scholarly journals Early Detection Techniques for Osteoporosis

Osteoporosis ◽  
10.5772/29798 ◽  
2012 ◽  
Author(s):  
Kanika Singh ◽  
Kyung Chun
Keyword(s):  
Early Detection ◽  
Detection Techniques

scholarly journals Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3052
Author(s):  
Mas Ira Syafila Mohd Hilmi Tan ◽  
Mohd Faizal Jamlos ◽  
Ahmad Fairuz Omar ◽  
Fatimah Dzaharudin ◽  
Suramate Chalermwisutkul ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Early Detection ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Analytics ◽  
Detection System ◽  
Imaging Techniques ◽  
Ganoderma Boninense ◽  
Machine Learning Classification ◽  
Detection Techniques

Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.

scholarly journals Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies

Chemosensors ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 7 ◽  
Author(s):  
Monika Garbacz ◽  
Agnieszka Malec ◽  
Sylwia Duda-Saternus ◽  
Zbigniew Suchorab ◽  
Łukasz Guz ◽  
...  
Keyword(s):  
Early Detection ◽  
Gas Sensor ◽  
Sick Building Syndrome ◽  
Sensor Arrays ◽  
Short Review ◽  
Detection Methods ◽  
Detection Techniques ◽  
Microbiological Techniques ◽  
Chemical Conditions ◽  
Gas Sensor Arrays

In this review, the problem of microbiological infestation of buildings was discussed. The techniques of detection were described as well, with special attention drawn to the rapid-early detection methods based on gas sensor arrays. The physical and chemical conditions of the building environment conducive to the development of microorganisms and the technical conditions influencing the problem of microbiological infestation were investigated. Additionally, the harmful effects on human health caused by the microbiological contamination were discussed, with a short review of particular groups of microorganisms causing sick building syndrome. Among the detection techniques, the traditional microbiological techniques as well as the molecular and chemical methods were presented. Different designs of the gas sensor arrays together with the various techniques of analyzing the received multidimensional signal were described, analyzed, and compared in detail.

A Novel Approach for the Early Detection and Identification of Botnets

2011 ◽  
Vol 403-408 ◽  
pp. 4469-4475
Author(s):  
S. Benson Edwin Raj ◽  
V.S. Jayanthi ◽  
R. Shalini
Keyword(s):  
Early Detection ◽  
Optimization Technique ◽  
Machine Learning Algorithms ◽  
Ip Address ◽  
Detection Techniques ◽  
Detection And Identification ◽  
Novel Approach ◽  
Size Number ◽  
Ip Spoofing ◽  
The Right

Botnets are growing in size, number and impact. It continues to be one of the top three web threats that mankind has ever known. The botnets are the souped-up cyber engines driving nearly all criminal commerce on the Internet and are seen as relaying millions of pieces of junk e-mail, or spam. Thus, the need of the hour is the early detection and identification of the heart of network packet flooding or the C&C centre. Most of the botmasters perform DDos attacks on a target server by spoofing the source IP address. The existing botnet detection techniques rely on machine learning algorithms and do not expound the IP spoofing issue. These approaches are also found to be unsuccessful in the meticulous identification of the botmasters. Here we propose an architecture that depend on the PSO-based IP tracebacking. Our architecture also introduces the IP spoofing detector unit so as to ensure that the Traceback moves in the right direction. The approach also detects the zombies and utilizes the PSO optimization technique that aid in the identification of the C&C node. The experimental results show that our approach is successful in prompt detection of the bots.

