Search results for: electronic intelligence

Authors: Ekeh Greg

Abstract:

Learning has been part of human existence from time immemorial. The aim of every learning is to know the truth. In education, it is desirable that true knowledge is imparted and imbibed. For this to be achieved, there is need for honesty, in this context, academic honesty among students, especially in e-learning. This is an ethical issue since honesty bothers on human conduct. However, research findings have shown that academic honesty has remained a big challenge to online learners, especially among the university students. This is worrisome since the university education is the final education system and a gateway to life in the wider society after schooling. If they are practicing honesty in their academic life, it is likely that they will practice honesty in the in the society, thereby bringing positive contributions to the society wherever they find themselves. With this in mind, the significance of this study becomes obvious. On grounds of this significance, this paper focuses on strategies that are adjudged certain to enhance the practice of honesty in e-learning so as to enable learners to be well equipped to contribute to the society through honest ways. The aim of the paper is to contribute to the efforts of instilling the consciousness and practice of honesty in the minds and hearts of learners. This will, in turn, promote effective teaching and learning, academic high standard, competence and self-confidence in university education. Philosophical methods of conceptual analysis, clarification, description and prescription are adopted for the study. Philosophical perspective is chosen so as to ground the paper on the basis of rationality rather than emotional sentiments and biases emanating from cultural, religious and ethnic differences and orientations. Such sentiments and biases can becloud objective reasoning and sound judgment. A review of related literature is also carried out. The findings show that academic honesty in e-learning is a cherished value, but it is bedeviled by some challenges, such as care-free attitude on the part of students and absence of monitoring. The findings also show that despite the challenges facing academic honesty, strategies such as self-discipline, determination, hard work, imbibing ethical and philosophical principles, among others, can certainly enhance the practice of honesty in e-learning among university students. The paper, therefore, concludes that these constitute strategies for enhancing academic honesty among students. Consequently, it is suggested that instructors, school counsellors and other stakeholders should endeavour to see that students are helped to imbibe these strategies and put them into practice. Students themselves are enjoined to cherish honesty in their academic pursuit and avoid short-cuts. Short-cuts can only lead to mediocrity and incompetence on the part of the learners, which may have long adverse consequences, both on themselves and others.

Keywords: academic, ethical, philosophical, strategies

Procedia PDF Downloads 76

Authors: Scott Andersen

Abstract:

Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

Procedia PDF Downloads 58

Authors: Afshin Kadri

Abstract:

Using Renewable Energy Resources (RES) as a type of DG unit is developing in distribution systems. The connection of these generation units to existing AC distribution systems changes the structure and some of the operational aspects of these grids. Most of the RES requires to power electronic-based interfaces for connection to AC systems. These interfaces consist of at least one DC/AC conversion unit. Nowadays, grid-connected inverters must have the required feature to support the grid under sag voltage conditions. There are two curves in these conditions that show the magnitude of the reactive component of current as a function of voltage drop value and the required minimum time value, which must be connected to the grid. This feature is named low voltage ride-through (LVRT). Implementing this feature causes problems in the operation of the inverter that increases the amplitude of high-frequency components of the injected current and working out of maximum power point in the photovoltaic panel connected inverters are some of them. The important phenomenon in these conditions is ripples in the DC bus voltage that affects the operation of the inverter directly and indirectly. The losses of DC bus capacitors which are electrolytic capacitors, cause increasing their temperature and decreasing its lifespan. In addition, if the inverter is connected to the photovoltaic panels directly and has the duty of maximum power point tracking, these ripples cause oscillations around the operating point and decrease the generating energy. Using a bidirectional converter in the DC bus, which works as a buck and boost converter and transfers the ripples to its DC bus, is the traditional method to eliminate these ripples. In spite of eliminating the ripples in the DC bus, this method cannot solve the problem of reliability because it uses an electrolytic capacitor in its DC bus. In this work, a control method is proposed which uses the bidirectional converter as the fourth leg of the inverter and eliminates the DC bus ripples using an injection of unbalanced currents into the grid. Moreover, the proposed method works based on constant power control. In this way, in addition, to supporting the amplitude of grid voltage, it stabilizes its frequency by injecting active power. Also, the proposed method can eliminate the DC bus ripples in deep voltage drops, which cause increasing the amplitude of the reference current more than the nominal current of the inverter. The amplitude of the injected current for the faulty phases in these conditions is kept at the nominal value and its phase, together with the phase and amplitude of the other phases, are adjusted, which at the end, the ripples in the DC bus are eliminated, however, the generated power decreases.

