دانلود و نمایش مقالات مرتبط با Disorders::صفحه 1
دانلود بهترین مقالات isi همراه با ترجمه فارسی 2

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - Disorders

تعداد مقالات یافته شده: 145
ردیف عنوان نوع
1 Plant leaf disease detection using computer vision and machine learning algorithms
تشخیص بیماری برگ گیاه با استفاده از بینایی کامپیوتری و الگوریتم های یادگیری ماشین-2022
Agriculture provides food to all the human beings even in case of rapid increase in the population. It is recom- mended to predict the plant diseases at their early stage in the field of agriculture is essential to cater the food to the overall population. But it unfortunate to predict the diseases at the early stage of the crops. The idea behind the paper is to bring awareness amongst the farmers about the cutting-edge technologies to reduces diseases in plant leaf. Since tomato is merely available vegetable, the approaches of machine learning and image processing with an accurate algorithm is identified to detect the leaf diseases in the tomato plant. In this investigation, the samples of tomato leaves having disorders are considered. With these disorder samples of tomato leaves, the farm- ers will easily find the diseases based on the early symptoms. Firstly, the samples of tomato leaves are resized to 256 × 256 pixels and then Histogram Equalization is used to improve the quality of tomato samples. The K-means clustering is introduced for partitioning of dataspace into Voronoi cells. The boundary of leaf samples is extracted using contour tracing. The multiple descriptors viz., Discrete Wavelet Transform, Principal Component Analysis and Grey Level Co-occurrence Matrix are used to extract the informative features of the leaf samples. Finally, the extracted features are classified using machine learning approaches such as Support Vector Machine (SVM), Convolutional Neural Network (CNN) and K-Nearest Neighbor (K-NN). The accuracy of the proposed model is tested using SVM (88%), K-NN (97%) and CNN (99.6%) on tomato disordered samples.
keywords: شبکه های عصبی کانولوشنال | تبدیل موجک گسسته | تجزیه و تحلیل مؤلفه های اصلی | نزدیکترین همسایه | بیماری برگ | Convolutional Neural Networks | Discrete Wavelet Transform | Principal Component Analysis | Nearest Neighbor | Leaf disease
مقاله انگلیسی
2 Design and architecture of smart belt for real time posture monitoring
طراحی و معماری کمربند هوشمند برای نظارت بر وضعیت بدن در زمان واقعی-2022
The bad back flexions are the main cause of the back disorders and pains. Many working conditions require that the worker remain sitting and slouching for long time. Having a correct sitting posture over time is the greatest way to protect workers from the back pains according to the latest medical researchers. In this paper, we present the architecture and design details of the proposed posture monitoring system. The aim of this study is to propose a tracking posture system include complete information about the back posture. The existing posture monitoring systems in literature were limited to trunk flexion monitoring. In this proposal we introduce the shoulder bent monitoring in addition to the trunk flexion monitoring in order to provide complete information about the back posture. The proposed posture monitoring system is a smart belt equipped by inertial sensors to detect the trunk flexion and a shoulder bent to monitor the posture over time. A smartphone application was developed to notify the person in case of bad posture detection. The proposed system demonstrates encouraging results to monitor the posture over time of seating persons and improves their seating behavior by receiving a real time notification in case of bad posture detection.
keywords: وضعیت نشستن | سنسورهای اینرسی | پشتی | نظارت بر وضعیت بدن | سیستم بلادرنگ | Seatingposture | Inertialsensors | Backpain | Posturemonitoring | Realtimesystem
مقاله انگلیسی
3 ECG based biometric identification using one-dimensional local difference pattern
شناسایی بیومتریک مبتنی بر ECG با استفاده از الگوی تفاوت محلی تک بعدی-2021
In this work, an enhanced version of 1D local binary pattern is proposed, for the derivation of the most relevant features for ECG-based human recognition. Generally, ECG signal characteristics by nature impose some notable challenges, mostly related to its sensitivity to noises, artifacts, behavioral and emotional disorders and other variability factors. To deal with this critical issue, we use a One-dimensional Local Difference Pattern (1D-LDP) operator to extract the discriminating statistical features from ECG by using the difference between consecutive neighboring samples to capture both the micro and macro patterns information in the heartbeat activity while reducing the local and global variation occurred in ECG over time. To verify its robustness, K-nearest neighbors (KNN) linear support vector machine (SVM) and neural network were performed as the classifier models in this work. Obtained results show that the 1D-LDP operator clearly outperforms existing 1D-LBP variants on MIT-BIH Normal Sinus Rhythm and ECG-ID database.
