-time collection and monitoring, management and analysis, dissemination of SARS disease information, and assistant decision-making support for prevention against SARS disease. Conclusion: The system that integrates epidemiology theories and GIS techniques together can provide a scientific, efficient means for monitoring, prevention of SARS disease in the future.展开更多
Design architecture is the edifice that strengthens the functionalities as well as the security of web applications.In order to facilitate architectural security from the web application’s design phase itself,practit...Design architecture is the edifice that strengthens the functionalities as well as the security of web applications.In order to facilitate architectural security from the web application’s design phase itself,practitioners are now adopting the novel mechanism of security tactics.With the intent to conduct a research from the perspective of security tactics,the present study employs a hybrid multi-criteria decision-making approach named fuzzy analytic hierarchy process-technique for order preference by similarity ideal solution(AHP-TOPSIS)method for selecting and assessing multi-criteria decisions.The adopted methodology is a blend of fuzzy analytic hierarchy process(fuzzy AHP)and fuzzy technique for order preference by similarity ideal solution(fuzzy TOPSIS).To establish the efficacy of this methodology,the results are obtained after the evaluation have been tested on fifteen different web application projects(Online Quiz competition,Entrance Test,and others)of the Babasaheb Bhimrao Ambedkar University,Lucknow,India.The tabulated outcomes demonstrate that the methodology of the Multi-Level Fuzzy Hybrid system is highly effective in providing accurate estimation for strengthening the security of web applications.The proposed study will help experts and developers in developing and managing security from any web application design phase for better accuracy and higher security.展开更多
In this paper,an advanced and optimized Light Gradient Boosting Machine(LGBM)technique is proposed to identify the intrusive activities in the Internet of Things(IoT)network.The followings are the major contributions:...In this paper,an advanced and optimized Light Gradient Boosting Machine(LGBM)technique is proposed to identify the intrusive activities in the Internet of Things(IoT)network.The followings are the major contributions:i)An optimized LGBM model has been developed for the identification of malicious IoT activities in the IoT network;ii)An efficient evolutionary optimization approach has been adopted for finding the optimal set of hyper-parameters of LGBM for the projected problem.Here,a Genetic Algorithm(GA)with k-way tournament selection and uniform crossover operation is used for efficient exploration of hyper-parameter search space;iii)Finally,the performance of the proposed model is evaluated using state-of-the-art ensemble learning and machine learning-based model to achieve overall generalized performance and efficiency.Simulation outcomes reveal that the proposed approach is superior to other considered methods and proves to be a robust approach to intrusion detection in an IoT environment.展开更多
This paper describes a new method based on Four Neighbor Distance Transformation (FNDT) and Equal Diagonal Algorithm (EDA) to extract the medial axis and locate the centromere of the chromosome Compared to the Classic...This paper describes a new method based on Four Neighbor Distance Transformation (FNDT) and Equal Diagonal Algorithm (EDA) to extract the medial axis and locate the centromere of the chromosome Compared to the Classical Thinning Algorithm and Four Neighbor Distance Transformation, the new method (FNDT-DEA) is more noise-tolerant, simpler in programming and faster in execution. The FDNTEDA provides the connective and one-pixel thick medial axis representing the length of chromosome. The Crofton directive parameters were used in the algorithm to locate the centromere in some chromosome. The number of chromosomes in a given cell is obtained with calculating either the Euler Number or the clase-curve’s subset. An intergroups classifier has also been designed. The FNDT-DEA gave results quite similar to those given with human assessment. It was concluded that this new method, FNDT-EDA, is appropriate for microcomputer-based analyzing the human chromosomes.展开更多