Keywords: renewable energy resources, voltage drop value, DC bus ripples, bidirectional converter

Procedia PDF Downloads 76

Authors: Kirolos Gerges Yakoub Gerges

Abstract:

Self-sustaining agricultural machines act in stochastic surroundings and therefore, should be capable of perceive the surroundings in real time. This notion can be done using image sensors blended with superior device learning, mainly Deep mastering. Deep convolutional neural networks excel in labeling and perceiving colour pix and since the fee of RGB-cameras is low, the hardware cost of accurate notion relies upon heavily on memory and computation power. This paper investigates the opportunity of designing lightweight convolutional neural networks for semantic segmentation (pixel clever class) with reduced hardware requirements, to allow for embedded usage in self-reliant agricultural machines. The usage of compression techniques, a lightweight convolutional neural community is designed to carry out actual-time semantic segmentation on an embedded platform. The community is skilled on two big datasets, ImageNet and Pascal Context, to apprehend as much as four hundred man or woman instructions. The 400 training are remapped into agricultural superclasses (e.g. human, animal, sky, road, area, shelterbelt and impediment) and the capacity to provide correct actual-time perception of agricultural environment is studied. The network is carried out to the case of self-sufficient grass mowing the usage of the NVIDIA Tegra X1 embedded platform. Feeding case-unique pics to the community consequences in a fully segmented map of the superclasses within the picture. As the network remains being designed and optimized, handiest a qualitative analysis of the technique is entire on the abstract submission deadline. intending this cut-off date, the finalized layout is quantitatively evaluated on 20 annotated grass mowing pictures. Light-weight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show aggressive performance on the subject of accuracy and speed. It’s miles viable to offer value-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigationaxial flux machines, axial flux applications, coreless machines, PM machinesautonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 26

Authors: V. Reyes, P. Ferreira

Abstract:

In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

Procedia PDF Downloads 118

Authors: Victor Au, Khin Maung Than, Zaw Win Aung, Linawati Jumat

Abstract:

Background & Objectives: Cardiac arrests can occur anywhere or anytime, and most of the cases will be brought to the emergency department except the cases that happened in at in-patient setting. Raja IsteriPangiran Anak Saleha (RIPAS) Hospital is the only tertiary government hospital which located in Brunei Muara district and received all referral from other Brunei districts. Data of cardiac arrests in Brunei Darussalam scattered between Emergency Medical Ambulance Services (EMAS), Emergency Department (ED), general inpatient wards, and Intensive Care Unit (ICU). In this audit, we only focused on cardiac arrest cases which had happened or presented to the emergency department RIPAS Hospital. Theobjectives of this audit were to look at demographic of cardiac arrest cases and the survival to discharge rate of In-Hospital Cardiac Arrest (IHCA) and Out-Hospital Cardiac Arrest (OHCA). Methodology: This audit retrospective study was conducted on all cardiac arrest cases that underwent Cardiopulmonary Resuscitation (CPR) in ED RIPAS Hospital, Brunei Muara, in the year 2019-2020. All cardiac arrest cases that happened or were brought in to emergency department were included. All the relevant data were retrieved from ED visit registry book and electronic medical record “Bru-HIMS” with keyword diagnosis of “cardiac arrest”. Data were analyzed and tabulated using Excel software. Result: 313 cardiac arrests were recorded in the emergency department in year 2019-2020. 92% cases were categorized as OHCA, and the remaining 8% as IHCA. Majority of the cases were male with age between 50-60 years old. In OHCA subgroup, only 12.4% received bystander CPR, and 0.4% received Automatic External Defibrillator (AED) before emergency medical personnel arrived. Initial shockable rhythm in IHCA group accounted for 12% compare to 4.9% in OHCA group. Outcome of ED resuscitation, 32% of IHCA group achieved return of spontaneous circulation (ROSC) with a survival to discharge rate was 16%. For OHCA group, 12.35% achieved ROSC, but unfortunately, none of them survive till discharge. Conclusion: Standardized registry for cardiac arrest in the emergency department is required to provide valid baseline data to measure the quality and outcome of cardiac arrest. Zero survival rate for out hospital cardiac arrest is very concerning, and it might represent the significant breach in cardiac arrest chains of survival. Systematic prospective data collection is needed to identify contributing factors and to improve resuscitation outcome.