Keywords: Electrocardiogram | 1D local binary pattern | Biometric | Classification
مقاله انگلیسی
4 Midwives knowledge of pre-eclampsia management: A scoping review
دانش ماماها از مدیریت پیشکلامپسی: بررسی اسکاپ-2021
Background: Pre-eclampsia is a multi-organ disease affecting pregnant women from the second trimester onwards resulting in multiple adverse outcomes. Sub-optimal treatment of pre-eclampsia is linked with unfavorable outcomes. It is critical for midwives as primary providers to be competent in the diagnosis and management of pre-eclampsia especially in low-and middle-income countries.
Aim: To identify what midwives’ around the world know about pre-eclampsia management. Methods: A scoping review using the JBI three-step search strategy was used to identify relevant research articles and grey literature on the subject. Database searches in PubMed, CINAHL, Cochrane Databases, Web of Science, and Scopus yielded twenty papers in addition to nine guidelines from Google Scholar. The findings were synthesised using a metasynthesis approach and presented as themes.
Findings: Four themes were identified from the extracted data: Foundational knowledge of preeclampsia; Knowledge and management of a woman with pre-eclampsia according to guidelines; Knowledge of being prepared for emergency procedures and management of emergencies; Factors influencing knowledge. The first three themes addressed diagnosis and management whilst the last theme described how contextual factors led to either increased or decreased knowledge of preeclampsia.
Conclusion: Worldwide, practicing midwives lack knowledge on several aspects of pre-eclampsia diagnosis and care. Policies on in-service training should be oriented to include innovative nontraditional methods that have the potential to increase midwives’ knowledge.
keywords: ماماها | دانش | اطلاع | پیش از اکلامپسی | اختلالات فشار خون بالا بارداری | Midwives | Knowledge | Awareness | Pre-eclampsia | Hypertensive disorders pregnancy
مقاله انگلیسی
5 Vision-assisted recognition of stereotype behaviors for early diagnosis of Autism Spectrum Disorders
تشخیص رفتارهای کلیشه ای برای تشخیص زودهنگام اختلالات طیف اوتیسم با کمک بینایی ماشین-2021
Medical diagnosis supported by computer-assisted technologies is getting more popularity and acceptance among medical society. In this paper, we propose a non-intrusive vision-assisted method based on human action recognition to facilitate the diagnosis of Autism Spectrum Disorder (ASD). We collected a novel and comprehensive video dataset f the most distinctive Stereotype actions of this disorder with the assistance of professional clinicians. Several frameworks as a function of different input modalities were developed and used to produce extensive baseline results. Various local descriptors, which are commonly used within the Bag-of-Visual-Words approach, were tested with Multi-layer Perceptron (MLP), Gaussian Naive Bayes (GNB), and Support Vector Machines (SVM) classifiers for recognizing ASD associated behaviors. Additionally, we developed a framework that first receives articulated pose-based skeleton sequences as input and follows an LSTM network to learn the temporal evolution of the poses. Finally, obtained results were compared with two fine-tuned deep neural networks: ConvLSTM and 3DCNN. The results revealed that the Histogram of Optical Flow (HOF) descriptor achieves the best results when used with MLP classifier. The promising baseline results also confirmed that an action-recognition-based system can be potentially used to assist clinicians to provide a reliable, accurate, and timely diagnosis of ASD disorder.© 2021 Elsevier B.V. All rights reserved.
