scholarly journals Detection and categorization of severe cardiac disorders based solely on pulse interval measurements

2022 ◽  
Author(s):  
Shigeru Shinomoto ◽  
Yasuhiro Tsubo ◽  
Yoshinori Marunaka
Keyword(s):  
Detection System ◽  
Local Variation ◽  
Automated System ◽  
Pulse Interval ◽  
Medical Practitioners ◽  
Conventional Analysis ◽  
Suitable Combination ◽  
Cardiac Disorders ◽  
Cardiac Status ◽  
Better Than

Cardiac disorders are common conditions associated with a high mortality rate. Due to their potential for causing serious symptoms, it is desirable to constantly monitor cardiac status using an accessible device such as a smartwatch. While electrocardiograms (ECGs) can make the detailed diagnosis of cardiac disorders, the examination is typically performed only once a year for each individual during health checkups, and it requires expert medical practitioners to make comprehensive judgments. Here we describe a newly developed automated system for alerting individuals about cardiac disorders solely based on pulse interval measurements. For this purpose, we examined two metrics of heart rate variability (HRV) and analyzed 1-day ECG recordings of more than 1,000 subjects in total. We found that a newly introduced metric of local variation was more efficient than conventional HRV metrics for detecting premature contraction, and furthermore, that a suitable combination of the old and new metrics resulted in much superior detectability particularly for atrial fibrillation, which requires more attention. Even with a 1-minute recording of pulse intervals, our new detection system had a diagnostic performance even better than that of the conventional analysis method applied to a 1-day recording.

scholarly journals Design and Implementation of Automated Steganography Image-Detection System for the KakaoTalk Instant Messenger

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 103
Author(s):  
Jun Park ◽  
Youngho Cho
Keyword(s):  
Detection System ◽  
Automated Detection ◽  
Automated System ◽  
Detection Methods ◽  
Image Detection ◽  
Social Network Service ◽  
Detection Algorithms ◽  
Instant Messenger ◽  
And Control ◽  
Better Than

As the popularity of social network service (SNS) messengers (such as Telegram, WeChat or KakaoTalk) grows rapidly, cyberattackers and cybercriminals start targeting them, and from various media, we can see numerous cyber incidents that have occurred in the SNS messenger platforms. Especially, according to existing studies, a novel type of botnet, which is the so-called steganography-based botnet (stego-botnet), can be constructed and implemented in SNS chat messengers. In the stego-botnet, by using various steganography techniques, every botnet communication and control (C&C) messages are secretly embedded into multimedia files (such as image or video files) frequently shared in the SNS messenger. As a result, the stego-botnet can hide its malicious messages between a bot master and bots much better than existing botnets by avoiding traditional botnet-detection methods without steganography-detection functions. Meanwhile, existing studies have focused on devising and improving steganography-detection algorithms but no studies conducted automated steganography image-detection system although there are a large amount of SNS chatrooms on the Internet and thus may exist many potential steganography images on those chatrooms which need to be inspected for security. Consequently, in this paper, we propose an automated system that detects steganography image files by collecting and inspecting all image files shared in an SNS chatroom based on open image steganography tools. In addition, we implement our proposed system based on two open steganography tools (Stegano and Cryptosteganography) in the KakaoTalk SNS messenger and show our experimental results that validate our proposed automated detection system work successfully according to our design purposes.

Sustainable Security for the Internet of Things Using Artificial Intelligence Architectures

2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Experimental Testing ◽  
Cyber Attacks ◽  
Internet Technology ◽  
The Internet ◽  
Business Operations ◽  
Private Data ◽  
The Internet Of Things ◽  
Better Than

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.

System of Warning about Dangerous Atmospheric Phenomena in the North Caucasus for Objects of Economic Activity

2018 ◽  
Vol 931 ◽  
pp. 1019-1024
Author(s):  
Vitaliy A. Shapovalov
Keyword(s):  
Land Reclamation ◽  
Detection System ◽  
Radar Data ◽  
Automated System ◽  
Insurance Companies ◽  
North Caucasus ◽  
Weather Radars ◽  
The North ◽  
Lightning Detection ◽  
Atmospheric Phenomena

This paper presents the developed program-mathematical software for receiving, archiving, analysis and display of radar, lightning and satellite data on clouds and precipitation, interfacing of meteorological information. The program of processing of meteorological information "GIMET-2010" is established on a network of weather radars DMRL-C of the Russian Federation. An automated system combining radar and lightning detection system information applies to the command posts of the uniformed services on the fight against hail and centers of severe storm warning. Following items are provided: a receiving and transmitting to consumers the operational radar data on the actual weather; the detection, identification, and warning of hazardous weather phenomena for airports and populated areas; measurement of the intensity and amount of precipitation for agriculture, hydrological forecasts and land reclamation; obtaining precipitation map for agriculture and insurance companies.