Keywords: cardiac arrest, OHCA, IHCA, resuscitation, emergency department

Procedia PDF Downloads 99

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 125

Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

Abstract:

While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

Procedia PDF Downloads 108

Authors: Peter Adly Hamdy Fahmy

Abstract:

The aim of the study was to examine the effects of a physical education program on student learning by combining the teaching of personal and social responsibility (TPSR) with a physical education model and TPSR with a traditional teaching model, these learning outcomes involving self-learning. -Study. Athletic performance, enthusiasm for sport, group cohesion, sense of responsibility and game performance. The participants were 3 secondary school physical education teachers and 6 physical education classes, 133 participants with students from the experimental group with 75 students and the control group with 58 students, and each teacher taught the experimental group and the control group for 16 weeks. The research methods used surveys, interviews and focus group meetings. Research instruments included the Personal and Social Responsibility Questionnaire, Sports Enthusiasm Scale, Group Cohesion Scale, Sports Self-Efficacy Scale, and Game Performance Assessment Tool. Multivariate analyzes of covariance and repeated measures ANOVA were used to examine differences in student learning outcomes between combining the TPSR with a physical education model and the TPSR with a traditional teaching model. The research findings are as follows: 1) The TPSR sports education model can improve students' learning outcomes, including sports self-efficacy, game performance, sports enthusiasm, team cohesion, group awareness and responsibility. 2) A traditional teaching model with TPSR could improve student learning outcomes, including sports self-efficacy, responsibility, and game performance. 3) The sports education model with TPSR could improve learning outcomes more than the traditional teaching model with TPSR, including sports self-efficacy, sports enthusiasm, responsibility and game performance. 4) Based on qualitative data on teachers' and students' learning experience, the physical education model with TPSR significantly improves learning motivation, group interaction and sense of play. The results suggest that physical education with TPSR could further improve learning outcomes in the physical education program. On the other hand, the hybrid model curriculum projects TPSR - Physical Education and TPSR - Traditional Education are good curriculum projects for moral character education that can be used in school physics.

Keywords: approach competencies, physical, education, teachers employment, graduate, physical education and sport sciences, SWOT analysis character education, sport season, game performance, sport competence

Procedia PDF Downloads 59

Authors: Maria Antonieta Erna Castillo Holly

Abstract:

During the last decade, data analysis, strategic decision making, and the use of artificial intelligence (AI) tools in Latin American agriculture have been a challenge. In some countries, the availability, quality, and reliability of historical data, in addition to the current data recording methodology in the field, makes it difficult to use information systems, complete data analysis, and their support for making the right strategic decisions. This is something essential in Agriculture 4.0. where the increase in the global demand for fresh agricultural products of tropical origin, during all the seasons of the year requires a change in the production model and greater agility in the responses to the consumer market demands of quality, quantity, traceability, and sustainability –that means extensive data-. Having quality information available and updated in real-time on what, how much, how, when, where, at what cost, and the compliance with production quality standards represents the greatest challenge for sustainable and profitable agriculture in the region. The objective of this work is to present a methodological proposal for the collection of georeferenced data from the protected agriculture sector, specifically in production units (UP) with tall structures (Greenhouses), initially for Venezuela, taking the state of Mérida as the geographical framework, and horticultural products as target crops. The document presents some background information and explains the methodology and tools used in the 3 phases of the work: diagnosis, data collection, and analysis. As a result, an evaluation of the process is carried out, relevant data and dashboards are displayed, and the first satellite maps integrated with layers of information in a geographic information system are presented. Finally, some improvement proposals and tentatively recommended applications are added to the process, understanding that their objective is to provide better qualified and traceable georeferenced data for subsequent analysis of the information and more agile and accurate strategic decision making. One of the main points of this study is the lack of quality data treatment in the Latin America area and especially in the Caribbean basin, being one of the most important points how to manage the lack of complete official data. The methodology has been tested with horticultural products, but it can be extended to other tropical crops.

