Search results for: pixel-based change detection

Authors: Hebat‑Allah S. Tohamy, Mohamed El‑Sakhawy, Samir Kamel

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Fluorescent carbon quantum dots (CQDs) were prepared by an economical, green, and single-step procedure based on microwave heating of urea with sugarcane bagasse (SCB), cellulose (C), or carboxymethyl cellulose (CMC). The prepared CQDs were characterized using a series of spectroscopic techniques, and they had small size, strong absorption in the UV, and excitation wavelength-dependent fluorescence. The prepared CQDs were used for Pb(II) adsorption from an aqueous solution. The removal efficiency percentages (R %) were 99.16, 96.36, and 98.48 for QCMC, QC, and QSCB. The findings validated the efficiency of CQDs synthesized from CMC, cellulose, and SCB as excellent materials for further utilization in the environmental fields of wastewater pollution detection, adsorption, and chemical sensing applications. The kinetics and isotherms studied found that all CQD isotherms fit well with the Langmuir model than Freundlich and Temkin models. According to R², the pseudo-second-order fits the adsorption of QCMC, while the first-order one fits with QC and QSCB.

Keywords: carbon quantum dots, graphene quantum dots, fluorescence, quantum yield, water treatment, agricultural wastes

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Authors: A. Serap Fırat

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The aim of this study is to display conceptually the relationship and interaction between matter of human resources training and the information age. Fast development from industrial community to an information community has occurred and organizations have been seeking ways to overcome this change. Human resources policy and human capital with enhanced competence will have direct impact on work performance; therefore, this paper deals with the increased importance of human resource management due to the fact that it nurtures human capital. Researching and scanning are used as a method in this study. Both local and foreign literature and expert views are employed -as much as one could be- in the making of the theoretical framework of this study.

Keywords: human resources, information age, education, organization, occupation

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Authors: Moh Rizaldi, Ali Abdurachman, Indra Perwira

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The biggest demonstration after the 1998 reforms that took place in Indonesia for several days at the end of 2019 did not eliminate the intention of the People’s Representative Council (Dewan Perwakilan Rakyat or DPR) and the President to enact the law 19 of 2019 (KPK law). There is a central issue to be highlighted, namely whether the change is intended to strengthen or even weaken the KPK. To achieve this goal, the Analysis focuses on two agency principles namely the independent principle and the control principle as seen from three things namely the legal substance, legal structure, and legal culture. The research method is normative with conceptual, historical and statute approaches. The argument from this writing is that KPK Law has cut most of the KPK's authority as a result the KPK has become symbolic or toothless in combating corruption.

Keywords: control, independent, KPK, law no. 19 of 2019

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Authors: Mohammed Sghir Taleb

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Morocco is characterized by a great richness and diversity in aromatic and medicinal plants and it has an ancestral knowledge in the use of plants for medicinal and cosmetic purposes. In effect, the poverty of riparian, specially, mountain populations have greatly contributed to the development of traditional pharmacopoeia in Morocco. The analysis of the bibliographic data showed that a large number of plants in Morocco are exploited for aromatic and medicinal purposes and several of them are commercialized internationally. However, these potentialities of aromatic and medicinal plants are currently subjected to climate change and strong human pressures: Collecting fruits, agriculture development, harvesting plants, urbanization, overgrazing...