Due to our increased dependence on Internet and growing number of intrusion incidents, building effective intrusion detection systems are essential for protecting Internet resources and yet it is a great challenge. In...Due to our increased dependence on Internet and growing number of intrusion incidents, building effective intrusion detection systems are essential for protecting Internet resources and yet it is a great challenge. In literature, many researchers utilized Artificial Neural Networks (ANN) in supervised learning based intrusion detection successfully. Here, ANN maps the network traffic into predefined classes i.e. normal or specific attack type based upon training from label dataset. However, for ANN-based IDS, detection rate (DR) and false positive rate (FPR) are still needed to be improved. In this study, we propose an ensemble approach, called MANNE, for ANN-based IDS that evolves ANNs by Multi Objective Genetic algorithm to solve the problem. It helps IDS to achieve high DR, less FPR and in turn high intrusion detection capability. The procedure of MANNE is as follows: firstly, a Pareto front consisting of a set of non-dominated ANN solutions is created using MOGA, which formulates the base classifiers. Subsequently, based upon this pool of non-dominated ANN solutions as base classifiers, another Pareto front consisting of a set of non-dominated ensembles is created which exhibits classification tradeoffs. Finally, prediction aggregation is done to get final ensemble prediction from predictions of base classifiers. Experimental results on the KDD CUP 1999 dataset show that our proposed ensemble approach, MANNE, outperforms ANN trained by Back Propagation and its ensembles using bagging & boosting methods in terms of defined performance metrics. We also compared our approach with other well-known methods such as decision tree and its ensembles using bagging & boosting methods.展开更多
Backgroud:Parkinson’s disease(PD)is a neurodegenerative disorder with an increasing global prevalence.However,the development of drugs for PD treatment has not kept pace with the continuously growing number of patien...Backgroud:Parkinson’s disease(PD)is a neurodegenerative disorder with an increasing global prevalence.However,the development of drugs for PD treatment has not kept pace with the continuously growing number of patients.Currently,the search for new effective substances from natural drugs is a major research direction.Two Chinese medicinal materials,Saposhnikoviae Radix(Fangfeng)and Chuanxiong Rhizoma(Chuanxiong),are commonly used in the treatment of PD in China.However,the mechanism of their combination is not clear,and further research is needed.Methods:Data were collected from publicly available databases:TCMSP,UnitProt,GeneCards OMIM,PharmGKB,Therapeutic Target Database and DrugBank.Network pharmacology and molecular docking methods was used to analyze the data to discover the possible pharmacological effects of the two drugs in the treatment of PD.Results:Beta-sitosterol,Mandenol and Wallichilide were the active components of Saposhnikoviae Radix and Chuanxiong Rhizoma(FC),and they stably bonded with PD targets,including PTGS2,CASP3,AKT1 and JUN.The target genes of FC were significantly enriched in PD-associated pathways,including calcium signaling and apoptosis pathways.Moreover,the study revealed that the active components of FC may affect cellular structures,such as membrane rafts,membrane microdomains,membrane regions,and postsynaptic membranes,which,in turn,affect a variety of molecular functions and biological processes.Conclusion:The results of this study indicate the direction for clarifying the pharmacodynamic substances of FC,the extraction method of pharmacodynamic substances,as well as the mechanism and efficacy of pharmacodynamic substances.Importantly,this study provides a strategy for developing new therapeutic drugs for PD.展开更多
Background Spatial ability is an unique type of intelligence;it can be distinguished from other forms of intelligence and plays an essential role in an individual's success in many academic fields,particular in th...Background Spatial ability is an unique type of intelligence;it can be distinguished from other forms of intelligence and plays an essential role in an individual's success in many academic fields,particular in this era of technology.Instruction-assisted 3D technology can display stereo graphics and promote students'understanding of the geometrical structure and characteristics of graphics.Spatial ability includes several aspects.Few software programs are available for training different aspects of spatial ability for senior high school students.This study aims to explore an effective method for training the spatial ability for senior high school students,and to promote the development of students'independent inquiry ability.Methods First,an inquiry design strategy to improve the spatial ability of students is proposed.Based on this strategy,unity3D was used to develop a 3D inquiry environment that