Keywords: greenhouses, protected agriculture, data analysis, geographic information systems, Venezuela

Procedia PDF Downloads 131

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 130

Authors: Joni Asitashvili, Eka Chabashvili, Maya Virsaladze, Alexander Chokhonelidze

Abstract:

Studying the soundscape is a major challenge in many countries of the civilized world today. The sound environment and music itself are part of the Earth's ecosystem. Therefore, researching its positive or negative impact is important for a clean and healthy environment. The acoustics of nature gave people many musical ideas, and people enriched musical features and performance skills with the ability to imitate the surrounding sound. For example, a population surrounded by mountains invented the technique of antiphonal singing, which mimics the effect of an echo. Canadian composer Raymond Murray Schafer viewed the world as a kind of musical instrument with ever-renewing tuning. He coined the term "Soundscape" as a name of a natural environmental sound, including the sound field of the Earth. It can be said that from which the “music of nature” is constructed. In the 21st century, a new field–Ecomusicology–has emerged in the field of musical art to study the sound ecosystem and various issues related to it. Ecomusicology considers the interconnections between music, culture, and nature–According to the Aaron Allen. Eco-music is a field of ecomusicology concerning with the depiction and realization of practical processes using modern composition techniques. Finding an artificial sound source (instrumental or electronic) for the piece that will blend into the soundscape of Sound Oases. Creating a composition, which sounds in harmony with the vibrations of human, nature, environment, and micro- macrocosm as a whole; Currently, we are exploring the ambient sound of the Georgian urban and suburban environment to discover “Sound Oases" and compose Eco-music works. We called “Sound Oases" an environment with a specific sound of the ecosystem to use in the musical piece as an instrument. The most interesting examples of Eco-music are the round dances, which were already created in the BC era. In round dances people would feel the united energy. This urge to get united revealed itself in our age too, manifesting itself in a variety of social media. The virtual world, however, is not enough for a healthy interaction; we created plan of “contemporary round dance” in sound oasis, found during expedition in Georgian caves, where people interacted with cave's soundscape and eco-music, they feel each other sharing energy and listen to earth sound. This project could be considered a contemporary round dance, a long improvisation, particular type of art therapy, where everyone can participate in an artistic process. We would like to present research result of our eco-music experimental performance.

Keywords: eco-music, environment, sound, oasis

Procedia PDF Downloads 61

Authors: Arjumand Warsy

Abstract:

Among the Muslims, the Holy Quran is taught from early childhood and generally by the age of 7-8 years the reading of the entire Quran is completed by most of the children in Muslim families. During this period excellent reciter’s are selected to teach and emphasis is laid on correct reading, pronunciation and memorization. Following these years, the parents lay emphasis on the recitation of the Quran on daily basis. During the month of Ramadan the entire Quran is read one or more times and there are considerable number of Muslims who complete the entire Quran once or more each calendar month. Many Muslims do not know Arabic and for them message in the Quran is what others tell them and often they have no idea about this Guidance sent to them. This deficiency is reflected in many ways, both among people living in Muslim or non-Muslim countries. Due to the deficiency in knowledge about Islamic teachings, the foundations of Islam are being eroded by a variety of forces. In an attempt to guard against the non-Islamic influences, every Muslim must have a clear understanding of the Islamic teachings and requirements. The best guidance can be provided by the understanding of the Holy Quran. However, we are faced with the problem that often the Quran is taught in a way that fails to develop an interest and understanding of the message from Allah. Looking at the teaching of other subjects both scientific and non-scientific, at school, college or University levels, it is obvious that the advances in teaching methodologies using electronic technology have had a major impact, where both the understanding and the interest of the students are significantly elevated. We attempted to teach the meaning of the Holy Quran to children and adults using a scientific and modern approach using slide presentation and animations. The results showed almost 100% increase in the understanding of the Quran message; all attendees claimed they developed an increased interest in the study of the Holy Quran and did not lose track or develop boredom throughout the lectures. They learnt the information and remembered it more effectively. The love for Allah and Prophet Mohammad (PBUH) increased significantly. The fear of Allah and love of Heaven developed significantly. Historical facts and the stories of the past nations became clearer and the Greatness of the Creator was strongly felt. Several of attendees wanted to become better Muslims and to spread the knowledge of Islam. In this presentation, the adopted teaching method will be first presented and demonstrated to the audience using a short Surah from the Quran, followed by discussion on the results achieved during our study. We will endeavor to convey to the audience that there is a need to adopt a more scientific approach to teach the Quran so that a greater benefit is achieved by all.