scholarly journals A MODEL OF PETROLEUM PIPELINE SPILLAGE DETECTION SYSTEM FOR USE IN THE NIGER DELTA REGION OF NIGERIA

2016 ◽  
Vol 4 (12) ◽  
pp. 1-16
Author(s):  
Franklin OvueleloloOkorodudu ◽  
Philip OgheneogagaOkorodudu ◽  
Ekerikevwe Kennedy Irikefe
Keyword(s):  
Niger Delta ◽  
Detection System ◽  
Base Station ◽  
Drastic Reduction ◽  
Niger Delta Region ◽  
Switching Unit ◽  
Signal Path ◽  
Data Book ◽  
Microcontroller Unit ◽  
Better Than

In recent times, petroleum pipeline vandalism resulting into spillage has become a significant challenge in Nigeria. Citizens are regularly inundated with reported cases of vandalism which often lead to spillage and a drastic reduction in government’s revenue as is currently the case in Nigeria. This paper focuses on the design of petroleum pipeline spillage detection system. The design consists of the power supply unit, the comparator unit, the microcontroller unit, the switching unit, the transceiver unit and the base station. Simulation of the various units was done individually using the procedural programming application Proteus 8. Most of the components used were according to design specifications from data book with alternatives used in cases where they are unavailable. Wiring sensors which provided continuous electrical paths to break the signal path and trigger an alarm at the base station were used The design was done in units and were tested individually and the whole system was tested to perform the required task of detecting petroleum spillage and alerting the control room for action. It is found that the designed system had the advantage of responding to intrusion and vandalism better than existing systems.

scholarly journals An Electrocardiograph based Arrythmia Detection System

2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Veena K N ◽  
Shobha S.
Keyword(s):  
Detection System ◽  
Physical Symptoms ◽  
Heart Beat ◽  
Block Type ◽  
Ecg Signal ◽  
Av Block ◽  
Arrhythmia Detection ◽  
Cardiac Disorder ◽  
Cardiac Disorders ◽  
Serious Disease

Cardiac disorders turn out to be a serious disease if not diagnosed and treated at the earliest. Arrhythmia is a cardiac disorder that exists as a result of irregular heart beat conditions. There are several variants in this type of disorder which can be only diagnosed only when patient is under an intensive care conditions and also the patient with such disorder do not experience and physical symptoms. Such diseases turn out to be deadly if not treated early. A detection system is thus required which is capable of detecting these arrhythmias in real time and aid in the diagnosis. An FPGA based arrhythmia detection system is designed and implemented here which can detect second degree AV block type of arrhythmia. The designed system was simulated and tested with ECG signal from MIT-BH database and the results revealed that a robust arrhythmia detection system was implemented.

Accelerate Pheno™ blood culture detection system: a literature review

2020 ◽  
Vol 15 (16) ◽  
pp. 1595-1605
Author(s):  
Elio Cenci ◽  
Riccardo Paggi ◽  
Giuseppe V De Socio ◽  
Silvia Bozza ◽  
Barbara Camilloni ◽  
...  
Keyword(s):  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Detection System ◽  
Operating Time ◽  
Bloodstream Infections ◽  
Antimicrobial Susceptibility Testing ◽  
Automated System ◽  
Clinical Role ◽  
Stewardship Program ◽  
The Impact

Accelerate Pheno™ (ACC) is a fully automated system providing rapid identification of a panel of bacteria and yeasts, and antimicrobial susceptibility testing of common bacterial pathogens responsible for bloodstream infections and sepsis. Diagnostic accuracy for identification ranges from 87.9 to 100%, and antimicrobial susceptibility testing categorical agreement is higher than 91%. The present review includes peer-reviewed studies on ACC published to date. Both interventional and hypothetical studies evidenced the potential positive clinical role of ACC in the management and therapy of patients with bloodstream infections and sepsis, due to the important reduction in time to report, suggesting a crucial impact on the therapeutic management of these patients, provided the presence of a hospital antimicrobial stewardship program, a 24/7 laboratory operating time and a strict collaboration between clinical microbiologist and clinician. Further prospective multicenter studies are necessary to explore the impact of this system on mortality, length of stay and spread of multidrug-resistant organisms.

scholarly journals KM3NeT acoustic positioning and detection system

2019 ◽  
Vol 216 ◽  
pp. 02006 ◽  
Author(s):  
Salvatore Viola
Keyword(s):  
Cherenkov Radiation ◽  
Detection System ◽  
Charged Particles ◽  
Positioning System ◽  
Atmospheric Neutrinos ◽  
Neutrino Telescopes ◽  
Strongly Connected ◽  
Radiation Induced ◽  
Better Than ◽  
Acoustic Positioning