can use leap motion to complete a gesture interaction.Finally,researchers carried out experience-based activities and issued user experience questionnaires to participants to verify the application effect of the spatial ability inquiry environment and used interviews to understand the user experience of participants exploring the leap motion device in a 3D inquiry environment.Results 32 learners participated in the experiment.learners have a high score for perceived usefulness and willingness to use.Compared with the perceived ease of use and perceived usefulness,the average score of the application effect is relatively low.In terms of willingness to use,most of the learners expressed their willingness to use a similar inquiry environment for spatial ability training in the future.Conclusions The spatial ability inquiry environment can help learners better understand different concepts.The users showed a strong willingness to continue using the device.The device also updates the teaching concept to a certain extent and emphasizes the dominant position of a student.展开更多
Location prediction in social media,a growing research field,employs machine learning to identify users' locations from their online activities.This technology,useful in targeted advertising and urban planning,rel...Location prediction in social media,a growing research field,employs machine learning to identify users' locations from their online activities.This technology,useful in targeted advertising and urban planning,relies on natural language processing to analyze social media content and understand the temporal dynamics and structures of social networks.A key application is predicting a Twitter user's location from their tweets,which can be challenging due to the short and unstructured nature of tweet text.To address this challenge,the research introduces a novel machine learning model called the location-aware attention LSTM(LAA-LSTM).This hybrid model combines a Long Short-Term Memory(LSTM) network with an attention mechanism.The LSTM is trained on a dataset of tweets,and the attention network focuses on extracting features related to latitude and longitude,which are crucial for pinpointing the location of a user's tweet.The result analysis shows approx.10% improvement in accuracy over other existing machine learning approaches.展开更多
文摘The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.
基金Supported by the Sci & Tech Development Foundation of Shaanxi province(2003K10G61)
文摘Objective:To expound geographical information system (GIS) technology is a very important tool when it was employed to assist to present the distribution by time and place and the model of transmission of infectious disease. Methods: We illustrated the assistant decision-making support function of GIS with an example of the spatial decision support system for SARS controlling in Shaanxi province of China which was developed by us. Results: The spatial decision support system established by applying GIS technology fulfilled the needs of real-time collection and management and dissemination SARS information and of surveillance and analysis the epidemic situation of SARS. Conclusion: Occurrence and epidemic of diseases, implement prevention and intervention measures and collocation hygienic resources are all with the characteristic of the variation of time and space, therefore, GIS technology has become a powerful tool for identifying risk factors of diseases, providing clues of causation of diseases , evaluating the effects of intervention measures and drawing a health management plan.
文摘Most traffic control systems available in major cities in Cameroon are still out dated, make use of theories and models which are very slow to implement, waste resources and their efficiency is very low. Thus the number of road accidents encountered on our major highways and inter urban traffic networks has been increasing despite the various efforts made by government and certain NGO to synthesize road users on certain aspects of traffic control and safety road use. Taxis are not left out in the whole show and most of the blame always falls on them. The need to use available Information and Communication Technology ICT to improve on the control of traffic in inter urban cities and major highways is imperative. ITS optimizes the use of resources, reduce pollution, contribute to environmental protection and increases the national economy. . This paper starts by giving a brief situation of the transportation system in Cameroon, its drawbacks and proposes an optimized ITS based system.
基金funded by the Deanship of Scientific Research,the Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia under the project(KFU250420).