Keywords: The Holy Quran, Muslims, presentations, technology

Procedia PDF Downloads 427

Authors: Handan Alan, Ulkü Baykal

Abstract:

Personal characteristics help people understand and recognize both themselves and other people. They are also known to have direct effects on managerial behaviors. Managers’ personalities indicate how they think, perceive reality and relate to others, and affect their decision-making and problem-solving methods. This descriptive study aims to determine the personal characteristics of nurse managers and the personal and professional factors that affect them since sufficient data does not exist on personal characteristics despite the focus on the leadership and managerial characteristics in nursing. The study population consisted of nurses working in administrative positions at hospitals affiliated with the public hospitals union, research and practice hospitals affiliated with universities and private hospitals in cities in the Marmara Region. The study sample consisted of nurse managers working in the hospitals that permitted conducting the study (excluding private branch hospitals). The data were collected after obtaining the approval of the Clinical Research Ethics Committee of Çanakkale Onsekiz Mart University (Approval date: 1.7.2015, Decision No: 2015-01) and written official permissions from the administrations of the hospitals included in the study. The data analysis was carried out using means and standard deviations (SD) as descriptive statistics, one-way analysis of variance for inter-group comparisons and the independent samples t-test for paired group comparisons. A significance threshold of p < 0.05 was used to evaluate the findings. The data were collected using the Five Factor Personality Inventory. The study included 900 nurse managers, who obtained the highest mean score on the conscientiousness dimension (X=4.22 ±0.35). This dimension was followed by their mean scores on the agreeableness (X=4.06±0.40), intelligence (X=4.05±0.37), extroversion (X=3.50±0.43), and emotional instability (X=2.07±0.53) dimensions. Statistically significant differences were found between the independent variables of age, gender, marital status, education level, work institution, professional experience, institutional experience, managerial experience, administrative position, work unit and managerial education when compared using the five factor personality inventory (p < 0.05). In conclusion, the nurse managers described themselves having high conscientiousness. Statistically significant differences were found between the five factor personality inventory mean scores and their personal and professional characteristics.

Keywords: nurse manager, personality, personal characteristics, professional characteristics

Procedia PDF Downloads 256

Authors: Nizamuddin Zainuddin, Adam Mohd Saifudin, Ahmad Yusni Bahaudin, Mohd Hanizan Zalazilah, Roslan Jamaluddin

Abstract:

Students’ enhanced experience through simulation is a crucial factor that brings reality to the classroom. The enhanced experience is all about developing, enriching and applications of a generic process flow in the field of logistics and transportations. As educational technology has improved, the effective use of simulations has greatly increased to the point where simulations should be considered a valuable, mainstream pedagogical tool. Additionally, in this era of ongoing (some say never-ending) assessment, simulations offer a rich resource for objective measurement and comparisons. Simulation is not just another in the long line of passing fads (or short-term opportunities) in educational technology. It is rather a real key to helping our students understand the world. It is a way for students to acquire experience about how things and systems in the world behave and react, without actually touching them. In short, it is about interactive pretending. Simulation is all about representing the real world which includes grasping the complex issues and solving intricate problems. Therefore, it is crucial before stimulate the real process of inbound and outbound logistics and transportation a generic process flow shall be developed. The paper will be focusing on the validization of the process flow by looking at the inputs gains from the sample. The sampling of the study focuses on multi-national and local manufacturing companies, third party companies (3PL) and government agency, which are selected in Peninsular Malaysia. A simulation flow chart was proposed in the study that will be the generic flow in logistics and transportation. A qualitative approach was mainly conducted to gather data in the study. It was found out from the study that the systems used in the process of outbound and inbound are System Application Products (SAP) and Material Requirement Planning (MRP). Furthermore there were some companies using Enterprises Resources Planning (ERP) and Electronic Data Interchange (EDI) as part of the Suppliers Own Inventories (SOI) networking as a result of globalized business between one countries to another. Computerized documentations and transactions were all mandatory requirement by the Royal Custom and Excise Department. The generic process flow will be the basis of developing a simulation program that shall be used in the classroom with the objective of further enhanced the students’ learning experience. Thus it will contributes to the body of knowledge on the enrichment of the student’s employability and also shall be one of the way to train new workers in the logistics and transportation filed.