Keywords: aromatic, medicinal, plant, Morocco

Procedia PDF Downloads 287

Authors: Gulshan Mammadova

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This paper presents the results of studying the surface microrelief in 2D and 3D models and analyzing the spectroscopy of a three-junction TlInSe₂ crystal. Analysis of the results obtained showed that with a change in the composition of the TlInSe₂ crystal, sharp changes occur in the microrelief of its surface. An X-ray optical diffraction analysis of the TlInSe₂ crystal was experimentally carried out. Based on ellipsometric data, optical functions were determined - the real and imaginary parts of the dielectric permittivity of crystals, the coefficients of optical absorption and reflection, the dependence of energy losses and electric field power on the effective density, the spectral dependences of the real (σᵣ) and imaginary (σᵢ) parts, optical electrical conductivity were experimentally studied. The fluorescence spectra of the ternary compound TlInSe₂ were isolated and analyzed when excited by light with a wavelength of 532 nm. X-ray studies of TlInSe₂ showed that this phase crystallizes into tetragonal systems. Ellipsometric measurements showed that the real (ε₁) and imaginary (ε₂) parts of the dielectric constant are components of the dielectric constant tensor of the uniaxial joints under consideration and do not depend on the angle. Analysis of the dependence of the real and imaginary parts of the refractive index of the TlInSe₂ crystal on photon energy showed that the nature of the change in the real and imaginary parts of the dielectric constant does not differ significantly. When analyzing the spectral dependences of the real (σr) and imaginary (σi) parts of the optical electrical conductivity, it was noticed that the real part of the optical electrical conductivity increases exponentially in the energy range 0.894-3.505 eV. In the energy range of 0.654-2.91 eV, the imaginary part of the optical electrical conductivity increases linearly, reaches a maximum value, and decreases at an energy of 2.91 eV. At 3.6 eV, an inversion of the imaginary part of the optical electrical conductivity of the TlInSe₂ compound is observed. From the graphs of the effective power density versus electric field energy losses, it is known that the effective power density increases significantly in the energy range of 0.805–3.52 eV. The fluorescence spectrum of the ternary compound TlInSe₂ upon excitation with light with a wavelength of 532 nm has been studied and it has been established that this phase has luminescent properties.

Keywords: optical properties, dielectric permittivity, real and imaginary dielectric permittivity, optical electrical conductivity

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Devinder Singh, Arvind Kumar, Rajneesh Kumar

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The general solution of the equations for a homogeneous isotropic microstretch thermo elastic medium with mass diffusion for two dimensional problems is obtained due to normal and tangential forces. The integral transform technique is used to obtain the components of displacements, microrotation, stress and mass concentration, temperature change and mass concentration. A particular case of interest is deduced from the present investigation.

Keywords: normal force, tangential force, microstretch, thermoelastic, the integral transform technique, deforming force, microstress force, boundary value problem

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Authors: Maryam Panahiazar, Andrew M. Bishara, Yorick Chern, Roohallah Alizadehsani, Dexter Hadleye, Ramin E. Beygui

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Early detection plays a crucial role in enhancing the outcome for a patient with coronary artery disease (CAD). We utilized a big data analytics platform on ~23,000 patients with CAD from a total of 960,129 UCSF patients in 8 years. We traced the patients from their first encounter with a physician to diagnose and treat CAD. Characteristics such as demographic information, comorbidities, vital, lab tests, medications, and procedures are included. There are statistically significant gender-based differences in patients younger than 60 years old from the time of the first physician encounter to coronary artery bypass grafting (CABG) with a p-value=0.03. There are no significant differences between the patients between 60 and 80 years old (p-value=0.8) and older than 80 (p-value=0.4) with a 95% confidence interval. This recognition would affect significant changes in the guideline for referral of the patients for diagnostic tests expeditiously to improve the outcome by avoiding the delay in treatment.

Keywords: electronic medical records, coronary artery disease, data analytics, young women

