Search results for: diagnose

Authors: Fernando Doral

Abstract:

Family businesses are a key phenomenon within the business landscape. Nevertheless, it involves two terms (“family” and “business”) which are nowadays rapidly evolving. Consequently, it isn't easy to diagnose if a family business will be a growing or decreasing phenomenon, which is the objective of this study. For that purpose, a sample of 50 Spanish-established companies from various sectors was taken. Different factors were identified for each enterprise, related to the profile of the founders, such as age, the number of sons and daughters, or support received from the family at the moment to start it up. That information was taken as an input for a clustering method to identify groups, which could help define the founders' profiles. That characterization was carried as a base to identify three factors whose evolution should be analyzed: family structures, business landscape and entrepreneurs' motivations. The analysis of the evolution of these three factors seems to indicate a negative tendency of family businesses. Therefore the consequent diagnosis of this study is to consider family businesses as a declining phenomenon.

Keywords: business diagnose, business trends, family business, family business founders

Procedia PDF Downloads 181

Authors: Neerja Meena, Paresh Sukhani

Abstract:

Dandy walker malformation is a generalised disorder of mesenchymal development that affect both the cerebellum and overlying meninges. Classically dandy-walker malformation consists of a triad of- 1:vermian and hemispheric cerebellar hypoplasia 2:cystic dilatation of 4th ventricle 3: enlarged posterior fossa with the upward migration of tentorium(lambdoid- torcular inversion). Clinical presentation: four months old female child with hydrocephalus and neurological symptoms. Generally- early death is common in classic dandy walker malformation. However, if it is relatively mild and uncomplicated by other CNS anomalies, intelligence can be normal and neurologic deficits minimal. Usually, VP shunting is the treatment of choice for this hydrocephalus. Conclusion: MRI is the modality of choice to diagnose posterior fossa malformation. However, it can be ruled out through using during the antenatal check as the prognosis of this malformation is not good; it's better to diagnose it inutero.

Keywords: Dandy Walker, Mri, Earlydaignosis, Treatment

Procedia PDF Downloads 50

Authors: Abdeljalil Metioui

Abstract:

The purpose of this article is to present the results of two-stage qualitative research. The first involved the identification of the alternative conceptions of 80 elementary pre-service teachers from Quebec in Canada about the operation of simple electrical circuits. To do this, they completed a two-choice questionnaire (true or false) with justification. Data analysis identifies many conceptual difficulties. For example, for their majority, whatever the electrical device that composes an electrical circuit, the current source (power supply), and the generated electrical power is constant. The second step was to develop a double multiple-choice questionnaire based on the identified designs. It allows teachers to quickly diagnose their students' conceptions and take them into account in their teaching.

Keywords: development, electrical circuits, two-tier diagnostic test, secondary and high school

Procedia PDF Downloads 86

Authors: Hossain A., Chowdhury S. I.

Abstract:

Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

Procedia PDF Downloads 72

Authors: Falntina Ahmad Alata, Natheer Abu Obeid

Abstract:

This paper is a research report of an experimental study on a proposed typology system to diagnose and evaluate the affordances of varying architectural environments. The study focused on architectural environments which have been developed with a shift in their use of adaptive reuse. The novelty in the newly developed environments was tested in terms of human responsiveness and interaction using a variety of selected cases. The study is a follow-up on previous research by the same authors, in which a typology of 16 categories of environmental affordances was developed and introduced. The current study introduced other new categories, which together with the previous ones establish what could be considered a basic language of affordance typology. The experiment was conducted on ten architectural environments while adopting two processes: 1. Diagnostic process, in which the environments were interpreted in terms of their affordances using the previously developed affordance typology, 2. The evaluation process, in which the diagnosed environments were evaluated using measures of emotional experience and architectural evaluation criteria of beauty, economy and function. The experimental study demonstrated that the typology system was capable of diagnosing different environments in terms of their affordances. It also introduced new categories of human interaction: “multiple affordances,” “conflict affordances,” and “mix affordances.” The different possible combinations and mixtures of categories demonstrated to be capable of producing huge numbers of other newly developed categories. This research is an attempt to draw a roadmap for designers to diagnose and evaluate the affordances within different architectural environments. It is hoped to provide future guidance for developing the best possible adaptive reuse according to the best affordance category within their proposed designs.