Keywords: enhancement, simulation, process flow, logistics, transportation

Procedia PDF Downloads 329

Authors: Ana Claudia de Souza Costa, Beatriz de Cássia Pinheiro Goulart, Karine de Cássia Cavalari, Henrique Ceretta Oliveira, Edineis de Brito Guirardello

Abstract:

Background: During the COVID-19 pandemic, nursing represents the largest category of health professionals who were on the front line. Thus, investigating the practice environment and the job satisfaction of nursing professionals during the pandemic becomes fundamental since it reflects on the quality of care and the safety climate. The aim of this study was to evaluate and compare the nursing professionals' perception of the work environment, job satisfaction, and safety climate of the different hospitals and work shifts during the COVID-19 pandemic. Method: This is a cross-sectional survey with 130 nursing professionals from public, private and mixed hospitals in Brazil. For data collection, was used an electronic form containing the personal and occupational variables, work environment, job satisfaction, and safety climate. The data were analyzed using descriptive statistics and ANOVA or Kruskal-Wallis tests according to the data distribution. The distribution was evaluated by means of the Shapiro-Wilk test. The analysis was done in the SPSS 23 software, and it was considered a significance level of 5%. Results: The mean age of the participants was 35 years (±9.8), with a mean time of 6.4 years (±6.7) of working experience in the institution. Overall, the nursing professionals evaluated the work environment as favorable; they were dissatisfied with their job in terms of pay, promotion, benefits, contingent rewards, operating procedures and satisfied with coworkers, nature of work, supervision, and communication, and had a negative perception of the safety climate. When comparing the hospitals, it was found that they did not differ in their perception of the work environment and safety climate. However, they differed with regard to job satisfaction, demonstrating that nursing professionals from public hospitals were more dissatisfied with their work with regard to promotion when compared to professionals from private (p=0.02) and mixed hospitals (p< 0.01) and nursing professionals from mixed hospitals were more satisfied than those from private hospitals (p= 0.04) with regard to supervision. Participants working in night shifts had the worst perception of the work environment related to nurse participation in hospital affairs (p= 0.02), nursing foundations for quality care (p= 0.01), nurse manager ability, leadership and support (p= 0.02), safety climate (p< 0.01), job satisfaction related to contingent rewards (p= 0.04), nature of work (p= 0.03) and supervision (p< 0.01). Conclusion: The nursing professionals had a favorable perception of the environment and safety climate but differed among hospitals regarding job satisfaction for the promotion and supervision domains. There was also a difference between the participants regarding the work shifts, being the night shifts, those with the lowest scores, except for satisfaction with operational conditions.