文摘Underwater wireless sensor networks(UWSNs)rely on data aggregation to streamline routing operations by merging information at intermediate nodes before transmitting it to the sink.However,many existing data aggregation techniques are designed exclusively for static networks and fail to reflect the dynamic nature of underwater environments.Additionally,conventional multi-hop data gathering techniques often lead to energy depletion problems near the sink,commonly known as the energy hole issue.Moreover,cluster-based aggregation methods face significant challenges such as cluster head(CH)failures and collisions within clusters that degrade overall network performance.To address these limitations,this paper introduces an innovative framework,the Cluster-based Data Aggregation using Fuzzy Decision Model(CDAFDM),tailored for mobile UWSNs.The proposed method has four main phases:clustering,CH selection,data aggregation,and re-clustering.During CH selection,a fuzzy decision model is utilized to ensure efficient cluster head selection based on parameters such as residual energy,distance to the sink,and data delivery likelihood,enhancing network stability and energy efficiency.In the aggregation phase,CHs transmit a single,consolidated set of non-redundant data to the base station(BS),thereby reducing data duplication and saving energy.To adapt to the changing network topology,the re-clustering phase periodically updates cluster formations and reselects CHs.Simulation results show that CDAFDM outperforms current protocols such as CAPTAIN(Collection Algorithm for underwater oPTical-AcoustIc sensor Networks),EDDG(Event-Driven Data Gathering),and DCBMEC(Data Collection Based on Mobile Edge Computing)with a packet delivery ratio increase of up to 4%,an energy consumption reduction of 18%,and a data collection latency reduction of 52%.These findings highlight the framework’s potential for reliable and energy-efficient data aggregation mobile UWSNs.
基金funded by Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah under grant No.(RG-6-611-43)the authors,therefore,acknowledge with thanks DSR technical and financial support.
文摘The integration of the Internet of Things(IoT)into healthcare systems improves patient care,boosts operational efficiency,and contributes to cost-effective healthcare delivery.However,overcoming several associated challenges,such as data security,interoperability,and ethical concerns,is crucial to realizing the full potential of IoT in healthcare.Real-time anomaly detection plays a key role in protecting patient data and maintaining device integrity amidst the additional security risks posed by interconnected systems.In this context,this paper presents a novelmethod for healthcare data privacy analysis.The technique is based on the identification of anomalies in cloud-based Internet of Things(IoT)networks,and it is optimized using explainable artificial intelligence.For anomaly detection,the Radial Boltzmann Gaussian Temporal Fuzzy Network(RBGTFN)is used in the process of doing information privacy analysis for healthcare data.Remora Colony SwarmOptimization is then used to carry out the optimization of the network.The performance of the model in identifying anomalies across a variety of healthcare data is evaluated by an experimental study.This evaluation suggested that themodel measures the accuracy,precision,latency,Quality of Service(QoS),and scalability of themodel.A remarkable 95%precision,93%latency,89%quality of service,98%detection accuracy,and 96%scalability were obtained by the suggested model,as shown by the subsequent findings.
基金funded by Grant No.12-INF2970-10 from the National Science,Technology and Innovation Plan(MAARIFAH)the King Abdul-Aziz City for Science and Technology(KACST)Kingdom of Saudi Arabia.
文摘Maintaining software reliability is the key idea for conducting quality research.This can be done by having less complex applications.While developers and other experts have made signicant efforts in this context,the level of reliability is not the same as it should be.Therefore,further research into the most detailed mechanisms for evaluating and increasing software reliability is essential.A signicant aspect of growing the degree of reliable applications is the quantitative assessment of reliability.There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software.However,none of these mechanisms are useful for all kinds of failure datasets and applications.Hence nding the most optimal model for reliability prediction is an important concern.This paper suggests a novel method to substantially pick the best model of reliability prediction.This method is the combination of analytic hierarchy method(AHP),hesitant fuzzy(HF)sets and technique for order of preference by similarity to ideal solution(TOPSIS).In addition,using the different iterations of the process,procedural sensitivity was also performed to validate the ndings.The ndings of the software reliability prediction models prioritization will help the developers to estimate reliability prediction based on the software type.