Identification and Classification of Cyber Threats Through SSH Honeypot Systems

2020 ◽  
pp. 105-129
Author(s):  
José María Jorquera Valero ◽  
Manuel Gil Pérez ◽  
Alberto Huertas Celdrán ◽  
Gregorio Martínez Pérez
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Machine Learning Algorithms ◽  
Intrusion Detection Systems ◽  
Security Systems ◽  
Detection Techniques ◽  
Detection Systems ◽  
Cyber Threats ◽  
Detection Capabilities

As the number and sophistication of cyber threats increases year after year, security systems such as antivirus, firewalls, or Intrusion Detection Systems based on misuse detection techniques are improved in detection capabilities. However, these traditional systems are usually limited to detect potential threats, since they are inadequate to spot zero-day attacks or mutations in behaviour. Authors propose using honeypot systems as a further security layer able to provide an intelligence holistic level in detecting unknown threats, or well-known attacks with new behaviour patterns. Since brute-force attacks are increasing in recent years, authors opted for an SSH medium-interaction honeypot to acquire a log set from attacker's interactions. The proposed system is able to acquire behaviour patterns of each attacker and link them with future sessions for early detection. Authors also generate a feature set to feed Machine Learning algorithms with the main goal of identifying and classifying attacker's sessions, and thus be able to learn malicious intentions in executing cyber threats.

Breast Cancer Screening: A Social Marketing Study

1996 ◽  
Vol 3 (1) ◽  
pp. 24-35 ◽  
Author(s):  
Carol A. Bryant ◽  
Stephen Cole ◽  
Bonnie Salazar ◽  
James Lindenberger ◽  
Kay Perrin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
United States ◽  
At Risk ◽  
Early Detection ◽  
Social Marketing ◽  
Underserved Populations ◽  
The United States ◽  
Physician Referral ◽  
Detection Techniques ◽  
Incidence And Mortality

Breast cancer is one of the leading types of preventable cancer among women in the United States. Despite improvements in mammography and early detection techniques for breast cancer, special population groups within the United States continue to experience high incidence and mortality rates. This paper focuses on Kentucky's underserved populations. The research objectives were to: 1) identify the factors that motivate women at risk to be screened for breast cancer; and, 2) identify the factors that deter women at risk from being screened for breast cancer. A combination of quantitative (survey n=407) and qualitative (focus groups=19; in-depth interviews=58) research methods were used to examine factors that influence mammography use. Factors that motivate women to have mammograms include: physician referral; the belief that early detection will improve breast cancer outcomes; and, the belief that a mammogram is an effective test. Factors deterring women from having mammograms include: lack of physician referral; cost; and, the belief that mammography is dangerous. Research findings point to the need for a comprehensive, integrated approach to increasing utilization rates. This approach includes recommendations for increasing physician referrals, modifying service delivery, training staff, and development of client education materials and a public information campaign. These recommendations have been incorporated into a social marketing plan to increase utilization of mammography services in the state of Kentucky.

A Study to Assess the Knowledge regarding Early Detection of Oral Cancer among Professional Drivers attending Regional Transport Office Thiruvalla

2021 ◽  
pp. 257-261
Author(s):  
Anu K Chacko ◽  
Anu Varghese ◽  
Binitha Susan Simon ◽  
Jessy Aley Varghese ◽  
Lincy K Abraham ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Early Detection ◽  
Sampling Technique ◽  
Knowledge Score ◽  
Research Approach ◽  
Chi Square ◽  
Regional Transport ◽  
Professional Drivers ◽  
Detection Techniques ◽  
Chi Square Test

In most people’s minds there is no scarier diagnosis than that of cancer. Cancer is often thought as and untreatable, unbearably painful disease with no cure. Cancer is undoubtedly a serious and potentially life-threatening illness. It is the leading cause of death in Indians under the age of 85. One of the recent concerns playing the field of cancer study or oncology are the increasing number of men who are being diagnosed with cancer. We can reduce the rate of deaths regarding this with early detection techniques. This study is aimed to find out the level of knowledge regarding early detection of oral cancer among professional drivers using a structured questionnaire, to find the association between the pretest knowledge scores and selected baseline variables. Research approach adopted for the study was quantitative approach and research design was pre experimental (one group pretest). The study was conducted among professional drivers attending regional transport office Thiruvalla. The sample of the study was selected by convenient sampling technique and sample size was 30. The pilot study was conducted with 8 samples following to which the data collection procedure was carried out. The main study was conducted among professional drivers attending Regional Transport Office Thiruvalla. Data analysis was done by using chi-square test and the result shows that 15 (50.0%) samples have poor knowledge, 14 (46.7%) samples have average knowledge and 1(3.3%) samples have good knowledge. It was also found that there is a moderate significant association with education level and knowledge score (p=0.07.

