The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness...The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.展开更多
Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized...Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized relevant literatures published in recent years,and sorted out and analyzed the types of pesticides used and detection techniques of common diseases in Chinese chives.展开更多
Plant diseases and pests present significant challenges to global food security, leading to substantial losses in agricultural productivity and threatening environmental sustainability. As the world’s population grow...Plant diseases and pests present significant challenges to global food security, leading to substantial losses in agricultural productivity and threatening environmental sustainability. As the world’s population grows, ensuring food availability becomes increasingly urgent. This review explores the significance of advanced plant disease detection techniques in disease and pest management for enhancing food security. Traditional plant disease detection methods often rely on visual inspection and are time-consuming and subjective. This leads to delayed interventions and ineffective control measures. However, recent advancements in remote sensing, imaging technologies, and molecular diagnostics offer powerful tools for early and precise disease detection. Big data analytics and machine learning play pivotal roles in analyzing vast and complex datasets, thus accurately identifying plant diseases and predicting disease occurrence and severity. We explore how prompt interventions employing advanced techniques enable more efficient disease control and concurrently minimize the environmental impact of conventional disease and pest management practices. Furthermore, we analyze and make future recommendations to improve the precision and sensitivity of current advanced detection techniques. We propose incorporating eco-evolutionary theories into research to enhance the understanding of pathogen spread in future climates and mitigate the risk of disease outbreaks. We highlight the need for a science-policy interface that works closely with scientists, policymakers, and relevant intergovernmental organizations to ensure coordination and collaboration among them, ultimately developing effective disease monitoring and management strategies needed for securing sustainable food production and environmental well-being.展开更多
In recent years,the prevalence of allergens in food warning notices,both domestically and internationally,has become the second leading concern after microbial contamination.Among the various factors that threaten hum...In recent years,the prevalence of allergens in food warning notices,both domestically and internationally,has become the second leading concern after microbial contamination.Among the various factors that threaten human health reported by the World Health Organization,food allergy ranks fourth,and food allergy has become a global security problem.As of now,no definitive treatment for food allergies exists,making the avoidance of allergen-containing foods the most effective prevention method.Consequently,labeling foods with allergen information serves as a crucial warning for allergic populations.Moreover,to enhance comprehension of food allergies,this article provides a brief overview of their definition and sensitization mechanisms.The main focus lies in highlighting the structure of primary allergens found in eight commonly allergenic foods and the resulting clinical symptoms they cause.Additionally,a summary of commonly employed allergen detection techniques is presented,with an analysis of their principles,advantages,and limitations.Looking ahead,the integration of diverse technological approaches to establish an efficient,accurate,and affordable allergen detection method remains a significant trend.This article has certain reference value for understanding the direction of food allergies.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensi...Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensive applications in law enforcement and the commercial domain,and the rapid advancement of practical technologies.Despite the significant advancements,modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions,occlusion,and diverse facial postures.In such scenarios,human perception is still well above the capabilities of present technology.Using the systematic mapping study,this paper presents an in-depth review of face detection algorithms and face recognition algorithms,presenting a detailed survey of advancements made between 2015 and 2024.We analyze key methodologies,highlighting their strengths and restrictions in the application context.Additionally,we examine various datasets used for face detection/recognition datasets focusing on the task-specific applications,size,diversity,and complexity.By analyzing these algorithms and datasets,this survey works as a valuable resource for researchers,identifying the research gap in the field of face detection and recognition and outlining potential directions for future research.展开更多
One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks ba...One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability requirement. In this survey paper, we provide a classification of attacks based on the OSI model and discuss in more detail the cyber-attacks that can target the different layers of smart grid networks communication. We also propose new classifications for the detection and countermeasure techniques and describe existing techniques under each category. Finally, we discuss challenges and future research directions.展开更多
Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthr...Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.展开更多
This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the second...This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.展开更多