文摘Ever since its outbreak inWuhan,COVID-19 has cloaked the entireworld in a pall of despondency and uncertainty.The present study describes the exploratory analysis of all COVID cases in Saudi Arabia.Besides,the study has executed the forecastingmodel for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period.Towards this intent,the study analyzed different age groups of patients(child,adult,elderly)who were affected by COVID-19.The analysis was done city-wise and also included the number of recoveries recorded in different cities.Furthermore,the study also discusses the impact of COVID-19 on the economy.For conducting the stated analysis,the authors have created a list of factors that are known to cause the spread of COVID-19.As an effective countermeasure to contain the spread of Coronavirus in Saudi Arabia,this study also proposes to identify the most effective Computer Science technique that can be used by healthcare professionals.For this,the study employs the Fuzzy-Analytic Hierarchy Process integrated with the Technique for Order Performance by Similar to Ideal Solution(F.AHP.TOPSIS).After prioritizing the various Computer Science techniques,the ranking order that was obtained for the different techniques/tools to contain COVID-19 was:A4>A1>A2>A5>A3.Since the Blockchain technique obtained the highest priority,the study recommends that it must be used extensively as an efficacious and accurate means to combat COVID-19.
基金Funding for this study was granted by the King Abdul-Aziz City for Science and Technology(KACST),Kingdom of Saudi Arabia under the Grant Number:12-INF2970-10.
文摘The present study examines the various techniques being used to maintain the integrity of the medical devices,and develops a quantitative framework to list these in the sequence of priority.To achieve the intended objective,the study employs the combined procedure of Fuzzy Analytic Network Process(ANP)and Fuzzy Technical for Order Preference by Similarities to Ideal Solution(TOPSIS).We selected fuzzy based decision making techniques for assessing the integrity of medical devices.The suggested methodology was then used for classifying the suitable techniques used to evaluate the integrity of medical devices.Different techniques or the procedures of integrity assessment were ranked according to their satisfaction weights.The rating of the options determined the order of priority for the procedures.As per the findings of the study,among all the options,A1 was assessed to be the most likely option.This means that the integrity of medical devices of A2 is the highest amongst all the chosen alternatives.This analysis will be a corroborative guideline for manufacturers and developers to quantitatively test the integrity of medical devices in order to engineer efficacious devices.The evaluations undertaken with the assistance of the planned procedure are accurate and conclusive.Hence instead of conducting a manual valuation,this experimental study is a better and reliable option for assessing the integrity of the medical devices.
基金Funding for this study was received from the Ministry of Education andDeanship of Scientific Research at King Abdulaziz University, Kingdom of Saudi Arabia underthe Grant No. IFPHI-267-611-2020.
文摘Ever since its outbreak in the Wuhan city of China,COVID-19 pandemic has engulfed more than 211 countries in the world,leaving a trail of unprecedented fatalities.Even more debilitating than the infection itself,were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus.Such enforced alienation affected both the mental and social condition of people significantly.Social interactions and congregations are not only integral part of work life but also form the basis of human evolvement.However,COVID-19 brought all such communication to a grinding halt.Digital interactions have failed to enthuse the fervor that one enjoys in face-to-face meets.The pandemic has shoved the entire planet into an unstable state.The main focus and aim of the proposed study is to assess the impact of the pandemic on different aspects of the society in Saudi Arabia.To achieve this objective,the study analyzes two perspectives:the early approach,and the late approach of COVID-19 and the consequent effects on different aspects of the society.We used a Machine Learning based framework for the prediction of the impact of COVID-19 on the key aspects of society.Findings of this research study indicate that financial resources were the worst affected.Several countries are facing economic upheavals due to the pandemic and COVID-19 has had a considerable impact on the lives as well as the livelihoods of people.Yet the damage is not irretrievable and the world’s societies can emerge out of this setback through concerted efforts in all facets of life.
基金the support of the National Science Council under grant NSC 98-2221-E006-058
文摘This study discusses the experimental result of the viscoplastic response and col- lapse of sharp-notched 316L stainless steel tubes with different notched depths subjected to cyclic bending. The tube bending machine and curvature-ovalization measurement apparatus were used for conducting the symmetric curvature-controlled cyclic bending. To highlight the viscoplastic behavior, three different curvature-rates, 0.0035, 0.035 and 0.35 m-1s-1, were controlled. Ob- servations of a certain curvature-rate reveal that five almost parallel lines corresponding to five different notch-depth （0.2, 0.4, 0.6, 0.8 and 1.0 mm） tubes were presented in the experimental relationship between the cyclic controlled curvature and the number of cycles needed to pro- duce buckling on a log-log scale. However, the slopes for the three different curvature-rates are different. An empirical formulation was proposed to simulate the aforementioned relationship. When comparing with the experimental findings, the simulation was in good agreement with the experimental data.
