Search results for: aortic dissection detection risk score

Authors: Sule Pallavi, Shah Priyank, Thavkar Amit, Rohira Poonam, Mehta Suyog

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Introduction: Minoxidil has been used topically for a long time to assist hair growth in the management of male androgenetic alopecia. The aim of this study was a comparative assessment of the irritation potential of three commercial formulations of minoxidil 2% topical solution in a human patch test. Methodology: The study was a non-randomized, double-blind, controlled, single-center study of 56 healthy adult Indian subjects. A 24-hour occlusive patch test was conducted with three formulations of minoxidil 2% topical solution. Products tested were aqueous-based minoxidil 2% (AnasureTM 2%, Sun Pharma, India – Brand A), alcohol-based minoxidil 2% (Brand B) and aqueous-based minoxidil 2% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate as a negative and positive control, respectively, were included. Patches were applied on the back, followed by removal after 24 hours. The Draize scale (0-4 points scale for erythema/dryness/wrinkles and for oedema) was used to evaluate and clinically score the skin reaction under constant artificial daylight 24 hours after the removal of the patches. The patch test was based on the principles outlined by Bureau of Indian Standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). A mean combined score up to 2.0/8.0 indicates that a product is “non-irritant,” and a score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and a score above 4.0/8.0 indicates “irritant”. In case of any skin reaction that was observed, a follow-up was planned after one week to confirm recovery. Results: The 56 subjects who participated in the study had a mean age of 28.7 years (28 males and 28 females). The combined mean score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.29± 0.53 (Brand B), 0.30 ± 0.46 (Brand C), 3.25 ± 0.77 (positive control) and 0.02 ± 0.13 (negative control). This mean score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.016) and that of Brand C (p=0.004). The mean erythema score ± standard deviation was: 0.09 ± 0.29 (Brand A), 0.27 ± 0.49 (Brand B), 0.30 ± 0.46 (Brand C), 2.5 ± 0.66 (positive control) and 0.02 ± 0.13 (negative control). The mean erythema score of Brand A (Sun Pharma) was significantly lower than that of Brand B (p=0.019) and that of Brand C (p=0.004). Reactions that were observed 24 hours after patch removal subsided in a week’s time. Conclusion: Based on the human patch test as per the BIS, IS 4011:2018, all the three topical formulations of minoxidil 2% were found to be non-irritant. Brand A of 2% minoxidil (Sun Pharma) was found to be the least irritant than Brand B and Brand C based on the combined mean score and mean erythema score.

Keywords: erythema, irritation, minoxidil, patch test

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

Procedia PDF Downloads 150

Authors: Siti Nor Amira Bt. Mohamad, Mohamad Yazis B. Ali Basah, Muhammad Ridhwan B. Ab. Aziz, Khairil Faizal B. Khairi, Mazlynda Bt. Md. Yusuf, Hisham B. Sabri

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The understanding of risk and the concept of it occurs associated in Islamic financing was well-known in the financial industry by the using of Profit-and-Loss Sharing (PLS). It was presently in any Islamic financial transactions in order to comply with shariah rules. However, the existence of risk in Murabahah contract of financing is an ability that the counterparty is unable to complete its obligations within the agreed terms. Therefore, it is called as credit or default risk. Credit risk occurs when the client fails to make timely payment after the bank makes complete delivery of assets. Thus, it affects the growth of the bank as the banking business is in no position to have appropriate measures to cover the risk. Therefore, the bank may impose penalty on the outstanding balance. This paper aims to highlight the credit risk determinant and issues surrounding in Islamic bank in Malaysia in terms of Murabahah financing and how to manage it by using the proper techniques. Finally, it explores the credit risk management concept that might solve the problems arise. The study found that the credit risk can be managed properly by improving the use of comprehensive reference checklist of business partners on their character and past performance as well as their comprehensive database. Besides that, prevention of credit risk can be done by using collateral as security against the risk and we also argue on the Shariah guidelines and procedures should be implement coherently by the banking business because so that the risk would be control by having an effective instrument for Islamic modes of financing.