In the Mediterranean Sea, the KM3NeT Collaboration is constructing a the deep-sea research infrastructure hosting next generation neutrino telescopes. In the KM3NeT telescopes the Cherenkov radiation induced by the secondary charged particles produced in the interaction of cosmic and atmospheric neutrinos within an effective volume between megaton and several cubic kilometers of water are detected by an array of thousands of photomultipliers. The capability of the telescope to determine the direction of secondary charged particles and to point back to the neutrino source is strongly connected to the accuracy on photomultipliers positions. In KM3NeT, the photomultiplier positions are continuously monitored by an acoustic positioning system, designed by the KM3NeT Collaboration to reach an accuracy of the photomultiplier positions better than 20 cm.

The Role of the Computer in Team Problem-Solving: Critiquing or Partial Automation?

1993 ◽  
Vol 37 (15) ◽  
pp. 1029-1029
Author(s):  
Stephanie A. E. Guerlain ◽  
Philip J. Smith
Keyword(s):  
Problem Solving ◽  
Computer System ◽  
Real World ◽  
Automated System ◽  
Computer Interface ◽  
Rule Base ◽  
Heuristic Strategy ◽  
System Designs ◽  
Better Than

A testbed was developed for studying the effects of different computer system designs on human-computer team problem-solving, using the real-world task of antibody identification. The computer interface was designed so that practitioners could solve antibody identification cases using the computer as they normally would using paper and pencil. A rule-base was then encoded into the computer such that it had knowledge for applying a heuristic strategy that is often helpful for solving cases. With this testbed, studies have been run comparing different computer system designs. A critiquing system was found to be better than a partially automated system on cases where the computer's knowledge is incompetent.

An Automated Detection System for Most L-α-Amino Acids

1969 ◽  
Vol 15 (2) ◽  
pp. 154-161 ◽  
Author(s):  
K Van Dyke ◽  
C Szustkiewicz
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Detection System ◽  
Automated System ◽  
Acid Oxidase ◽  
Enzymatic Reactions ◽  
Amino Acid Oxidase ◽  
Automated Method ◽  
Wide Range

Abstract An automated system for the determination of the L-α form of the majority of amino acids is presented. The method is based upon oxidative deamination of the amino acid coupled with oxidation of o-dianisidine by hydrogen peroxide. This procedure can be used comparatively for the determination of a mixture of L-α-amino acids or for the majority of separated L-α-amino acids (especially in conjunction with column separations from urine and blood which give falsely positive identification with ninhydrin detection). The stereospecific nature of the L-α-amino acid oxidase enables the investigator to quantitate the amount of L-α-amino acid in the presence of the D-α form. From an academic viewpoint, the extreme sensitivity and wide range of the detection system make it advantageous for the study of the enzyme itself. This automated method also may be employed to follow enzymatic reactions—e.g., those catalyzed by peptidases or racemases. The methodology is extremely convenient with good reagent stability and is much more sensitive than manometric technics.

scholarly journals A Framework for Detecting Vehicle Occupancy Based on the Occupant Labeling Method

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jooyoung Lee ◽  
Jihye Byun ◽  
Jaedeok Lim ◽  
Jaeyun Lee
Keyword(s):  
Detection System ◽  
Automated Detection ◽  
Detection Accuracy ◽  
Occupancy Detection ◽  
Single Side ◽  
Binary Case ◽  
Left And Right ◽  
Hov Lanes ◽  
Labeling Method ◽  
Better Than

High-occupancy vehicle (HOV) lanes or congestion toll discount policies are in place to encourage multipassenger vehicles. However, vehicle occupancy detection, essential for implementing such policies, is based on a labor-intensive manual method. To solve this problem, several studies and some companies have tried to develop an automated detection system. Due to the difficulties of the image treatment process, those systems had limitations. This study overcomes these limits and proposes an overall framework for an algorithm that effectively detects occupants in vehicles using photographic data. Particularly, we apply a new data labeling method that enables highly accurate occupant detection even with a small amount of data. The new labeling method directly labels the number of occupants instead of performing face or human labeling. The human labeling, used in existing research, and occupant labeling, this study suggested, are compared to verify the contribution of this labeling method. As a result, the presented model’s detection accuracy is 99% for the binary case (2 or 3 occupants or not) and 91% for the counting case (the exact number of occupants), which is higher than the previously studied models’ accuracy. Basically, this system is developed for the two-sided camera, left and right, but only a single side, right, can detect the occupancy. The single side image accuracy is 99% for the binary case and 87% for the counting case. These rates of detection are also better than existing labeling.

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