基金supported in part by the China 863 Program grants 2007AA10Z235, 2007AA01Z179, 2006BAJ09B05, 2008BADA0B05the NSFC grants 60972073, 60871042, 60872049, and 60971082+1 种基金the China National Great Science Specifi c Project grant 2009ZX03003-011the China 973 Program grant 2009CB320407
文摘We study the transmission capacities of two coexisting spread-spectrum wireless networks (a primary network vs. a secondary network) that operate in the same geographic region and share the same spectrum. We defi ne transmission capacity as the product among the density of transmissions, the transmission rate, and the successful transmission probability. The primary (PR) network has a higher priority to access the spectrum without particular considerations for the secondary (SR) network, while the SR network limits its interference to the PR network by carefully controlling the density ofits transmitters. Considering two types of spread-spectrum transmission schemes (FH-CDMA and DS-CDMA) and the channel inversion power control mechanism, we quantify the transmission capacities for these two networks based on asymptotic analysis. Our results show that if the PR network permits a small increase ofits outage probability, the sum transmission capacities of the two networks (i.e., the overall spectrumefficiency per unit area) will be boosted significantly over that of a single network.
基金Funding for this study was received from the Taif University Researchers Supporting Projects at Taif University,Kingdom of Saudi Arabia under Grant No.TURSP-2020/254.
文摘In a digital world moving at a breakneck speed,consultancy services have emerged as one of the prominent resources for seeking effective,sustainable and economically viable solutions to a given crisis.The present day consultancy services are aided by the use of multiple tools and techniques.However,ensuring the security of these tools and techniques is an important concern for the consultants because even a slight malfunction of any tool could alter the results drastically.Consultants usually tackle these functions after establishing the clients’needs and developing the appropriate strategy.Nevertheless,most of the consultants tend to focus more on the intended outcomes only and often ignore the security-specific issues.Our research study is an initiative to recommend the use of a hybrid computational technique based on fuzzy Analytical Hierarchy Process(AHP)and fuzzy Technique for Order Preference by Similarity to Ideal Solutions(TOPSIS)for prioritizing the tools and techniques that are used in consultancy services on the basis of their security features and efficacy.The empirical analysis conducted in this context shows that after implementing the assessment process,the rank of the tools and techniques obtained is:A7>A1>A4>A2>A3>A5>A6>A7,and General Electric McKinsey(GE-McKinsey)Nine-box Matrix(A7)obtained the highest rank.Thus,the outcomes show that this order of selection of the tools and techniques will give the most effective and secure services.The awareness about using the best tools and techniques in consultancy services is as important as selecting the most secure tool for solving a given problem.In this league,the results obtained in this study would be a conclusive and a reliable reference for the consultants.
基金Supported by the Sci &Tech Development Foundation ofShaanxi province(2003K10G61)
文摘Objective: To develop the management information system for SARS surveillance and control in Shaanxi province of China responding to the urgent needs for preventing and curing SARS disease. Methods: Based on geographic information system technology, the management information system for SARS disease in Shaanxi province of China was established using "SuperMap Objects 3.0" GIS development platform and Delphi 7.0.Results: The following functions were implemented in the system: the real-time collection and monitoring, management and analysis, dissemination of SARS disease information, and assistant decision-making support for prevention against SARS disease. Conclusion: The system that integrates epidemiology theories and GIS techniques together can provide a scientific, efficient means for monitoring, prevention of SARS disease in the future.