Food safety has always been a critical issue concerning people s livelihoods.The complexity and diversity of hazardous substances in food make systematical and scientifical identification of potential risk factors aff...Food safety has always been a critical issue concerning people s livelihoods.The complexity and diversity of hazardous substances in food make systematical and scientifical identification of potential risk factors affecting food safety and accurate assessment and early warning for such risks one of the urgent problems for food safety inspection authorities.This paper explored food safety risk identification technologies,food safety risk monitoring technologies,and food safety risk early warning methods,aiming to provide theoretical support and research insights for improving food risk early warning systems.展开更多
This research study predominantly emphases on spatiotemporal extensions of urban area of Peshawar;its adverse impacts and contributions to climate and environment during 1931 to 2011. To probe these interventions, met...This research study predominantly emphases on spatiotemporal extensions of urban area of Peshawar;its adverse impacts and contributions to climate and environment during 1931 to 2011. To probe these interventions, meteorological data, Satellite’s temporal imagery of Landsat ETM+ and TM, anthropogenic and demographic secondary data were congregated. In relation to map out land cover changes, maximum likelihood classification algorithm and followed by change detection techniques were applied to study area. The outcome of this process was further subjected through Geographic Information System (GIS) overlay analysis which suggested a clear straggle in urban area. Auxiliary data (Population growth rate, transportation, electricity connections, etc.) also support the fact of urban area extension. This study proposes that severs contributions of massive heat energy and CO<sub>2</sub> have been added to local climate and environment ensuing substantial increment in temperature drawn out from the trends. Consequently, Remote Sensing, GIS and allied data were found to be effective to gauge such variations. To eliminate anomalies in sprawl and environment, few suggestions and recommendation are made in latter part of this study.展开更多
Objective To develop an in situ PCR in combination with flow cytometry （ISPCR-FCM） for monitoring cholera toxin positive Vibrio cholerae. Methods In running this method, 4% paraformaldehyde was used to fix the Vibri...Objective To develop an in situ PCR in combination with flow cytometry （ISPCR-FCM） for monitoring cholera toxin positive Vibrio cholerae. Methods In running this method, 4% paraformaldehyde was used to fix the Vibrio cholerae cells and 1 mg/mL lysozyme for 20 min to permeabilize the cells. Before the PCR thermal cycling, 2.5% glycerol was added into the PCR reaction mixture in order to protect the integrality of the cells. Results A length of 1037bp DNA sequence was amplified, which is specific for the cholera toxin gene （ctxAB gene）. Cells subjected to ISPCR showed the presences of ctxAB gene both in epifluorescence microscopy and in flow cytometric analysis. The specificity and sensitivity of the method were investigated. The sensitivity was relatively low （10^5 cells/mL）, while the specificity was high. Conclusion We have successfully developed a new technique for detection of toxigenic Vibrio cholerae strains. Further study is needed to enhance its sensitivities. ISPCR-FCM shows a great promise in monitoring specific bacteria and their physiological states in environmental samples.展开更多
Side-channel attacks have recently progressed into software-induced attacks.In particular,a rowhammer attack,which exploits the characteristics of dynamic random access memory(DRAM),can quickly and continuously access...Side-channel attacks have recently progressed into software-induced attacks.In particular,a rowhammer attack,which exploits the characteristics of dynamic random access memory(DRAM),can quickly and continuously access the cells as the cell density of DRAM increases,thereby generating a disturbance error affecting the neighboring cells,resulting in bit flips.Although a rowhammer attack is a highly sophisticated attack in which disturbance errors are deliberately generated into data bits,it has been reported that it can be exploited on various platforms such as mobile devices,web browsers,and virtual machines.Furthermore,there have been studies on bypassing the defense measures of DRAM manufacturers and the like to respond to rowhammer attacks.A rowhammer attack can control user access and compromise the integrity of sensitive data with attacks such as a privilege escalation and an alteration of the encryption keys.In an attempt to mitigate a rowhammer attack,various hardware-and software-based mitigation techniques are being studied,but there are limitations in that the research methods do not detect the rowhammer attack in advance,causing overhead or degradation of the system performance.Therefore,in this study,a rowhammer attack detection technique is proposed by extracting common features of rowhammer attack files through a static analysis of rowhammer attack codes.展开更多
Metastasis usually presents in the different courses of tumor diseases and associates with poor prognosis.Circulating tumor cells(CTC) are considered to be essential for conforming metastasis and can be detected in tu...Metastasis usually presents in the different courses of tumor diseases and associates with poor prognosis.Circulating tumor cells(CTC) are considered to be essential for conforming metastasis and can be detected in tumor patients' peripheral blood.CTC are not easily detected by conventional cytology methods because of their low frequency in peripheral blood.Our article reviews the recent research results on this subject,and also discusses the problems and prospects in this area.展开更多
A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow ...A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.展开更多