Keywords: Islamic banking, credit risk, Murabahah financing, risk mitigation

Procedia PDF Downloads 449

Authors: Zeinab Farhat, Nicolas Errien, Romuald Wernert, Véronique Verriele, Frédéric Amiard, Philippe Daniel

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Ovarian cancer, also known as the silent killer, is the fifth most common cancer among women worldwide, and its death rate is higher than that of other gynecological cancers. The low survival rate of women with high-grade serous ovarian carcinoma highlights the critical need for the development of new methods for early detection and diagnosis of the disease. The aim of this study was to evaluate if Raman spectroscopy combined with chemometric methods such as Principal Component Analysis (PCA) could differentiate between cancerous and normal tissues from different types of samples, such as paraffin embedding, chemical deparaffinized, formalin-fixed and fresh samples of the same normal and malignant ovarian tissue. The method was applied specifically to two critical spectral regions: the signature region (860-1000 〖cm〗^(-1)) and the high-frequency region (2800-3100 〖cm〗^(-1) ). The mean spectra of paraffin-embedded in normal and malignant tissues showed almost similar intensity. On the other hand, the mean spectra of normal and cancer tissues from chemical deparaffinized, formalin-fixed, and fresh samples show significant intensity differences. These spectral differences reflect variations in the molecular composition of the tissues, particularly lipids and proteins. PCA, which was applied to distinguish between cancer and normal tissues, was performed on whole spectra and on selected regions—the PCA score plot of paraffin-embedded shows considerable overlap between the two groups. However, the PCA score of chemicals deparaffinized, formalin-fixed, and fresh samples showed a good discrimination of tissue types. Our findings were validated by analyses of a set of samples whose status (normal and cancerous) was not previously known. The results of this study suggest that Raman Spectroscopy associated with PCA methods has the capacity to provide clinically significant differentiation between normal and cancerous ovarian tissues.

Keywords: Raman spectroscopy, ovarian cancer, signal processing, Principal Component Analysis, classification

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Authors: Alhaji Musa Abdullahi, Usman Abdullahi, Adamu Lawan, Aminu Maidala

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Abstract 16 healthy lactating cows will be randomly selected for the trial and will be randomly divided in to 4 groups with 4 cows in each. They will be kept under similar management condition (conventional management system). Animals of relatively same weight and age will be used. After 11days for adaptation, feed intake and performance of the experimental animals will be determine. Milk sample will be collected at each milking in the morning and afternoon to determine; Milk yield, Milk fat percentage, Solid not fat percentage, Total solid percentage of milk. Cows dung will be observe to determine; Score 1 very loose watery stool, Score 2 semi solid with undigested raw material, Score 3 semi solid with less undigested raw material, Score 4 solid with very less undigested raw material, Score 5 good dung no undigested raw material. At the end of the experiment, blood samples will be analyzed for full blood counts and differentials {White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (Hb), Packed Cell Volume (PCV), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Platelets (PLT), Lymphocytes (LYM), Basophils, Eosinophils and Monocytes Proportion (MXD) and Neutrophils (NEUT)} using automated hematology analyzer. Serum samples will be analyzed for heat shock transcription factors, heat shock proteins and hormones (Serum glucocorticoid, prolactin and cortisol). Moreover, biochemical analysis will also be conducted to check for Total protein (TP), Albumen (ALB), Globulin (GBL), Total cholesterol (TCH), glucose (G), sodium (Na+), potassium (K+), chloride (Cl-) and pH. Keywords: Lactating cows, milk composition, dung score and blood parameters.

Keywords: Lactating cows , Milk yield , Dung score , Blood parameters

Procedia PDF Downloads 178

Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary

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We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.

Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning

Procedia PDF Downloads 232

Authors: Azar Baghtaghi

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Financial risk management is critically important as it enables companies to maintain stability and profitability amidst market fluctuations and unexpected events. It involves the precise identification of risks that could impact investments, assets, and potential revenues. By implementing effective risk management strategies, companies can insure themselves against adverse market changes and prevent potential losses. In today's era, where markets are highly complex and influenced by various factors such as macroeconomic policies, exchange rate fluctuations, and natural disasters, the need for meticulous planning to cope with these uncertainties is more pronounced. Ultimately, financial risk management means being prepared for the future and the ability to sustain business in changing environments. A company capable of managing its risks not only achieves sustainable profitability but also gains the confidence of shareholders, investors, and business partners, enhancing its competitive position in the market. In this article, the types of financial risk and risk management strategies for improving financial performance were investigated. By identifying the risks stated in this article and their evaluation techniques, it is possible to improve the organization's financial performance.