Keywords: Action recognition | Autism Spectrum Disorder | Patient monitoring | Bag-of-visual-words | Convolutional neural networks
مقاله انگلیسی
6 Postharvest environmentally and human-friendly pre-treatments to minimize carrot waste in the supply chain caused by physiological disorders and fungi
پیش تصفیه های دوستانه محیط زیست و انسانی پس از برداشت برای به حداقل رساندن ضایعات هویج در زنجیره تأمین ناشی از اختلالات فیزیولوژیکی و قارچ ها-2021
Background: Carrot is one of the most important horticultural crops, with an annual worldwide production exceeding 40 million tonnes. Carrots are sold either fresh intact or fresh-cut as minimally processed vegetables (MPV). In the postharvest supply chain, physiological disorders, fungal decay, and their combinations reduce the quality of fresh intact and MPV carrots. MPV carrots are more susceptible to quality changes than fresh intact carrots due to a higher loss of protective epidermis, greater number of wounded cells, and increased respiration rates. Scope and approach: The current review summarizes different environmentally and human-friendly treatments applied in the postharvest supply chain to minimize the adverse effects of handling and storage on physiological disorders and fungal decay. Key findings and conclusions: Bitterness, white blush, and browning are the most critical physiological disorders of fresh and MPV carrots. Bitterness can be prevented by storing carrots in well-ventilated rooms without ethylene- producing fruit and vegetables, while white blush and browning can be controlled by the application of heat treatment, ultraviolet (UV)-irradiation, hydrogen sulfide (H2S), and edible films. Sclerotinia sclerotiorum, Botrytis cinerea, Alternaria radicina, and Berkeleyomyces spp. (formerly Thielaviopsis spp.) are important fungi causing carrot postharvest losses and waste. Fungal decay of carrots can be controlled by selecting healthy carrots and applying natural compounds, ozone (O3), heat treatment, UV-irradiation, inorganic salt, and/or biocontrol agents, and their combinations. However, a successful combination of different sustainable treatment methods requires treatment compatibility, and -omics techniques may reveal the best combinations of sustainable treatment methods.
Keywords: Daucus carota | Horticulture | Supply chain | Ozone | UV-Irradiation | Heat treatment
مقاله انگلیسی
7 How does traditional knowledge of Cassiae semen shed light on weight management? – A classical and modern literature review
دانش سنتی منی فلوس چگونه مدیریت وزن را روشن می کند؟ - بررسی ادبیات کلاسیک و مدرن-2021
Ethnopharmacological relevance: The seed of Senna obtusifolia (L.) H. S. Irwin & Barneby (Cassiae semen, CS) also known as Jue ming zi in China, has been traditionally used for weight management by purging the liver and improving the liver functions to support digestion. In the past decades, it has been used for hepatoprotection and treatment of overweight and other metabolic disorders such as hyperlipidaemia and diabetes. Aim of the review: This review aimed at providing comprehensive information on the traditional usages, phar- macology, phytochemistry and toxicology of CS and critically exploring its potential usage for clinical weight management from both traditional and modern application perspectives. Materials and methods: In order to fully understand the properties, actions and indications of CS, two sets of Chinese classical texts were searched, namely: Zhong Hua Yi Dian (Encyclopedia of Traditional Chinese Medi- cine) and Zhong Guo Ben Cao Quan Shu (Complete Collection of Traditional Texts on Chinese Materia Medica). The purpose of studying these classical texts was to determine the traditional use of CS in weight management. Comprehensive searches were also performed on seven databases for publications on original randomised clinical trials (RCT), in vivo, in vitro or in silico studies related to pharmacological effects of CS. Detailed information about the phytochemistry of CS was collected from books, encyclopedia, online databases and journal literature. Findings: In classical literature review, 89 classic texts provided information of properties, actions and indications of CS. In modern literature review, 44 studies were included for analysis, including 5 RCTs, 7 in vivo studies, 14 in vitro studies, 2 in silico studies and 16 studies of mixed types. Chinese classic literature has provided traditional evidence of the usage of CS for weight management. Contemporary studies have revealed that CS has weight loss effects and possesses some other pharmacological activities supporting weight management. Some chemical compounds of CS have been hypothesised to have a direct or indirect contribution to weight control. Conclusions: The relationships between chemical compounds and the corresponding weight-loss target proteins are not fully understood. Therefore, CS constituents should be further explored for the development of novel therapeutic or preventive agents for the treatment of overweight and obesity.