Keywords: affordance theory, affordance categories, architectural environments, architectural evaluation criteria, adaptive reuse environment, emotional experience, shift in use environment

Procedia PDF Downloads 160

Authors: Edy Wahyu Susilo

Abstract:

This research discusses a comparative analysis of various anti-corruption responses of three Indonesian City Governments (Jakarta, Surabaya, and Medan) and completes previous findings on the effectiveness of the city anti-corruption program. Some factors (transparency, accountability, leadership, law enforcement, and bureaucratic reform) have been chosen in this study to diagnose the main role in the success and the failure of anti-corruption programs in these cities. These factors diagnose the relationship between factors and their dominancy, which is then utilized to create the city’s strategic anti-corruption programs. Although this study found leadership had a dominant influence both in encouraging and discouraging the performance of city transformation drastically, however, it is not the only factor that determined the performance of the city in the fight against corruption. It needs other factors as an ideal balancing element to achieve an anti-corruption program, namely KPK’s intervention and public engagement. Based on the dominance factors found, this research then develops an appropriate strategy using a policy evaluation approach to create a real practical guide regardless of the existence of good or bad leadership in the city. This research is expected to be a useful reference for stakeholders, especially the government, as a blueprint to prevent corruption by considering several important steps and guidance in efforts to eradicate corruption in the city, especially in Indonesia.

Keywords: intervention, KPK (corruption eradication commission), law enforcements, leadership, policy evaluation

Procedia PDF Downloads 68

Authors: Mariana Sabino, Janes Cleiton de Oliveira, Carlos Luna de Melo

Abstract:

This paper presents a discussion about the importance and influence of the environment in the patient’s recovery process. Some users (employees and patients) were submitted to a questionnaire that helps to diagnoses the major problems of the hospital, specially related to comfort (aesthetic, thermal, acoustic, light, ergonomic), well-being, how does the flow of patients and employees works in the hospital and wayfinding as well. After a short literature review presenting the topic, the hospital will be characterized, showing photos, the projects available and describing the hospital as well (how many rooms, functions of each one, receptions, waiting rooms, between other things.), than the questionnaire will be applied to patients and to the employees. Lastly the results of the answers given will be analyzed in graphics, and it will help to identify which are the major improvements needed immediately. This paper has the intention to propose a methodology to diagnose architecture problems in a cancer hospital in Brasilia, Brazil, besides to open a space to hear the people that use the building to tell about their discomforts and perceptions of the environment, it also will give an opportunity to apply the possible improvements. It is important to tell that it will be considered if the hospital has a healing environment, and it will also be considered the ergonomic issues about comfort and the way the system of this particular hospital works in general.

Keywords: cancer hospital, comfort, diagnose, healing environment

Procedia PDF Downloads 194

Authors: Swati Kishor Zode, Rahul Ambekar

Abstract:

Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized.

Keywords: classification, homomorphic encryption, clinical decision support, privacy

Procedia PDF Downloads 311

Authors: Waziralilah N. Fathiah, A. Aminudin, U. Alyaa Hashim, T. Vikneshvaran D. Shakirah Shukor

Abstract:

This paper presents the experimental analysis conducted on a structure borne noise in a rectangular enclosure prototype made by joining of sheet aluminum metal and plywood. The study is significant as many did not realized the annoyance caused by structural borne-noise. In this study, modal analysis is carried out to seek the structure’s behaviour in order to identify the characteristics of enclosure in frequency domain ranging from 0 Hz to 200 Hz. Here, numbers of modes are identified and the characteristic of mode shape is categorized. Modal experiment is used to diagnose the structural behaviour while microphone is used to diagnose the sound. Spectral testing is performed on the enclosure. It is acoustically excited using shaker and as it vibrates, the vibrational and noise responses sensed by tri-axis accelerometer and microphone sensors are recorded respectively. Experimental works is performed on each node lies on the gridded surface of the enclosure. Both experimental measurement is carried out simultaneously. The modal experimental results of the modal modes are validated by simulation performed using MSC Nastran software. In pursuance of reducing the structure borne-noise, mitigation method is used whereby the stiffener plates are perpendicularly placed on the sheet aluminum metal. By using this method, reduction in structure borne-noise is successfully made at the end of the study.