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Authors: Poonam Goswami

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Background: The diagnosis of a serious illness like cancer can have an impact on a patient’s emotional well-being and may result in psychological symptoms, anxiety, depression, and loss of control. Advance care planning discussions ensure patients’ values and goals of care, including patients’ freedom to choose their place of death, are respected. Unfortunately, these discussions are often delayed and are not initiated early in patients’ cancer trajectory. As a result, patients’ wishes often remains unknown until the last phase of their life. Evidence suggests that many patients inappropriately receive aggressive treatment near the end of life, which does lead to higher resource utilization, decreased quality of life, and increased cost. Additionally, the novel coronavirus disease 2019 (COVID-19) pandemic challenged the health care systems worldwide and raised important ethical issues, especially regarding the potential need for rationing health care in the context of scarce resources and crisis capacity. The importance of goal concordant care is now even substantially important and is heightened in the context of this pandemic. Problem: Although there is growing evidence on the effects of the ACP on the completion of advanced directives, improved patient and family concordance for preferences for medical care, and receipt of care, there is still a lack of standardized ACP conversation strategies for patients with cancer. Methods: The Key concepts of ACP include (1) assessing patient and family readiness, (2) identifying a surrogate decision maker ( medical power of attorney), (3) exploring patient and family understanding of the disease and treatment options,(4) discussing the values and goals of care, and options for end-of-life care, (5) documenting patient preferences in the medical record, and (6) revisiting the discussions at every change in the treatment plan and /or change in clinical status, including at every hospitalization. Conclusion/Implication for practice: Advance Care Planning (ACP) and end-of-life (EOL) discussions are important for patients, families, and health care providers. Adopting the verbal and nonverbal communication strategies can help overcome the barriers to effective communication on these difficult discussions. ACP with goals of care discussions should not be delayed until the patient is hospitalized.

Keywords: advance care planning, end of life, cancer, global, pandemic

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Authors: Renjith George Pallivathukal, Preethy Mary Donald

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Asymptomatic oral lesions are often ignored by the patients and usually will be identified only in advanced stages. Early detection of precancerous lesions is important for better prognosis. It is also important for the oral health care person to be aware of the regional prevalence of oral lesions in order to provide early care for the same. We conducted a retrospective study to assess the prevalence of oral lesions based on the information available from patient records in a teaching dental school. Dental records of patients who attended the department of Oral medicine and diagnosis between September 2014 and September 2016 were retrieved and verified for oral lesions. Results: The ages of the patients ranged from 13 to 38 years with a mean age of 21.8 years. The lesions were classified as white (40.5%), red (23%), ulcerated (10.5%), pigmented (15.2%) and soft tissue enlargements (10.8%). 52% of the patients were unaware of the oral lesions before the dental visit. Overall, the prevalence of lesions in dental patients lower to national estimates, but the prevalence of some lesions showed variations.

Keywords: oral mucosal lesion, pre-cancer, prevalence, soft tissue lesion

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Sakshi Kaul, Sundeep Verma

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The focus of the current paper is to evaluate the therapeutic power of words. This will be done by critically evaluating the impact reading, writing and storytelling have on individuals. When we read, tell or listen to a story we are exercising our imagination. Imagination becomes the source of activation of thoughts and actions. This enables and helps the reader, writer or the listener to express the suppressed emotions or desires. The stories told, untold may bring various human emotions and attributes to forth such as hope, optimism, fear, happiness. Each story narrated evokes different emotions, at times they help us unravel ourselves in the world of the teller thereby bringing solace. Stories heard or told add to individual’s life by creating a community around, giving wings of thoughts that enable individual to be more imaginative and creative thereby fostering positively and happiness. Reading if looked at from the reader’s point of view can broaden the horizon of information and ideas about facts and life laws giving more meaning to life. From ‘once upon a time’ to ‘to happily ever after’, all that stories talk about is life’s learning. The power of words sometimes may be negated, this paper would reiterate the power of words by critically evaluating how words can become powerful and therapeutic in various structures and forms in the society. There is a story behind every situation, action and reaction. Hence it is of prime importance to understand each story, to enable a person to deal with whatever he or she may be going through. For example, if a client is going through some trauma in his or her life, the counsellor needs to know exactly what is the turmoil that is being faced so that the client can be assisted accordingly. Counselling is considered a process of healing through words or as Talk therapy, where merely through words we try to heal the client. In a counselling session, the counsellor focuses on working with the clients to bring a positive change. The counsellor allows the client to express themselves which is referred to as catharsis. The words spoken, written or heard transcend to heal and can be therapeutic. The therapeutic power of words has been seen in various cultural practices and belief systems. The underlining belief that words have the power to heal, save and bring change has existed from ages. Many religious and spiritual practices also acclaim the power of the words. Through this empirical paper, we have tried to bring to light how reading, writing, and storytelling have been used as mediums of healing and have been therapeutic in nature.