Keywords: strategy, risk, risk management, financial performance

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Authors: Saiakhil Chilaka

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Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: Aqleem Fatimah

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The purpose of study was to find out the impact of teachers’ gender on students’ score achievement. Focusing on primary level’s teachers & students, a survey research was conducted by using convenient sampling technique. All the students of grade four (1500) and fifty-six teachers (equally divided by gender) from the 50 randomly selected coeducational schools from Lahore were taken as sample. The academic performance was operationalized using a t-test on standardized achievement tests of the students in language, science mathematics and social studies. In addition, all those gender based characteristics of teachers that count a lot in classroom interactions (taking Multi-grade classes, classroom strategies, feedback strategies and evaluation method) that influence students’ achievement were also analyzed by using a questionnaire and an observation schedule. The results of the study showed better academic achievement of students (girl &boy) of female teachers comparatively to the students of male teachers. Therefore, as the female teachers’ number lacks in Pakistan, the study suggests policy makers to seek guidelines to induct more specialized and professionally competent female teachers because their induction will prove highly beneficial for the betterment of students’ score achievement.

Keywords: gender, teacher, competency, score achievement

Procedia PDF Downloads 313

Authors: O. J. G. Somsen

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One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simpler spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various width we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application

Keywords: anomaly detection, spectroscopic line imaging, image analysis, outdoor detection

Procedia PDF Downloads 476

Authors: Mende Mensa Sorato, Majid Davari, Abbas Kebriaeezadeh, Nizal Sarrafzadegan, Tamiru Shibru, Behzad Fatemi

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Markov model, like cardiovascular disease (CVD) policy model based simulation, is being used for evaluating the cost-effectiveness of hypertension treatment. Stroke, angina, myocardial infarction (MI), cardiac arrest, and all-cause mortality were included in this model. Hypertension is a risk factor for a number of vascular and cardiac complications and CVD outcomes. Objective: This systematic review was conducted to evaluate the comprehensiveness of this model across different regions globally. Methods: We searched articles written in the English language from PubMed/Medline, Ovid/Medline, Embase, Scopus, Web of Science, and Google scholar with a systematic search query. Results: Thirteen cohort studies involving a total of 2,165,770 (1,666,554 hypertensive adult population and 499,226 adults with treatment-resistant hypertension) were included in this scoping review. Hypertension is clearly associated with coronary heart disease (CHD) and stroke mortality, unstable angina, stable angina, MI, heart failure (HF), sudden cardiac death, transient ischemic attack, ischemic stroke, subarachnoid hemorrhage, intracranial hemorrhage, peripheral arterial disease (PAD), and abdominal aortic aneurism (AAA). Association between HF and hypertension is variable across regions. Treatment resistant hypertension is associated with a higher relative risk of developing major cardiovascular events and all-cause mortality when compared with non-resistant hypertension. However, it is not included in the previous CVD policy model. Conclusion: The CVD policy model used can be used in most regions for the evaluation of the cost-effectiveness of hypertension treatment. However, hypertension is highly associated with HF in Latin America, the Caribbean, Eastern Europe, and Sub-Saharan Africa. Therefore, it is important to consider HF in the CVD policy model for evaluating the cost-effectiveness of hypertension treatment in these regions. We do not suggest the inclusion of PAD and AAA in the CVD policy model for evaluating the cost-effectiveness of hypertension treatment due to a lack of sufficient evidence. Researchers should consider the effect of treatment-resistant hypertension either by including it in the basic model or during setting the model assumptions.

Keywords: cardiovascular disease policy model, cost-effectiveness analysis, hypertension, systematic review, twelve major cardiovascular events

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Authors: Chawarat Rotejanaprasert, Andrew Lawson

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Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

Procedia PDF Downloads 310

Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

Procedia PDF Downloads 420

Authors: Angela Meyer

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The operation and maintenance cost for wind parks make up a major fraction of the park’s overall lifetime cost. To minimize the cost and risk involved, an optimal operation and maintenance strategy requires continuous monitoring and analysis. In order to facilitate this, we present a decision support system that automatically scans the stream of telemetry sensor data generated from the turbines. By learning decision boundaries and normal reference operating states using machine learning algorithms, the decision support system can detect anomalous operating behavior in individual wind turbines and diagnose the involved turbine sub-systems. Operating personal can be alerted if a normal operating state boundary is exceeded. The presented decision support system and method are applicable for any turbine type and manufacturer providing telemetry data of the turbine operating state. We demonstrate the successful detection and diagnosis of anomalous operating states in a case study at a German onshore wind park comprised of Vestas V112 turbines.