Keywords: enclosure, modal analysis, sound analysis, structure borne-noise

Procedia PDF Downloads 401

Authors: Jesús David Argueta Moreno, Taria Ruiz, Cesar Ortega

Abstract:

This qualitative investigation represents the first stage of the human capital engineering analysis, along the small and medium textile manufacturing companies, located on the city of Tegucigalpa, Honduras where the symptoms of the local manufacturing industry´s describe a severe gender displacement phenomenon. The evaluation of this phenomena, intends to trigger the Honduran small and medium technology manufactures into a collective performance, analysis through the development of a sectorial diagnose and the creation of a manufacturers guide, personalized. In accordance to the Honduran textile manufacturing needs, in order to strengthen their personnel capacities and thereby smoothen the gender equilibrium on this particular sector. It is worth mentioning, that on the last decade, the female gender has gathered positive statistics upon Central American job market´s, were the local business landscape describes a significant displacement of the Honduran female operators over the male gender workers that has significantly diminished their employment predominance. On the other hand, this study aims to evaluate the main features that impact on the job market local gender supplanting. On the other hand, this document aims to holistically describe the Honduran manufacturing context, as well as the current textile operator qualifications, in order to infer over the most proper human resources enforcement approaches/techniques on the industry.

Keywords: gender predominance, manufacturing, higher education institutions, emerging trends

Procedia PDF Downloads 406

Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

Procedia PDF Downloads 98

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

Procedia PDF Downloads 27

Authors: Manal Suleiman, George Abu-Aqil, Uraib Sharaha, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman, Mahmoud Huleihel

Abstract:

Klebsiella pneumoniae is one of the most aggressive multidrug-resistant bacteria associated with human infections resulting in high mortality and morbidity. Thus, for an effective treatment, it is important to diagnose both the species of infecting bacteria and their susceptibility to antibiotics. Current used methods for diagnosing the bacterial susceptibility to antibiotics are time-consuming (about 24h following the first culture). Thus, there is a clear need for rapid methods to determine the bacterial susceptibility to antibiotics. Infrared spectroscopy is a well-known method that is known as sensitive and simple which is able to detect minor biomolecular changes in biological samples associated with developing abnormalities. The main goal of this study is to evaluate the potential of infrared spectroscopy in tandem with Random Forest and XGBoost machine learning algorithms to diagnose the susceptibility of Klebsiella pneumoniae to antibiotics within approximately 20 minutes following the first culture. In this study, 1190 Klebsiella pneumoniae isolates were obtained from different patients with urinary tract infections. The isolates were measured by the infrared spectrometer, and the spectra were analyzed by machine learning algorithms Random Forest and XGBoost to determine their susceptibility regarding nine specific antibiotics. Our results confirm that it was possible to classify the isolates into sensitive and resistant to specific antibiotics with a success rate range of 80%-85% for the different tested antibiotics. These results prove the promising potential of infrared spectroscopy as a powerful diagnostic method for determining the Klebsiella pneumoniae susceptibility to antibiotics.

Keywords: urinary tract infection (UTI), Klebsiella pneumoniae, bacterial susceptibility, infrared spectroscopy, machine learning

Procedia PDF Downloads 135

Authors: Falntina Ahmad Alata, Natheer Abu Obeid

Abstract:

This paper revolves around the concept of affordance. It aims to discover and develop an architectural typology based on the ecological concept of affordance. In order to achieve this aim, an analytical study is conducted and two sources were taken into account: 1- Gibson's definition of the concept of affordance and 2- The researches that are concerned on the affordance categorisation. As a result, this paper concluded 16 typologies of affordances, including the possibilities of mixing them based on both sources. To clarify these typologies and provide further understanding, a wide range of architectural examples are presented and proposed in the paper. To prove this vocabulary’s capability to diagnose and evaluate the affordance of different environments, an experimental study with two processes have been adapted: 1. Diagnostic process: the interpretation of the environments with regards to its affordance by using the new vocabulary (the developed typologies). 2. Evaluating process: the evaluation of the environments that have been interpreted and classified with regards to their affordances. By using the measures of emotional experience (the positive affect ‘PA’ and the negative affect ‘NA’) and the architectural evaluation criteria (beauty, economy and function). The experimental study proves that the typologies are capable of reading the affordance within different environments. Additionally, it explains how these different typologies reflect different interactions based on the previous processes. The data which are concluded from the evaluation of measures explain how different typologies of affordance that have already reflected different environments had different evaluations. In fact, some of them are recommended while the others are not. In other words, the paper draws a roadmap for designers to diagnose, evaluate and analyse the affordance into different architectural environments. After that, it guides them through adapting the best interaction (affordance category), which they intend to adapt into their proposed designs.