Cancer,as one of the most notorious health diseases,represents the main reason attributed to millions of worldwide deaths each year.Timely detection and accurate diagnosis are thus vital to cancer prevention and timel...Cancer,as one of the most notorious health diseases,represents the main reason attributed to millions of worldwide deaths each year.Timely detection and accurate diagnosis are thus vital to cancer prevention and timely therapy.Traditional cancer prescreening is not only cumbersome but also heavily reliant on sufficient expert knowledge,which inevitably increases the complexity of cancer diagnosis and limits early cancer diagnosis.To overcome this problem,recent terahertz(THz)technology,as an unconventional bio-friendly detection approach,has emerged with great potential in human disease diagnosis due to its non-ionic and high-resolution features.By combining the THz detection technique and artificial intelligence technique,here we propose a dense and efficient channel attention network(DECANet)framework-based THz diagnosis system for cancer prescreening.The cancer identification and diagnosis process are transformed into one end-to-end classification process of THz signals reflected from cancer tissue.The biosamples of breast and skin cancer tissue are characterized to validate the effectiveness and applicability of the proposed approach.Our quantified results indicate that our proposed THz diagnosis framework has promising feature extraction capability for abnormal cancerous tissue and provides an effective complement tool to assist the healthcare cancer diagnosis.展开更多
Biogenic amine is one of the main categories of hazardous compounds in meat and meat products,making its detection methods vital for the assurance of edible safety.In this sense,many biogenic amine detection technique...Biogenic amine is one of the main categories of hazardous compounds in meat and meat products,making its detection methods vital for the assurance of edible safety.In this sense,many biogenic amine detection techniques such as chromatographic,electrophoretic,and electrochemical methods have been developed,which play an irreplaceable role in ensuring the safety of meat and meat products.Due to the increasing demand for fast and on-site detection techniques,visual detection methods have been gradually developed compared with non-visual methods such as chromatography and electrophoresis.Herein,we comprehensively review the mechanism and the latest progress of these biogenic amine detection methods;besides,we put forward the prospects for the future development of biogenic amine detection techniques,with a view to providing support for the establishment of more accurate and efficient detection,prevention and control strategies of biogenic amines.展开更多
The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back...The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back approximately five thousand years in the recorded history of China. With advances in the development of modern technology, the concept of health monitoring of a variety of engineering structures in several applications has begun to attract widespread attention. Of particular interest in this study is the health monitoring of civil structures. It seem natural, and even beneficial, that these two health-monitoring methods, one as applies to the human body and the other to civil structures, should be analyzed and compared. In this paper, the basic concepts and theories of the two monitoring methods are first discussed. Similarities are then summarized and commented upon. It is hoped that this correlation analysis may help provide structural engineers with some insights into the intrinsic concept of using pulse diagnosis in human health monitoring, which may of be some benefit in the development of modern structural health monitoring methods.展开更多
Based on the transmitting theory of "smoke ring effect", the transient electromagnetism technique was used in coal mines to detect abnormal areas of aquiferous structures in both roofs and floors of coal sea...Based on the transmitting theory of "smoke ring effect", the transient electromagnetism technique was used in coal mines to detect abnormal areas of aquiferous structures in both roofs and floors of coal seams and in front of excavated roadways. Survey devices, working methods and techniques as well as data processing and interpretation are discussed systematically. In addition, the direction of mini-wireframe emission electromagnetic wave of the full space transient electromagnetism technique was verified by an underground borehole for water detection and drainage. The result indicates that this technique can detect both horizontal and vertical development rules of abnormal water bodies to a certain depth below the floor of coal seams and can also detect the abnormal, low resistance water bodies within a certain distance of roofs. Furthermore, it can detect such abnormal bodies in ahead of the excavated roadway front. Limited by the underground environment, the full space transient electromagnetism technique can detect to a depth of only 120 m or so.展开更多
Diphenhydramine(DPH),a commonly used over-the-counter(OTC)antihistamine and sedative,requires accurate and reliable analytical methods to be evaluated in various matrices.The systematic review provides a comprehensive...Diphenhydramine(DPH),a commonly used over-the-counter(OTC)antihistamine and sedative,requires accurate and reliable analytical methods to be evaluated in various matrices.The systematic review provides a comprehensive analysis of the current analytical techniques to detect DPH in biological samples and pharmaceutical formulations between 2012 and 2022.Case reports of DPH-related fatalities and intoxications were included along with crime statistics of OTC drug seizure in India from 2017 to 2021.The review also points out gaps in the body of knowledge and recommends areas for future study to provide novel and reliable analytical techniques for detecting DPH.Researchers,analysts,and regulatory bodies engaged in toxicology,drug analysis,and pharmaceutical quality control will find this review’s conclusions helpful.展开更多
文摘The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.