scholarly journals Emerging advances of in vivo detection of chronic traumatic encephalopathy and traumatic brain injury

2019 ◽  
Vol 92 (1101) ◽  
pp. 20180925 ◽  
Author(s):  
Julian D. Dallmeier ◽  
Somayeh Meysami ◽  
David A. Merrill ◽  
Cyrus A. Raji
Keyword(s):  
Early Detection ◽  
Diffusion Mri ◽  
Neurodegenerative Disorder ◽  
Chronic Traumatic Encephalopathy ◽  
Neurofibrillary Tangle ◽  
Detection Methods ◽  
Detection Techniques ◽  
In Vivo Detection ◽  
Neuroimaging Techniques

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder that is of epidemic proportions in contact sports athletes and is linked to subconcussive and concussive repetitive head impacts (RHI). Although postmortem analysis is currently the only confirmatory method to diagnose CTE, there has been progress in early detection techniques of fluid biomarkers as well as in advanced neuroimaging techniques. Specifically, promising new methods of diffusion MRI and radionucleotide PET scans could aid in the early detection of CTE. The authors examine early detection methods focusing on various neuroimaging techniques. Advances in structural and diffusion MRI have demonstrated the ability to measure volumetric and white matter abnormalities associated with CTE. Recent studies using radionucleotides such as flortaucipir and 18F-FDDNP have shown binding patterns that are consistent with the four stages of neurofibrillary tangle (NFT) distribution postmortem. Additional research undertakings focusing on fMRI, MR spectroscopy, susceptibility-weighted imaging, and singlephoton emission CT are also discussed as are advanced MRI methods such as diffusiontensor imaging and arterial spin labeled. Neuroimaging is fast becoming a key instrument in early detection and could prove essential for CTE quantification. This review explores a global approach to in vivo early detection. Limited data of in vivo CTE biomarkers with postmortem confirmation are available. While some data exist, they are limited by selection bias. It is unlikely that a single test will be sufficient to properly diagnosis and distinguish CTE from other neurodegenerative diseases such as Alzheimer disease or Frontotemporal Dementia. However, with a combination of fluid biomarkers, neuroimaging, and genetic testing, early detection may become possible.

scholarly journals Knowledge, attitude and practice of Sri Lankan women towards breast cancer: A cross sectional study

2020 ◽  
Author(s):  
N.D. Ranaweera ◽  
P.M.C. Dinesha ◽  
C.A.K. Pathirage ◽  
P.W.D.N. Weerasinghe ◽  
D.M.K.N. Senarathna ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Sri Lanka ◽  
Early Detection ◽  
Signs And Symptoms ◽  
Good Knowledge ◽  
Screening Methods ◽  
Breast Cancers ◽  
Detection Techniques ◽  
Cancer Hospital

Abstract Introduction Breast cancer is a type of cancer that develops from breast tissue. Although the knowledge on breast cancer among women in Sri Lanka is high, their practice of breast self-examination is poor. This study was aimed to determine attitudes, practices and the awareness of early detection techniques and risk factors among women in Sri Lanka. Method A study was conducted between two groups in National Cancer hospital, Sri Lanka and a peripheral women clinic consisting 317 participants in each group. Self-administered questionnaire was used to collect data regarding the awareness of early detection techniques, signs and symptoms and risk factors for breast cancers. Results A total of 33.8% of peripheral women clinic and 65.0% in National Cancer hospital patients had good knowledge regarding risk factors. The knowledge of risk factors, signs and symptoms and screening methods about breast cancers was significantly high in patients attending to National cancer hospital. Older aged people have less awareness about screening methods compared to younger people. People with high education background and those have a family history of breast cancer had more aware about screening and therapeutic methods. Conclusion Comparative to the peripheral women clinic, patients attending to National Cancer Hospital had a fairly good knowledge, practice and attitude regarding the early detection techniques, risk factors, signs and symptoms.

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