Keywords: Affordance theory, Affordance categories, Architectural environments, Architectural Evaluation Criteria (AEC), emotional experience (PA, NA)

Procedia PDF Downloads 141

Authors: Savita, Anurag Sharma, Harsukhpreet Singh

Abstract:

Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

Procedia PDF Downloads 379

Authors: Milena Gojny-Zbierowska

Abstract:

In the last decades psychological tests have been gaining in popularity as a method used for evaluating personnel, and they bring consulting companies solid profits rising by up to 10% each year. The market is offering a growing range of tools for the assessment of personality. Tests are used in organizations mainly in the recruitment and selection of staff. This paper is an attempt to initially diagnose the state of the use of psychological tests in Polish companies on the basis of empirical research.

Keywords: psychological tests, personality, content analysis, NEO FFI, big five personality model

Procedia PDF Downloads 319

Authors: Małgorzata Smolarek

Abstract:

One of the barriers to the development of small and medium-sized enterprises (SME) are difficulties connected with management of human resources. The first part of article defines the specifics of staff management in small and medium enterprises. The practical part presents results of own studies in the area of diagnosis of the state of the human resources management in small and medium-sized enterprises in Poland. It takes into account its impact on the functioning of SME in a variable environment. This part presents findings of empirical studies, which enabled verification of the hypotheses and formulation of conclusions. The findings presented in this paper were obtained during the implementation of the project entitled 'Tendencies and challenges in strategic managing SME in Silesian Voivodeship.' The aim of the studies was to diagnose the state of strategic management and human resources management taking into account its impact on the functioning of small and medium enterprises operating in Silesian Voivodeship in Poland and to indicate improvement areas of the model under diagnosis. One of the specific objectives of the studies was to diagnose the state of the process of strategic management of human resources and to identify fundamental problems. In this area, the main hypothesis was formulated: The enterprises analysed do not have comprehensive strategies for management of human resources. The survey was conducted by questionnaire. Main Research Results: Human resource management in SMEs is characterized by simplicity of procedures, and the lack of sophisticated tools and its specificity depends on the size of the company. The process of human resources management in SME has to be adjusted to the structure of an organisation, result from its objectives, so that an organisation can fully implement its strategic plans and achieve success and competitive advantage on the market. A guarantee of success is an accurately developed policy of human resources management based on earlier analyses of the existing procedures and possessed human resources.

Keywords: human resources management, human resources policy, personnel strategy, small and medium enterprises

Procedia PDF Downloads 217

Authors: Annika Kjallman Alm, Ove Hellzen, Malin Rising-Holmstrom

Abstract:

Worldwide, the number of people who are living with dementia is increasing because of an aging population, which leads to increased financial and social costs, including reduced quality of life for people with dementia and their care partners. Most people who have dementia reside in the community. Aging in place could be described as having the health and social supports and services you need to live safely and independently in your home or your society for as long as you wish and are able. People with dementia are not different than people without dementia where they want to remain at home, if possible, with a sense of familiarity and engagement in typical everyday activities. So how do persons with dementia or cognitive decline see their possibilities to be socially involved and experience support? The aim of this study was to explore persons with cognitive decline's sense of involvement and support living in the ordinary dwelling. The study was approved by the Ethical Review Authority in Sweden prior to the interviews. Interviews were conducted with 20 persons living at home, either alone or in a relationship. The persons had perceived cognitive decline; some were under investigation or already had a diagnose of early dementia. Thematic analysis was used to identify, analyze, and report patterns within the data. Researchers extracted three main themes through participants’ interviews: a) Importance of social involvement with family and friends. b) Hindrances for social involvement. c) Struggling mentally with a new life situation. Results found that going to activity centers, staying involved, and meeting friends and family enhanced the sense of involvement and support. There were also hindrances to a sense of involvement and support as they struggled with the diagnose and the changes in daily life, such as physical problems, mental problems, or economic issues. The mental struggle of accepting the cognitive decline and the changes in daily life it brought was also an issue for some of the participants. A multidimensional support should be provided by the community to enable persons with cognitive decline to stay involved in family and community in the comfort of their own homes.