基金Supported by Special Project of the Central Government in Guidance of Local Science and Technology Development (Scientific and Technological Innovation Base Project) (226Z5504G)The Fourth Batch of High-end Talent Project in Hebei Province.
文摘Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized relevant literatures published in recent years,and sorted out and analyzed the types of pesticides used and detection techniques of common diseases in Chinese chives.
文摘Plant diseases and pests present significant challenges to global food security, leading to substantial losses in agricultural productivity and threatening environmental sustainability. As the world’s population grows, ensuring food availability becomes increasingly urgent. This review explores the significance of advanced plant disease detection techniques in disease and pest management for enhancing food security. Traditional plant disease detection methods often rely on visual inspection and are time-consuming and subjective. This leads to delayed interventions and ineffective control measures. However, recent advancements in remote sensing, imaging technologies, and molecular diagnostics offer powerful tools for early and precise disease detection. Big data analytics and machine learning play pivotal roles in analyzing vast and complex datasets, thus accurately identifying plant diseases and predicting disease occurrence and severity. We explore how prompt interventions employing advanced techniques enable more efficient disease control and concurrently minimize the environmental impact of conventional disease and pest management practices. Furthermore, we analyze and make future recommendations to improve the precision and sensitivity of current advanced detection techniques. We propose incorporating eco-evolutionary theories into research to enhance the understanding of pathogen spread in future climates and mitigate the risk of disease outbreaks. We highlight the need for a science-policy interface that works closely with scientists, policymakers, and relevant intergovernmental organizations to ensure coordination and collaboration among them, ultimately developing effective disease monitoring and management strategies needed for securing sustainable food production and environmental well-being.
文摘In recent years,the prevalence of allergens in food warning notices,both domestically and internationally,has become the second leading concern after microbial contamination.Among the various factors that threaten human health reported by the World Health Organization,food allergy ranks fourth,and food allergy has become a global security problem.As of now,no definitive treatment for food allergies exists,making the avoidance of allergen-containing foods the most effective prevention method.Consequently,labeling foods with allergen information serves as a crucial warning for allergic populations.Moreover,to enhance comprehension of food allergies,this article provides a brief overview of their definition and sensitization mechanisms.The main focus lies in highlighting the structure of primary allergens found in eight commonly allergenic foods and the resulting clinical symptoms they cause.Additionally,a summary of commonly employed allergen detection techniques is presented,with an analysis of their principles,advantages,and limitations.Looking ahead,the integration of diverse technological approaches to establish an efficient,accurate,and affordable allergen detection method remains a significant trend.This article has certain reference value for understanding the direction of food allergies.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
文摘Face recognition has emerged as one of the most prominent applications of image analysis and under-standing,gaining considerable attention in recent years.This growing interest is driven by two key factors:its extensive applications in law enforcement and the commercial domain,and the rapid advancement of practical technologies.Despite the significant advancements,modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions,occlusion,and diverse facial postures.In such scenarios,human perception is still well above the capabilities of present technology.Using the systematic mapping study,this paper presents an in-depth review of face detection algorithms and face recognition algorithms,presenting a detailed survey of advancements made between 2015 and 2024.We analyze key methodologies,highlighting their strengths and restrictions in the application context.Additionally,we examine various datasets used for face detection/recognition datasets focusing on the task-specific applications,size,diversity,and complexity.By analyzing these algorithms and datasets,this survey works as a valuable resource for researchers,identifying the research gap in the field of face detection and recognition and outlining potential directions for future research.
文摘One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability requirement. In this survey paper, we provide a classification of attacks based on the OSI model and discuss in more detail the cyber-attacks that can target the different layers of smart grid networks communication. We also propose new classifications for the detection and countermeasure techniques and describe existing techniques under each category. Finally, we discuss challenges and future research directions.
文摘Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.
文摘This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.
基金Supported by Hebei Provincial Outstanding Talent Development ProgramTangshan Talent Funding Project(A202202005).
文摘Food safety has always been a critical issue concerning people s livelihoods.The complexity and diversity of hazardous substances in food make systematical and scientifical identification of potential risk factors affecting food safety and accurate assessment and early warning for such risks one of the urgent problems for food safety inspection authorities.This paper explored food safety risk identification technologies,food safety risk monitoring technologies,and food safety risk early warning methods,aiming to provide theoretical support and research insights for improving food risk early warning systems.