Keywords: anomaly detection, decision support, machine learning, monitoring, performance optimization, wind turbines

Procedia PDF Downloads 163

Authors: Sohanur Rahman, Elisabeth Sinnewe, Larelle (Ellie) Chapple, Sarah Osborne

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Greater political attention to global climate change exposes firms to a higher level of political uncertainty, which can lead to adverse capital market consequences. However, a higher level of discourse on environment-specific political risk (EPR) between management and investors can mitigate information asymmetry, followed by less stock price crash risk. This study examines whether EPR discourse in discourse in the earnings conference calls (ECC) reduces firm-level stock price crash risk in the US market. This research also explores if adverse disclosures via media channels further moderates the association between EPR on crash risk. Employing a dataset of 28,933 firm-year observations from 2002 to 2020, the empirical analysis reveals that EPR discourse in ECC reduces future stock price crash risk. However, adverse disclosures via media channels can offset the favourable effect of EPR discourse on crash risk. The results are robust to the potential endogeneity concern in a quasi-natural experiment setting.

Keywords: earnings conference calls, environment, environment-specific political risk discourse, environmental disclosures, information asymmetry, reputation risk, stock price crash risk

Procedia PDF Downloads 134

Authors: Pellecchia M. T., Savarese G., Carpinelli L., Calabrese M.

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Introduction: Parkinson's disease (PD) is characterized by a progressive loss of autonomy which undoubtedly has a significant impact on the quality of life of caregivers, and parents are the main informal caregivers. Caring for a person with PD is associated with an increased risk of psychiatric morbidity and persistent anxiety-depressive distress. The aim of the study is to investigate the burden on caregivers of patients with PD, through the use of multidimensional scales and to identify their personological and environmental determinants. Methods: The study has been approved by the Ethic Committee of the University of Salerno and informed consent for participation to the study was obtained from patients and their caregivers. The study was conducted at the Neurology Department of the A.O.U. "San Giovanni di Dio and Ruggi D’Aragona" of Salerno between September 2020 and May 2021. Materials: The questionnaires used were: a) Caregiver Burden Inventory - CBI a questionnaire of 24 items that allow identifying five sub-categories of burden (objective, psychological, physical, social, emotional); b) Depression Anxiety Stress Scales Short Version - DASS-21 questionnaire consisting of 21 items and valid in examining three distinct but interrelated areas (depression, anxiety and stress); c) Family Strain Questionnaire Short Form - FSQ-SF is a questionnaire of 30 items grouped in areas of increasing psychological risk (OK, R, SR, U); d) Zarit Caregiver Burden Inventory - ZBI, consisting of 22 items based on the analysis of two main factors: personal stress and pressure related to his role; e) Life Satisfaction, a single item that aims to evaluate the degree of life satisfaction in a global way using a 0-100 Likert scale. Findings: N ° 29 caregivers (M age = 55.14, SD = 9.859; 69% F) participated in the study. 20.6% of the sample had severe and severe burden (CBI score = M = 26.31; SD = 22.43) and 13.8% of participants had moderate to severe burden (ZBI). The FSQ-SF highlighted a minority of caregivers who need psychological support, in some cases urgent (Area SR and Area U). The DASS-21 results show a prevalence of stress-related symptoms (M = 10.90, SD = 10.712) compared to anxiety (M = 7.52, SD = 10.752) and depression (M = 8, SD = 10.876). There are significant correlations between some specific variables and mean test scores: retired caregivers report higher ZBI scores (p = 0.423) and lower Life Satisfaction levels (p = -0.460) than working caregivers; years of schooling show a negative linear correlation with the ZBI score (p = -0.491). The T-Test indicates that caregivers of patients with cognitive impairment are at greater risk than those of patients without cognitive impairment. Conclusions: It knows the factors that affect the burden the most would allow for early recognition of risky situations and caregivers who would need adequate support.

Keywords: anxious-depressive axis, caregivers’ burden, Parkinson’ disease, psychological risks

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Authors: Fereshteh Darash

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Reflective tax management corresponds to the Agency Theory since it determines the motivation of managers for tax management actions and short-term and long-term consequences. Therefore, selection of tax strategy contributes to the tax and financial position of the firm in the future. The aim of the present research is to evaluate the effect of tax management components on risk-taking of firms listed in Tehran stock exchange by using regression analysis method. Results show that tax effective rate, tax risk and tax planning have no significant effect on the firm's future risk. Results suggest that stakeholders assess the effective tax rate and delay in tax payment in line with their benefits. They tend to accept the higher risk cost for reduction of tax payments and benefits of higher liquidity in current period. Hence, effective tax rate and tax risk have no significant effect on future risk of the firm. Moreover, tax planning yields no information regarding the predictability of the future profits and as a result, it has no significant effect on the future risk of the firm since specific goals of financial reporting are in priority for the stakeholders and regardless of the firm’s data analysis, they take investment decisions and they less intend to purchase the stocks in a rational manner.