Keywords: aging in place, cognitive decline, dementia, sense of involvement

Procedia PDF Downloads 91

Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

Abstract:

Objective: Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. Methods: 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as independent component analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. Results: The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. Conclusion: This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: ICA, RSN, refractory epilepsy, rsfMRI

Procedia PDF Downloads 42

Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

Abstract:

Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

Procedia PDF Downloads 73

Authors: Man-Yun Liu, Emily Chia-Yu Su

Abstract:

Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

Procedia PDF Downloads 296

Authors: D. Densenbal, Ts. Naidansuren, M. Oyunchimeg, Ts. Manaljav, D. Udval, L. Khosbayar, Kh. Solongo, D. Ichinnorov, B. Solongo

Abstract:

Background: The rapid economic growth and to the common use of smoky fuel such as coal in the small traditional houses (Ger) in Mongolia is worsening its air pollution problem. In addition, the smoking rate is considered to be high. Despite these conditions, few prevalence studies of COPD epidemiology and diagnose have been performed in Mongolia. The spirometric test is a widely used diagnose for COPD. Aims: Healthy and over the 40 aged adults were evaluated of Pulmonary function test in Ulaanbaatar. Methods: Healthy, over the 40 aged residences were admitted for this study from II sub-district, in Khan-Uul district of Ulaanbaatar city. In this cross-sectional study. Health information was collected 184 subjects between 01-03 July in 2013; spirometry device was named Hichest–105 Japan that was employed for this study. Studies were using the acceptability standards outlined, and data were compared with personal reference data generated on Asian subjects which were performed abnormally to evaluated by global initiative obstructive lung decreases (GOLD). Data were analyzed using SPSS 20 software. Results: A total of 134 subjects (age 52.9±9.8, man 32.8%) were performed PFT which were interpreted normal 73.9% (sum of man 65.0% and woman 79.4% ), abnormal 26.1% which were typed obstruction 17.2% (23), restriction 6% (8), mixed 3% (4). Airflow obstruction were determined in all man 25% (11), woman 13.3% (12) which were classified mild 43.4% (man 54.5%, woman 33.3%), moderate 52.2% (36.3% vs. 66.7%) and severe 4.3% man 1 GOLD degree. Undetermined a very severe obstruction. Normal PFT subjects were compared a group of gender and age group which man was significantly higher than the women (p<0.05). Age group of PFT decrease was no difference in gender (p>0.05) also no difference in BMI (p>0.05). Normal PFT subjects were compared with predicted values were used to Asian population which was significantly lower than FEV1 (0.15±0.36 l), PEF (1.92±1.31 l) and same deference occurred man (FEV1 0.19±0.42 l, PEF 2.04±1.64), women (0.14±0.33 l vs. 1.86±1.15 l). The decrease of FEV1 was defined in over the 60 age group higher than other age groups. Conclusion: Not only observed an air flow limitation prevalence dominance in all case but also COPD prevalence diagnosed man were higher than women. Normal PFT subjects were compared with predicted values were used to Asian population which was significant air flow limitation started early.

Keywords: PFT, obstruction, FEV1, COPD

Procedia PDF Downloads 186

Authors: Ünal Kızıl, Levent Genç, Sefa Aksu, Ahmet Tapınç

Abstract:

The Figaro AM-1 sensor module which employs TGS 2600 model gas sensor in air quality assessment was used. The system was coupled with a microprocessor that enables sensor module to create warning message via telephone. This low cot sensor system’s performance was compared with a Diagnose II commercial electronic nose system. Both air quality sensor and electronic nose system employ metal oxide chemical gas sensors. In the study experimental setup, data acquisition methods for electronic nose system, and performance of the low cost air quality system were evaluated and explained.

Keywords: air quality, electronic nose, environmental quality, gas sensor

Procedia PDF Downloads 414

Authors: Hanaa M. Abu El Einin, Ahmed T. Sharaf El- Din

Abstract:

Biomphalaria snails play an integral role in the transmission of Schistosoma mansoni, the causative agent for human schistosomiasis. Two species of Biomphalaria were reported from Egypt, Biomphalaria alexandrina and Biomphalaria glabrata, and later on a hybrid of B. alexandrina and B. glabrata was reported in streams at Nile Delta. All were known to be excellent hosts of S. mansoni. Host-parasite relationship can be viewed in terms of snail susceptibility and parasite infectivity. The objective of this study will highlight the progress that has been made in using molecular approaches to describe the correct identification of snail species that participating in transmission of schistosomiasis, rapid diagnose of infection in addition to susceptibility and resistance type. Snails were identified using of molecular methods involving Randomly Amplified Polymorphic DNA (RAPD), Polymerase Chain Reaction, Restriction Fragment Length Polymorphisms (PCR-RFLP) and Species - specific- PCR. Molecular approaches to diagnose parasite in snails from Egypt: Nested PCR assay and small subunit (SSU) rRNA gene. Also RAPD PCR for study susceptible and resistance phenotype. The results showed that RAPD- PCR, PCR-RFLP and species-specific-PCR techniques were confirmed that: no evidence for the presence of B. glabrata in Egypt, All Biomphalaria snails collected identified as B. alexandrina snail i-e B alexandrinia is a common and no evidence for hybridization with B. glabrata. The adopted specific nested PCR assay revealed much higher sensitivity which enables the detection of S. mansoni infected snails down to 3 days post infection. Nested PCR method for detection of infected snails using S. mansoni fructose -1,6- bisphosphate aldolase (SMALDO) primer, these primers are specific only for S. mansoni and not cross reactive with other schistosomes or molluscan aldolases Nested PCR for such gene is sensitive enough to detect one cercariae. Genetic variations between B. alexandrina strains that are susceptible and resistant to Schistosoma infec¬tion using a RAPD-PCR showed that 39.8% of the examined snails collected from the field were resistant, while 60.2% of these snails showed high infection rates. In conclusion the genetics of the intermediate host plays a more important role in the epidemiological control of schistosomiasis.

Keywords: biomphalaria, molecular differentiation, parasite detection, schistosomiasis

Procedia PDF Downloads 174

Authors: Ivanka Valova

Abstract:

This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

Procedia PDF Downloads 39

Authors: Ramandeep Kaur, Gurjit Singh Bhathal

Abstract:

Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.

Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations

Procedia PDF Downloads 363

Authors: Seong Woo Kwak, Jung-Min Yang

Abstract:

A strategy of fault diagnosis and tolerance for asynchronous sequential machines is discussed in this paper. With no synchronizing clock, it is difficult to diagnose an occurrence of permanent or stuck-in faults in the operation of asynchronous machines. In this paper, we present a fault detector comprised of a timer and a set of static functions to determine the occurrence of faults. In order to realize immediate fault tolerance, corrective control theory is applied to designing a dynamic feedback controller. Existence conditions for an appropriate controller and its construction algorithm are presented in terms of reachability of the machine and the feature of fault occurrences.

Keywords: asynchronous sequential machines, corrective control, fault diagnosis and tolerance, fault detector

Procedia PDF Downloads 321

Authors: Chee Fai Tan, L. S. Wahidin, S. N. Khalil

Abstract:

Nowadays, manufacturing cost is one of the important factors that will affect the product cost as well as company profit. There are many methods that have been used to reduce the manufacturing cost in order for a company to stay competitive. One of the factors that effect manufacturing cost is the time. Expert system can be used as a method to reduce the manufacturing time. The purpose of the expert system is to diagnose and solve the problem of design of assembly. The paper describes an architecture framework for design of assembly expert system that focuses on commercial vehicle seat manufacturing industry.

Keywords: design of assembly, expert system, vehicle seat, mechanical engineering

Procedia PDF Downloads 418

Authors: Abdulrahman Algaeed

Abstract:

The Ophthalmic Ultrasound is the easiest method of early diagnosing Retinoblastoma after clinical examination. It can be done with ease without sedation. King Khaled Eye Specialist Hospital is a tertiary care center where Retinoblastoma patients are often seen and treated there. The first modality to rule out the disease is Ophthalmic Ultrasound. Classic Retinoblastoma is easily diagnosed by using the conventional 10MHz Ophthalmic Ultrasound probe in the regular clinic setup. Retinal lesion with multiple, very highly reflective surfaces within lesion typical of Calcium deposits. The use of Standardized A-scan is very useful where internal reflectivity is classified as very highly reflective. Color Doppler is extremely useful as well to show the blood flow within lesion/s. In conclusion: Ophthalmic Ultrasound should be the first tool to be used to diagnose Retinoblastoma after clinical examination. The accuracy of the Exam is very high.

Keywords: doppler, retinoblastoma, reflectivity, ultrasound

Procedia PDF Downloads 79

Authors: Hassan Sharafuddin, Chekra Allani

Abstract:

Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

Procedia PDF Downloads 408