文摘Design architecture is the edifice that strengthens the functionalities as well as the security of web applications.In order to facilitate architectural security from the web application’s design phase itself,practitioners are now adopting the novel mechanism of security tactics.With the intent to conduct a research from the perspective of security tactics,the present study employs a hybrid multi-criteria decision-making approach named fuzzy analytic hierarchy process-technique for order preference by similarity ideal solution(AHP-TOPSIS)method for selecting and assessing multi-criteria decisions.The adopted methodology is a blend of fuzzy analytic hierarchy process(fuzzy AHP)and fuzzy technique for order preference by similarity ideal solution(fuzzy TOPSIS).To establish the efficacy of this methodology,the results are obtained after the evaluation have been tested on fifteen different web application projects(Online Quiz competition,Entrance Test,and others)of the Babasaheb Bhimrao Ambedkar University,Lucknow,India.The tabulated outcomes demonstrate that the methodology of the Multi-Level Fuzzy Hybrid system is highly effective in providing accurate estimation for strengthening the security of web applications.The proposed study will help experts and developers in developing and managing security from any web application design phase for better accuracy and higher security.
文摘In this paper,an advanced and optimized Light Gradient Boosting Machine(LGBM)technique is proposed to identify the intrusive activities in the Internet of Things(IoT)network.The followings are the major contributions:i)An optimized LGBM model has been developed for the identification of malicious IoT activities in the IoT network;ii)An efficient evolutionary optimization approach has been adopted for finding the optimal set of hyper-parameters of LGBM for the projected problem.Here,a Genetic Algorithm(GA)with k-way tournament selection and uniform crossover operation is used for efficient exploration of hyper-parameter search space;iii)Finally,the performance of the proposed model is evaluated using state-of-the-art ensemble learning and machine learning-based model to achieve overall generalized performance and efficiency.Simulation outcomes reveal that the proposed approach is superior to other considered methods and proves to be a robust approach to intrusion detection in an IoT environment.
文摘This paper describes a new method based on Four Neighbor Distance Transformation (FNDT) and Equal Diagonal Algorithm (EDA) to extract the medial axis and locate the centromere of the chromosome Compared to the Classical Thinning Algorithm and Four Neighbor Distance Transformation, the new method (FNDT-DEA) is more noise-tolerant, simpler in programming and faster in execution. The FDNTEDA provides the connective and one-pixel thick medial axis representing the length of chromosome. The Crofton directive parameters were used in the algorithm to locate the centromere in some chromosome. The number of chromosomes in a given cell is obtained with calculating either the Euler Number or the clase-curve’s subset. An intergroups classifier has also been designed. The FNDT-DEA gave results quite similar to those given with human assessment. It was concluded that this new method, FNDT-EDA, is appropriate for microcomputer-based analyzing the human chromosomes.
文摘Due to our increased dependence on Internet and growing number of intrusion incidents, building effective intrusion detection systems are essential for protecting Internet resources and yet it is a great challenge. In literature, many researchers utilized Artificial Neural Networks (ANN) in supervised learning based intrusion detection successfully. Here, ANN maps the network traffic into predefined classes i.e. normal or specific attack type based upon training from label dataset. However, for ANN-based IDS, detection rate (DR) and false positive rate (FPR) are still needed to be improved. In this study, we propose an ensemble approach, called MANNE, for ANN-based IDS that evolves ANNs by Multi Objective Genetic algorithm to solve the problem. It helps IDS to achieve high DR, less FPR and in turn high intrusion detection capability. The procedure of MANNE is as follows: firstly, a Pareto front consisting of a set of non-dominated ANN solutions is created using MOGA, which formulates the base classifiers. Subsequently, based upon this pool of non-dominated ANN solutions as base classifiers, another Pareto front consisting of a set of non-dominated ensembles is created which exhibits classification tradeoffs. Finally, prediction aggregation is done to get final ensemble prediction from predictions of base classifiers. Experimental results on the KDD CUP 1999 dataset show that our proposed ensemble approach, MANNE, outperforms ANN trained by Back Propagation and its ensembles using bagging & boosting methods in terms of defined performance metrics. We also compared our approach with other well-known methods such as decision tree and its ensembles using bagging & boosting methods.