Keywords: tax management, tax effective rate, tax risk, tax planning, firm risk

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Authors: Gregory Michael McMahon

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Risk management for the purposes of minimizing the damages from the operations of dams has met with opposition emerging from organisations and authorities, and their practitioners. It appears that the cause may be a misunderstanding of risk management arising from exchanges that mix deterministic thinking with risk-centric thinking and that do not separate uncertainty from reliability and accuracy from probability. This paper sets out those misunderstandings that arose from dam operations at Wivenhoe in 2011, using a comparison of outcomes that have been based on the methodology and its rules and those that have been operated by applying misunderstandings of the rules. The paper addresses the performance of one risk-centric Flood Manual for Wivenhoe Dam in achieving a risk management outcome. A mixture of engineering, administrative, and legal factors appear to have combined to reduce the outcomes from the risk approach. These are described. The findings are that a risk-centric Manual may need to assist administrations in the conduct of scenario training regimes, in responding to healthy audit reporting, and in the development of decision-support systems. The principal assistance needed from the Manual, however, is to assist engineering and the law to a good understanding of how risks are managed – do not assume that risk management is understood. The wider findings are that the critical profession for decision-making downstream of the meteorologist is not dam engineering or hydrology, or hydraulics; it is risk management. Risk management will provide the minimum flood damage outcome where actual rainfalls match or exceed forecasts of rainfalls, that therefore risk management will provide the best approach for the likely history of flooding in the life of a dam, and provisions made for worst cases may be state of the art in risk management. The principal conclusion is the need for training in both risk management as a discipline and also in the application of risk management rules to particular dam operational scenarios.

Keywords: risk management, flood control, dam operations, deterministic thinking

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Authors: Anders Thorsén, Behrooz Sangchoolie, Peter Folkesson, Ted Strandberg

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As more parts of the power grid become connected to the internet, the risk of cyberattacks increases. To identify the cybersecurity threats and subsequently reduce vulnerabilities, the common practice is to carry out a cybersecurity risk assessment. For safety classified systems and products, there is also a need for safety risk assessments in addition to the cybersecurity risk assessment in order to identify and reduce safety risks. These two risk assessments are usually done separately, but since cybersecurity and functional safety are often related, a more comprehensive method covering both aspects is needed. Some work addressing this has been done for specific domains like the automotive domain, but more general methods suitable for, e.g., intelligent distributed grids, are still missing. One such method from the automotive domain is the Security-Aware Hazard Analysis and Risk Assessment (SAHARA) method that combines safety and cybersecurity risk assessments. This paper presents an approach where the SAHARA method has been modified in order to be more suitable for larger distributed systems. The adapted SAHARA method has a more general risk assessment approach than the original SAHARA. The proposed method has been successfully applied on two use cases of an intelligent distributed grid.

Keywords: intelligent distribution grids, threat analysis, risk assessment, safety, cybersecurity

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

Abstract:

The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

Procedia PDF Downloads 362

Authors: Joe Collins, Matthias Rother

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Background: Oral non-steroidal anti-inflammatory drugs (NSAIDs) are widely used for the relief of joint pain during and post-exercise. However, oral NSAIDs increase the risk of systemic side effects, even in healthy individuals, and retard recovery from muscle soreness. TDT 064 (Flexiseq®), a topical formulation containing ultra-deformable drug-free Sequessome™ vesicles, has demonstrated equivalent efficacy to oral celecoxib in reducing osteoarthritis-associated joint pain and stiffness. TDT 064 does not cause NSAID-related adverse effects. We describe clinical study data and a case report on the effectiveness of TDT 064 in reducing joint pain after exercise. Methods: Participants with a pain score ≥3 (10-point scale) 12–16 hours post-exercise were randomized to receive TDT 064 plus oral placebo, TDT 064 plus oral ketoprofen, or ketoprofen in ultra-deformable phospholipid vesicles plus oral placebo. Results: In the 168 study participants, pain scores were significantly higher with oral ketoprofen plus TDT 064 than with TDT 064 plus placebo in the 7 days post-exercise (P = 0.0240) and recovery from muscle soreness was significantly longer (P = 0.0262). There was a low incidence of adverse events. These data are supported by clinical experience. A 24-year-old male professional rugby player suffered a traumatic lisfranc fracture in March 2014 and underwent operative reconstruction. He had no relevant medical history and was not receiving concomitant medications. He had undergone anterior cruciate ligament reconstruction in 2008. The patient reported restricted training due to pain (score 7/10), stiffness (score 9/10) and poor function, as well as pain when changing direction and running on consecutive days. In July 2014 he started using TDT 064 twice daily at the recommended dose. In November 2014 he noted reduced pain on running (score 2-3/10), decreased morning stiffness (score 4/10) and improved joint mobility and was able to return to competitive rugby without restrictions. No side effects of TDT 064 were reported. Conclusions: TDT 064 shows efficacy against exercise- and injury-induced joint pain, as well as that associated with osteoarthritis. It does not retard muscle soreness recovery after exercise compared with an oral NSAID, making it an alternative approach for the treatment of joint pain during and post-exercise.

Keywords: exercise, joint pain, TDT 064, phospholipid vesicles

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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Authors: Chih-Hsiang Chang, Fang-Jyun Su

Abstract:

This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.

Keywords: stock characteristics, herding formation, investment decision, US equity market, lead-lag relationship

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Authors: Enqing Chen, Jianbo Wang

Abstract:

It is well known that the wavelet transform provides a very effective framework for multiscale edges analysis. However, wavelets are not very effective in representing images containing distributed discontinuities such as edges. In this paper, we propose a novel multiscale edge detection method in nonsubsampled contourlet transform (NSCT) domain, which is based on the dominant multiscale, multidirection edge expression and outstanding edge location of NSCT. Through real images experiments, simulation results demonstrate that the proposed method is better than other edge detection methods based on Canny operator, wavelet and contourlet. Additionally, the proposed method also works well for noisy images.

Keywords: edge detection, NSCT, shift invariant, modulus maxima

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

Abstract:

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Nina V. Zaitseva, Pavel Z. Shur, Nina G. Atiskova

Abstract:

Nowadays harmonization of sanitary and hygienic standards of environmental quality with international standards is crucial part of integration of Russia into the international community. Harmonization of Russian and international ambient air quality standards may be realized by risk-based standards development. In this paper approaches to risk-based standards development and examples of these approaches implementation are presented.

Keywords: harmonization, health risk assessment, evolutionary modelling, benchmark level, nickel, manganese

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Authors: F. Christie, M. Staber

Abstract:

Malnutrition is a predictor of poor clinical outcome in the elderly. Up to 60% of hip fracture patients are clinically malnourished on admission. This study assessed the perioperative nutritional state of patients admitted with a proximal femoral fracture and examined if adequate nutritional support was achieved. Methods: Prospective, the observational audit of 30 patients, admitted with a proximal femoral fracture, over a one-month period. We recorded: patient demographics; surgical delay; nutritional state on admission; documentation of Malnutrition Universal Screening Tool (MUST) score; dietician input and daily calorie intake through food charts. The nutritional state was re-assessed weekly and at discharge. The outcome was measured by the length of hospital stay and thirty-day mortality. Results: Mean age 87, M:F 1:2 and all patients were ASA three or four. Five patients (17%) had a prolonged ( >24 hours) fasting period. All patients had a MUST score completed on admission, 27% were underweight and 30% were high risk for malnutrition. Twenty-six patients (87%) were appropriately assessed for dietician referral. Thirteen patients had food charts; on average, hospital meals provided 1500kcal daily. No patient achieved > 75% of the provided calories with 69% of patients achieving 50% or less. Only three patients were started on nutritional supplements. Twenty-three patients (77%) lost weight, averaging 6% weight loss during admission. Mean length of stay (LOS) was 23 days and 30-day mortality 9%. Four patients (13%) gained weight, their mean LOS was 17 days and 30-day mortality 0%. Discussion: Malnutrition in the elderly originates in the community. Following major trauma it’s difficult to reverse nutritional deficits in hospitals. It’s therefore concerning that no high-risk patient achieved their recommended calorie intake. Perioperative optimisation needs to include early nutritional intervention, early anaesthetic review and adjusted anaesthetic techniques to support feeding.

Keywords: trauma, nutrition, neck of femur fracture

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

Abstract:

Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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