Keywords: reading, storytelling, therapeutic, words

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Authors: Jonida Canaj

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A simple method of extraction and determination of fifteen priority polycyclic aromatic hydrocarbons (PAHs) from drinking water using high performance liquid chromatography (HPLC) has been validated with limits of detection (LOD) and limits of quantification (LOQ), method recovery and reproducibility, and other factors. HPLC parameters, such as mobile phase composition and flow standardized for determination of PAHs using fluorescent detector (FLD). PAH was carried out by liquid-liquid extraction using dichloromethane. Linearity of calibration curves was good for all PAH (R², 0.9954-1.0000) in the concentration range 0.1-100 ppb. Analysis of standard spiked water samples resulted in good recoveries between 78.5-150%(0.1ppb) and 93.04-137.47% (10ppb). The estimated LOD and LOQ ranged between 0.0018-0.98 ppb. The method described has been used for determination of the fifteen PAHs contents in drinking water samples.

Keywords: high performance liquid chromatography, HPLC, method validation, polycyclic aromatic hydrocarbons, PAHs, water

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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Authors: Atlal El-Assaad

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Viruses change with time through mutations and result in new variants that may persist or disappear. A Mutation refers to an actual change in the virus genetic sequence, and a variant is a viral genome that may contain one or more mutations. Critical mutations may cause the virus to be more transmissible, with high disease severity, and more vulnerable to diagnostics, therapeutics, and vaccines. Thus, variants carrying such mutations may increase the risk to human health and are considered variants of concern (VOC). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - the contagious in humans, positive-sense single-stranded RNA virus that caused coronavirus disease 2019 (COVID-19) - has been studied thoroughly, and several variants were revealed across the world with their corresponding mutations. SARS-CoV-2 has four structural proteins, known as the S (spike), E (envelope), M (membrane), and N (nucleocapsid) proteins, but prior study and vaccines development focused on genetic mutations in the S protein due to its vital role in allowing the virus to attach and fuse with the membrane of a host cell. Specifically, subunit S1 catalyzes attachment, whereas subunit S2 mediates fusion. In this perspective, we studied all charged amino acid mutations of the SARS-CoV-2 viral spike protein S1 when bound to Antibody CC12.1 in a crystal structure and assessed the effect of different mutations. We generated all missense mutants of SARS-CoV-2 protein amino acids (AAs) within the SARS-CoV-2:CC12.1 complex model. To generate the family of mutants in each complex, we mutated every charged amino acid with all other charged amino acids (Lysine (K), Arginine (R), Glutamic Acid (E), and Aspartic Acid (D)) and studied the new binding of the complex after each mutation. We applied Poisson-Boltzmann electrostatic calculations feeding into free energy calculations to determine the effect of each mutation on binding. After analyzing our data, we identified charged amino acids keys for binding. Furthermore, we validated those findings against published experimental genetic data. Our results are the first to propose in silico potential life-threatening mutations of SARS-CoV-2 beyond the present mutations found in the five common variants found worldwide.