keywords: طب سنتی چینی | چاقی | اضافه وزن | ملین | لیپیدها | Traditional Chinese medicine | Senna obtusifolia | Cassia obtusifolia | Cassiae semen | Obesity | Overweight | Laxative | Lipids
مقاله انگلیسی
8 The link between mental health, crime and violence
پیوند بین سلامت روان ، جرم و خشونت-2020
Research investigating the link between mental health, crime and violence often rely on populations that are at a high-risk of violent and criminal behaviour, such as prison inmates and psychiatric patients. As a result of this selection bias, the relationship between mental health, criminal and violent behaviour is significantly overestimated, with mental health being incorrectly linked with violent and criminal behaviours. This study examines the relationship between mental health, violence and crime in a more representative community-based sample. One hundred and twenty-one individuals with and without a mental health disorder reported their involvement in crime and completed an aggression questionnaire. The results revealed that there is no statistically significant difference in terms of violence and crime involvement between individuals with a mental health diagnosis and those without. Moreover, the study did not find any statistically significant associations between specific mental health disorders and specific crime offences. The findings suggest that certain mental health disorders do not strongly contribute to crime violence and involvement. Limitations and implications are discussed in detail.
Keywords: Mental health | Crime | Violence | Aggression
مقاله انگلیسی
9 Evaluating the implementation of a prisoner re-entry initiative for individuals with opioid use and mental health disorders: Application of the consolidated framework for implementation research in a cross-system initiative
ارزیابی اجرای ابتکار ورود مجدد زندانی برای افراد دارای مصرف مواد افیونی و اختلالات سلامت روانی: استفاده از چارچوب تلفیقی برای تحقیقات پیاده سازی در یک ابتکار عمل متقابل-2020
Given the interrelated nature of opioid use, criminal justice interaction, and mental health issues, the current opioid crisis has created an urgent need for treatment, including medication assisted treatment, among justiceinvolved populations. Implementation research plays an important role in improving systems of care and integration of evidence-based practices within and outside of criminal justice institutions. The current study is a formative qualitative evaluation of the implementation of a cross-system (corrections and community-based) opioid use treatment initiative supported by Opioid State Targeted Response (STR) funding. The purpose of the study is to assess the fit of the Consolidated Framework for Implementation Research (CFIR) to a cross-system initiative, and to identify key barriers and facilitators to implementation. The process evaluation showed that adaptability of the clinical model and staff flexibility were critical to implementation. Cultural and procedural differences across correctional facilities and community-based treatment programs required frequent and structured forums for cross-system communication. Challenges related to recruitment and enrollment, staffing, MAT, and data collection were addressed through the collaborative development and continuous review of policies and procedures. This study found CFIR to be a useful framework for understanding implementation uptake and barriers. The framework was particularly valuable in reinforcing the use of implementation research as a means for continuous process improvement. CFIR is a comprehensive and flexible framework that may be adopted in future cross-system evaluations.
Keywords: Opioids | Medication assisted treatment | Implementation research | Criminal justice | Co-occurring disorders
مقاله انگلیسی
10 Comparing views on civil commitment for drug misuse and for mental illness among persons with opioid use disorder
مقایسه دیدگاه ها در مورد تعهد مدنی برای سو مصرف مواد و بیماری روانی در بین افراد مبتلا به اختلال استفاده از مواد افیونی-2020
Despite the growing use of civil commitment for drug use disorders, little is known about attitudes among individuals who might be subject to civil commitment. This study examined attitudes of persons with opioid use disorder toward civil commitment for drug misuse and for psychiatric illness. Consecutive persons entering a brief, inpatient opioid detoxification (n = 254) were surveyed regarding their attitudes about civil commitment for mental illness and for drug use, and responses were compared by commitment type and by individual history of being civilly committed for opioid misuse. Participants endorsed high support for civil commitment (both psychiatric and drug misuse-related) when used to address risk of harm to self, to others, and of criminal activity. Respondents were more likely to support civil commitment for psychiatric disorders than for drug misuse, expressing higher support for civil commitment in general, higher agreement with the criteria used to justify civil commitment, and greater perceived efficacy of commitment. Individuals previously committed for opioid misuse were less likely to support drug misuserelated commitment on the basis of its perceived efficacy. These results suggest individuals with opioid use disorder hold more favorable views toward civil commitment for mental health disorders than for drug misuse, and reinforce the need for more research on the procedures and outcomes related to civil commitment for drug misuse.
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 1767 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 1767 :::::::: افراد آنلاین: 52