文摘This research study predominantly emphases on spatiotemporal extensions of urban area of Peshawar;its adverse impacts and contributions to climate and environment during 1931 to 2011. To probe these interventions, meteorological data, Satellite’s temporal imagery of Landsat ETM+ and TM, anthropogenic and demographic secondary data were congregated. In relation to map out land cover changes, maximum likelihood classification algorithm and followed by change detection techniques were applied to study area. The outcome of this process was further subjected through Geographic Information System (GIS) overlay analysis which suggested a clear straggle in urban area. Auxiliary data (Population growth rate, transportation, electricity connections, etc.) also support the fact of urban area extension. This study proposes that severs contributions of massive heat energy and CO<sub>2</sub> have been added to local climate and environment ensuing substantial increment in temperature drawn out from the trends. Consequently, Remote Sensing, GIS and allied data were found to be effective to gauge such variations. To eliminate anomalies in sprawl and environment, few suggestions and recommendation are made in latter part of this study.
基金This work was supported by the Natural Sciences Foundation of China (Grant No. NSFC. 40176036).
文摘Objective To develop an in situ PCR in combination with flow cytometry （ISPCR-FCM） for monitoring cholera toxin positive Vibrio cholerae. Methods In running this method, 4% paraformaldehyde was used to fix the Vibrio cholerae cells and 1 mg/mL lysozyme for 20 min to permeabilize the cells. Before the PCR thermal cycling, 2.5% glycerol was added into the PCR reaction mixture in order to protect the integrality of the cells. Results A length of 1037bp DNA sequence was amplified, which is specific for the cholera toxin gene （ctxAB gene）. Cells subjected to ISPCR showed the presences of ctxAB gene both in epifluorescence microscopy and in flow cytometric analysis. The specificity and sensitivity of the method were investigated. The sensitivity was relatively low （10^5 cells/mL）, while the specificity was high. Conclusion We have successfully developed a new technique for detection of toxigenic Vibrio cholerae strains. Further study is needed to enhance its sensitivities. ISPCR-FCM shows a great promise in monitoring specific bacteria and their physiological states in environmental samples.
基金supported by a National Research Foundation of Korea(NRF)Grant funded by the Korean government(MSIT)(No.NRF-2017R1E1A1A01075110).
文摘Side-channel attacks have recently progressed into software-induced attacks.In particular,a rowhammer attack,which exploits the characteristics of dynamic random access memory(DRAM),can quickly and continuously access the cells as the cell density of DRAM increases,thereby generating a disturbance error affecting the neighboring cells,resulting in bit flips.Although a rowhammer attack is a highly sophisticated attack in which disturbance errors are deliberately generated into data bits,it has been reported that it can be exploited on various platforms such as mobile devices,web browsers,and virtual machines.Furthermore,there have been studies on bypassing the defense measures of DRAM manufacturers and the like to respond to rowhammer attacks.A rowhammer attack can control user access and compromise the integrity of sensitive data with attacks such as a privilege escalation and an alteration of the encryption keys.In an attempt to mitigate a rowhammer attack,various hardware-and software-based mitigation techniques are being studied,but there are limitations in that the research methods do not detect the rowhammer attack in advance,causing overhead or degradation of the system performance.Therefore,in this study,a rowhammer attack detection technique is proposed by extracting common features of rowhammer attack files through a static analysis of rowhammer attack codes.
文摘Metastasis usually presents in the different courses of tumor diseases and associates with poor prognosis.Circulating tumor cells(CTC) are considered to be essential for conforming metastasis and can be detected in tumor patients' peripheral blood.CTC are not easily detected by conventional cytology methods because of their low frequency in peripheral blood.Our article reviews the recent research results on this subject,and also discusses the problems and prospects in this area.
基金Project(50778015)supported by the National Natural Science Foundation of ChinaProject(2012CB725403)supported by the Major State Basic Research Development Program of China
文摘A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.
基金supported by the National Natural Science Foundation of China(52175115,52405587)supported by the China Postdoctoral Science Foundation(2023M740922)Postdoctoral Fellowship Program of CPSF(GZB20230953).