Keywords: SARS-CoV-2, variant, ionic amino acid, protein-protein interactions, missense mutation, AESOP

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Authors: Kaouther Jaouadi, Jihene Bettaieb, Amira Bennour, Ghassen Kharroubi, Sadok Salem, Afif Ben Salah

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In Tunisia, chronic cutaneous leishmaniasis due to Leishmania (L) tropica is an important health problem. Its spreading has not been fully elucidated. Information on sandfly vectors, as well as their associated Leishmania species, is of paramount importance since vector dispersion is one of the major factors responsible for pathogen dissemination. In total, 650 sandflies were captured between June and August 2015 using sticky paper traps in the governorate of Sidi Bouzid, a classical focus of L. major in the Central-West of Tunisia. Polymerase chain reaction-restriction fragment length polymorphism analysis of the internal transcribed spacer 1 and sequencing were used for Leishmania detection and identification. Ninety-seven unfed females were tested for the presence of Leishmania parasite DNA. Six Phlebotomus sergenti were found positive for L. tropica. This finding enhances the understanding of the cycle extension of L. tropica outside its original focus of Tataouine in the South-East of the country.

Keywords: cutaneous leishmaniasis, Leishmania tropica, sandflies, Tunisia

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Authors: Susan K. Steele-Moses, Aimee Badeaux

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Introduction: Nurse anesthesia education places high demands on students, creating stress and anxiety that can impact their success. Framed in Watson’s caring theory, the research question posed for this study was: What is the effect of a mindfulness application on the perceived stress and anxiety of nurse anesthesia students. Methods: A quantitative comparative research design was used to determine the effect of a mindfulness meditation application, Mindshift, on SRNA’s perceived stress and anxiety over time. The stress and anxiety subscales of the Depression Anxiety Stress Scale 21 (DASS-21) were used to measure the effectiveness of the intervention. After the IRB approval was obtained the 2024, 2025, and 2026 SRNA cohorts were invited to participate in the study (N = 56). Thirty-six students agreed to participate, completed the electronic informed consent, and the electronic DASS-21 baseline measure (64.3%). The Mindshift app was downloaded from the app store onto their personal device and the mindfulness meditation exercises were integrated into their daily routine. The stress and anxiety subscale of the DASS-21 was repeated at 1-month, 3-months, and 6-months, with 31 students completing all measures (86.1%). The difference over time was computed using a repeated measures ANCOVA. Results: Instrument reliability and validity was reconfirmed (Stress: α = .890; Anxiety: α = .788; χ2 = 232.898, p < .001). There was no difference in the student’s stress over time (F = 2.62, p = .079, η2 = .086). When the intervention was considered stress decreased at the 3- month (F = 4.497, p = .014, η2 .138) and 6-month (F = 7.998, p < .001, η2 = .222) intervals. Post-hoc analysis revealed no change between baseline and 1-month (p = .245) but improved from 1-month to 3-months (p = .014), 1-month to 6-months (p < .001), and 3-months to 6- months (p = .007). There was no difference in the student’s anxiety over time (F = .326, p = .683, η2 = .011) or at the three-month interval (F = .647 , p = .488, η2 .024), but anxiety decreased at the six-month interval (F = 4.686, p = .004, η2 = .143). Post-hoc analysis revealed no change between baseline and 1-month (p = .261) or 1-month to 3-months (p = .132). However the student’s anxiety significantly improved from 1-month to 6-months ( p < .001), and 3-months to 6-month (p = .014). Discussion: The mindfulness intervention reduced perceived stress and anxiety levels over time. The gradual decline in stress and the delayed improvement in anxiety suggest that continuous interventions are needed to achieve positive results. It is recommended that mindfulness meditation techniques are integrated into the curriculum highlighting the importance of longitudinal interventions.

Keywords: nurse anesthesia, nursing education, innovation in education, stress, anxiety

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means

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Authors: Ibrahim Aly, Waleed Elawamy, Hanan Taher, Amira Matar