文摘Backgroud:Parkinson’s disease(PD)is a neurodegenerative disorder with an increasing global prevalence.However,the development of drugs for PD treatment has not kept pace with the continuously growing number of patients.Currently,the search for new effective substances from natural drugs is a major research direction.Two Chinese medicinal materials,Saposhnikoviae Radix(Fangfeng)and Chuanxiong Rhizoma(Chuanxiong),are commonly used in the treatment of PD in China.However,the mechanism of their combination is not clear,and further research is needed.Methods:Data were collected from publicly available databases:TCMSP,UnitProt,GeneCards OMIM,PharmGKB,Therapeutic Target Database and DrugBank.Network pharmacology and molecular docking methods was used to analyze the data to discover the possible pharmacological effects of the two drugs in the treatment of PD.Results:Beta-sitosterol,Mandenol and Wallichilide were the active components of Saposhnikoviae Radix and Chuanxiong Rhizoma(FC),and they stably bonded with PD targets,including PTGS2,CASP3,AKT1 and JUN.The target genes of FC were significantly enriched in PD-associated pathways,including calcium signaling and apoptosis pathways.Moreover,the study revealed that the active components of FC may affect cellular structures,such as membrane rafts,membrane microdomains,membrane regions,and postsynaptic membranes,which,in turn,affect a variety of molecular functions and biological processes.Conclusion:The results of this study indicate the direction for clarifying the pharmacodynamic substances of FC,the extraction method of pharmacodynamic substances,as well as the mechanism and efficacy of pharmacodynamic substances.Importantly,this study provides a strategy for developing new therapeutic drugs for PD.
基金the National Key Research and Development Program of China(2018YFB1004903)the Key Discipline Cultivation Program of Zhejiang Province(18JYXK018).
文摘Background Spatial ability is an unique type of intelligence;it can be distinguished from other forms of intelligence and plays an essential role in an individual's success in many academic fields,particular in this era of technology.Instruction-assisted 3D technology can display stereo graphics and promote students'understanding of the geometrical structure and characteristics of graphics.Spatial ability includes several aspects.Few software programs are available for training different aspects of spatial ability for senior high school students.This study aims to explore an effective method for training the spatial ability for senior high school students,and to promote the development of students'independent inquiry ability.Methods First,an inquiry design strategy to improve the spatial ability of students is proposed.Based on this strategy,unity3D was used to develop a 3D inquiry environment that can use leap motion to complete a gesture interaction.Finally,researchers carried out experience-based activities and issued user experience questionnaires to participants to verify the application effect of the spatial ability inquiry environment and used interviews to understand the user experience of participants exploring the leap motion device in a 3D inquiry environment.Results 32 learners participated in the experiment.learners have a high score for perceived usefulness and willingness to use.Compared with the perceived ease of use and perceived usefulness,the average score of the application effect is relatively low.In terms of willingness to use,most of the learners expressed their willingness to use a similar inquiry environment for spatial ability training in the future.Conclusions The spatial ability inquiry environment can help learners better understand different concepts.The users showed a strong willingness to continue using the device.The device also updates the teaching concept to a certain extent and emphasizes the dominant position of a student.
文摘Location prediction in social media,a growing research field,employs machine learning to identify users' locations from their online activities.This technology,useful in targeted advertising and urban planning,relies on natural language processing to analyze social media content and understand the temporal dynamics and structures of social networks.A key application is predicting a Twitter user's location from their tweets,which can be challenging due to the short and unstructured nature of tweet text.To address this challenge,the research introduces a novel machine learning model called the location-aware attention LSTM(LAA-LSTM).This hybrid model combines a Long Short-Term Memory(LSTM) network with an attention mechanism.The LSTM is trained on a dataset of tweets,and the attention network focuses on extracting features related to latitude and longitude,which are crucial for pinpointing the location of a user's tweet.The result analysis shows approx.10% improvement in accuracy over other existing machine learning approaches.