文摘Cancer,as one of the most notorious health diseases,represents the main reason attributed to millions of worldwide deaths each year.Timely detection and accurate diagnosis are thus vital to cancer prevention and timely therapy.Traditional cancer prescreening is not only cumbersome but also heavily reliant on sufficient expert knowledge,which inevitably increases the complexity of cancer diagnosis and limits early cancer diagnosis.To overcome this problem,recent terahertz(THz)technology,as an unconventional bio-friendly detection approach,has emerged with great potential in human disease diagnosis due to its non-ionic and high-resolution features.By combining the THz detection technique and artificial intelligence technique,here we propose a dense and efficient channel attention network(DECANet)framework-based THz diagnosis system for cancer prescreening.The cancer identification and diagnosis process are transformed into one end-to-end classification process of THz signals reflected from cancer tissue.The biosamples of breast and skin cancer tissue are characterized to validate the effectiveness and applicability of the proposed approach.Our quantified results indicate that our proposed THz diagnosis framework has promising feature extraction capability for abnormal cancerous tissue and provides an effective complement tool to assist the healthcare cancer diagnosis.
基金This work was financially supported by the National Risk Assessment Laboratory of Agro-products Processing Quality and Safety,Ministry of Agriculture and Rural Affairs of the People’s Republic of China(S2021KFKT-14)the National Natural Science Foundation of China(32102079+2 种基金32072290)the Key Project of Zhejiang Provincial Natural Science Foundation of China(LZ22C200003)Zhejiang Provincial Department of Agriculture and Rural Affairs(2022SNJF020,2022SNJF069).
文摘Biogenic amine is one of the main categories of hazardous compounds in meat and meat products,making its detection methods vital for the assurance of edible safety.In this sense,many biogenic amine detection techniques such as chromatographic,electrophoretic,and electrochemical methods have been developed,which play an irreplaceable role in ensuring the safety of meat and meat products.Due to the increasing demand for fast and on-site detection techniques,visual detection methods have been gradually developed compared with non-visual methods such as chromatography and electrophoresis.Herein,we comprehensively review the mechanism and the latest progress of these biogenic amine detection methods;besides,we put forward the prospects for the future development of biogenic amine detection techniques,with a view to providing support for the establishment of more accurate and efficient detection,prevention and control strategies of biogenic amines.
基金the National Science Foundation through the International Collaboration Supplement of Grant No.CMS-0202320the HongKong Research Grants Council via the Competitive Earmarked Research Grant HKUST6220/01E
文摘The concept of health monitoring is a key aspect of the field of medicine that has been practiced for a long time. A commonly used diagnostic and health monitoring practice is pulse diagnosis, which can be traced back approximately five thousand years in the recorded history of China. With advances in the development of modern technology, the concept of health monitoring of a variety of engineering structures in several applications has begun to attract widespread attention. Of particular interest in this study is the health monitoring of civil structures. It seem natural, and even beneficial, that these two health-monitoring methods, one as applies to the human body and the other to civil structures, should be analyzed and compared. In this paper, the basic concepts and theories of the two monitoring methods are first discussed. Similarities are then summarized and commented upon. It is hoped that this correlation analysis may help provide structural engineers with some insights into the intrinsic concept of using pulse diagnosis in human health monitoring, which may of be some benefit in the development of modern structural health monitoring methods.
文摘Based on the transmitting theory of "smoke ring effect", the transient electromagnetism technique was used in coal mines to detect abnormal areas of aquiferous structures in both roofs and floors of coal seams and in front of excavated roadways. Survey devices, working methods and techniques as well as data processing and interpretation are discussed systematically. In addition, the direction of mini-wireframe emission electromagnetic wave of the full space transient electromagnetism technique was verified by an underground borehole for water detection and drainage. The result indicates that this technique can detect both horizontal and vertical development rules of abnormal water bodies to a certain depth below the floor of coal seams and can also detect the abnormal, low resistance water bodies within a certain distance of roofs. Furthermore, it can detect such abnormal bodies in ahead of the excavated roadway front. Limited by the underground environment, the full space transient electromagnetism technique can detect to a depth of only 120 m or so.
文摘Diphenhydramine(DPH),a commonly used over-the-counter(OTC)antihistamine and sedative,requires accurate and reliable analytical methods to be evaluated in various matrices.The systematic review provides a comprehensive analysis of the current analytical techniques to detect DPH in biological samples and pharmaceutical formulations between 2012 and 2022.Case reports of DPH-related fatalities and intoxications were included along with crime statistics of OTC drug seizure in India from 2017 to 2021.The review also points out gaps in the body of knowledge and recommends areas for future study to provide novel and reliable analytical techniques for detecting DPH.Researchers,analysts,and regulatory bodies engaged in toxicology,drug analysis,and pharmaceutical quality control will find this review’s conclusions helpful.