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Schistosomiasis is infection with blood flukes of the genus Schistosoma, which are acquired trans-cutaneously by swimming or wading in contaminated freshwater. The present study was proposed to produce ultra-sensitive, field-friendly high-throughput rapid immunochromatography diagnostic device for accurate detection of asymptomatic parasite carriers in schistosomiasis pre-elimination settings.For assessing diagnostic potential of rapid device, 50 blood samples from patients with schistosomiasis mansoni, 29 other proven parasitic diseases and 25 blood samples as negative control were from healthy individuals were used. The sensitivity of Quantitative antigen-capture nano-ELISAwas 82 %, and specificity was 87.1 %, where the sensitivity of Nano Dot- ELISA was 86 % and specificity was 90.7 %. The sensitivity of diagnostic device was 78 % and specificity was 85.2 %, with PPV and NPV of 86.2 % and 83.1 %, respectively.The Point of care device resulted in a good performance for the diagnosis of low-intensity infections, it was able to identify 19 out of 25 (76 %) individuals with ⩽7 eggs, 10 out of 14 individuals (71.4 %) with 11–99 eggs and 100 % of individuals with 100–399 eggs.

Keywords: schistosomiasis, immunochromatography, naon-dot-ELISa, diagnostis device

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Muhammad Saleem Ullah Khan Sumbal, Eric Tsui, Ricky Cheong, Eric See To

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Organizations are posed to a threat of valuable knowledge loss when employees leave either due to retirement, resignation, job change or because of disabilities e.g. death, etc. Due to changing economic conditions, globalization, and aging workforce, organizations are facing challenges regarding retention of valuable knowledge. On the one hand, large number of employees are going to retire in the organizations whereas on the other hand, younger generation does not want to work in a company for a long time and there is an increasing trend of frequent job change among the new generation. Because of these factors, organizations need to make sure that they capture the knowledge of employee before (s)he walks out of the door. The first step in this process is to know what type of knowledge employee possesses and whether this knowledge is important for the organization. Researchers reveal in the literature that despite the serious consequences of knowledge loss in terms of organizational productivity and competitive advantage, there has not been much work done in the area of knowledge loss assessment of departing employees. An important step in the knowledge retention process is to determine the critical ‘at risk’ knowledge. Thus, knowledge loss risk assessment is a process by which organizations can gauge the importance of knowledge of the departing employee. The purpose of this study is to explore this topic of knowledge loss risk assessment by conducting a qualitative study in oil and gas sector. By engaging in dialogues with managers and executives of the organizations through in-depth interviews and adopting a grounded methodology approach, the research will explore; i) Are there any measures adopted by organizations to assess the risk of knowledge loss from departing employees? ii) Which factors are crucial for knowledge loss assessment in the organizations? iii) How can we prioritize the employees for knowledge retention according to their criticality? Grounded theory approach is used when there is not much knowledge available in the area under research and thus new knowledge is generated about the topic through an in-depth exploration of the topic by using methods such as interviews and using a systematic approach to analyze the data. The outcome of the study will generate a model for the risk of knowledge loss through factors such as the likelihood of knowledge loss, the consequence/impact of knowledge loss and quality of the knowledge loss of departing employees. Initial results show that knowledge loss assessment is quite crucial for the organizations and it helps in determining what types of knowledge employees possess e.g. organizations knowledge, subject matter expertise or relationships knowledge. Based on that, it can be assessed which employee is more important for the organizations and how to prioritize the knowledge retention process for departing employees.

Keywords: knowledge loss, risk assessment, departing employees, Hong Kong organizations

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Satyendra Mourya, Jyoti Jaiswal, Gaurav Malik, Brijesh Kumar, Ramesh Chandra

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Present work describes the fabrication and sensing characteristics of the Pd-Pt decorated nanostructured silicon carbide (SiC) thin films on anodized porous silicon (PSi) substrate by RF magnetron sputtering. The gas sensing performance of Pd-Pt/SiC/PSi sensing electrode towards H2 gas under low (10–400 ppm) detection limit and high operating temperature regime (25–600 °C) were studied in detail. The chemiresistive sensor exhibited high selectivity, good sensing response, fast response/recovery time with excellent stability towards H2 at high temperature. The selectivity measurement of the sensing electrode was done towards different oxidizing and reducing gases and proposed sensing mechanism discussed in detail. Therefore, the investigated Pd-Pt/SiC/PSi structure may be a highly sensitive and selective hydrogen gas sensing electrode for deployment in extreme environment applications.

Keywords: RF Sputtering, silicon carbide, porous silicon, hydrogen gas sensor

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Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

Abstract:

This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

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Authors: Pushpinder Syal

Abstract:

Literary writing carries the stamp of the current language of its time. In translating such texts, it becomes a challenge to capture such reflections which may be evident at several levels: the level of dialectal use of language by characters in stories, the alterations in syntax as tools of writers’ individual stylistic choices, the insertion of quasi-proverbial and gnomic utterances, and even the level of the pragmatics of narrative discourse. Discourse strategies may differ between earlier and later texts, reflecting changing relationships between narrators and readers in changed cultural and social contexts. This paper is a consideration of these features by an approach that combines historicity with a description, contextualizing language change within a discourse framework. The process of translating a collection of writings of Punjabi literature spanning 100 years was undertaken for this study and it was observed that the factor of the historicity of language was seen to play a role. While intended for contemporary readers, the translation of literature over the span of a century poses the dual challenge of needing to possess both accessibility and immediacy as well as adherence to the 'old world' styles of communicating and narrating. The linguistic changes may be observed in a more obvious sense in the difference of diction and word formation – with evidence of more hybridized and borrowed forms in modern and contemporary writings, as compared to the older writings. The latter not only contain vestiges of proverbs and folk sayings, but are also closer to oral speech styles. These will be presented and analysed in the form of chronological listing and by these means, the social process of translation from orality to written text can be seen as traceable in the above-mentioned works. More subtle and underlying shifts can be seen through the analysis of speech acts and implicatures in the same literature, in which the social relationships underlying language use are evident as discourse systems of belief and understanding. They present distinct shifts in worldview as seen at different points in time. However, some continuities of language and style are also clearly visible, and these aid the translator in putting together a set of thematic links which identify the literature of a region and community, and constitute essential outcomes in the effort to preserve its distinctive nature.

Keywords: cultural change, dialect, historicity, stylistic variation

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Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar

Abstract:

Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.

Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes

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Authors: N. Dunleavy, E. Lovemore, K. Siljeur, D. Jackson, M. Hendricks, M. Hoosain, N. Plastow, S. Marais

Abstract:

Background: The work requirements of sewing machine operators cause physical and emotional strain. Past ergonomic interventions have been provided to alleviate physical concerns; however, a holistic, multimodal intervention was needed to improve these factors. Aim: The study aimed to examine the effect of an occupational therapy programme on sewing machine operators’ pain, mental health, and productivity within a factory in the South African context. Methods: A pilot randomised control trial was conducted with 22 sewing machine operators within a single factory. Stratified randomisation was used to determine the experimental (EG) and control groups (CG), using measures for pain intensity, level of depression (mental health), and productivity rates as stratification variables. The EG received the multimodal intervention, incorporating education, seating adaptations, and mental health intervention. In three months, the CG will receive the same intervention. Pre- and post-intervention testing have occurred with upcoming three- and six-month follow-ups. Results: Immediate results indicate a statistically significant decrease in pain in both experimental and control groups; no change in productivity scores and depression between the two groups. This may be attributed to external factors. The values for depression further showed no statistical significance between the two groups and within pre-and post-test results. The Statistical Program for Social Sciences (SPSS) version-24 was used as the data analysis testing, where all the tests will be evaluated at a 5% significance level. Contribution of research: The research adds to the body of knowledge informing the Occupational Therapy role in work settings, providing evidence on the effectiveness of workplace-based multimodal interventions. Conclusion: The study provides initial data on the effectiveness of a pilot randomised control trial on pain and mental health in South Africa. Results indicated no quantitative change between the experimental and control groups; however, qualitative data suggest a clinical significance of the findings.

Keywords: ergonomics programme, occupational therapy, sewing machine operators, workplace-based multimodal interventions

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

Abstract:

Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

Procedia PDF Downloads 97