Keywords: health facility environment, job satisfaction, patient safety, nursing

Procedia PDF Downloads 157

Authors: Lindsay Foreman

Abstract:

Introduction: Goals have become synonymous with the quest for the good life and the pursuit of happiness, with coaching and positive psychology gaining popularity as an approach in recent decades. And yet mental health is on the rise and the leading cause of disability, wellbeing is on the decline, stress is leading to 50-60% of workday absences and the need for action is indisputable and urgent. Purpose: The purpose of this study is to better understand two things we cannot see, but that play the most significant role in these outcomes - what we think and how we feel. With many working on the assumption that positive thinking and an optimistic outlook are necessary or valuable components of goal pursuit, this study uncovers the reality of the ‘inner-game’ from the coachee's perspective. Method: With a mixed methods design using a Q Method study of subjectivity to ‘make the unseen seen’. First, a wide-ranging universe of subjective thoughts and feelings experienced during goal pursuit are explored. These are generated from literature and a Qualtrics survey to create a Q-Set of 40 statements. Then 19 participants in professional and organisational settings offer their perspectives on these 40 Q-Set statements. Each rank them in a semi-forced distribution from ‘most like me’ to ‘least like me’ using Q-Sort software. From these individual perspectives, clusters of perspectives are identified using factor analysis and four distinct viewpoints have emerged. Findings: These Goal Pursuit Viewpoints offer insight into the states and self-talk experienced by coachees and may not reflect the assumption of positive thinking associated with achieving goals. The four Viewpoints are 1) the Optimistic View, 2) the Realistic View 3) The Dreamer View and 4) The Conflicted View. With only a quarter of the Dreamer View, and a third of the Optimistic view going on to achieve their goals, these assumptions need review. And with all the Realistic Views going on to achieve their goals, the role of self-doubt, overwhelm and anxiousness in goal achievement cannot be overlooked. Contribution: This study offers greater insight and understanding of people's inner experiences as they pursue goals and highlights the necessary and normal negative states associated with goal achievement. It also offers a practical tool of the Q-set statements to help coaches and coachees explore the current state and help navigate the journey towards goal achievement. It calls into question whether goals should always be part of coaching and if values, identity, and purpose may play a greater role than goals.

Keywords: coaching, goals, positive psychology, mindset, leadership, mental health, beliefs, cognition, emotional intelligence

Procedia PDF Downloads 113

Authors: Jillian M. Hagel, Joseph E. Tucker, Peter J. Facchini

Abstract:

With the aim of establishing a holistic approach for the treatment of central nervous system (CNS) disorders, we are pursuing a drug development program rapidly progressing through discovery and characterization phases. The drug candidates identified in this program are referred to as neuroplastogens owing to their ability to mediate neuroplasticity, which can be beneficial to patients suffering from anxiety, depression, or posttraumatic stress disorder. These and other related neuropsychiatric conditions are associated with the onset of neuronal atrophy, which is defined as a reduction in the number and/or productivity of neurons. The stimulation of neuroplasticity results in an increase in the connectivity between neurons and promotes the restoration of healthy brain function. We have synthesized a substantial catalogue of proprietary indolethylamine derivatives based on the general structures of serotonin (5-hydroxytryptamine) and psychedelic molecules such as N,N-dimethyltryptamine (DMT) and psilocin (4-hydroxy-DMT) that function as neuroplastogens. A primary objective in our screening protocol is the identification of derivatives associated with a significant reduction in hallucination, which will allow administration of the drug at a dose that induces neuroplasticity and triggers other efficacious outcomes in the treatment of targeted CNS disorders but which does not cause a psychedelic response in the patient. Both neuroplasticity and hallucination are associated with engagement of the 5HT2A receptor, requiring drug candidates differentially coupled to these two outcomes at a molecular level. We use novel and proprietary artificial intelligence algorithms to predict the mode of binding to the 5HT2A receptor, which has been shown to correlate with the hallucinogenic response. Hallucination is tested using the mouse head-twitch response model, whereas mouse marble-burying and sucrose preference assays are used to evaluate anxiolytic and anti-depressive potential. Neuroplasticity is assays using dendritic outgrowth assays and cell-based ELISA analysis. Pharmacokinetics and additional receptor-binding analyses also contribute the selection of lead candidates. A summary of the program is presented.

Keywords: neuroplastogen, non-hallucinogenic, drug development, anxiety, depression, PTSD, indolethylamine derivatives, psychedelic-inspired, 5-HT2A receptor, computational chemistry, head-twitch response behavioural model, neurite outgrowth assay

Procedia PDF Downloads 138

Authors: Suhayla Reda Al-Banai

Abstract:

Problem Statement: Tooth whitening was used for over one hundred and fifty year. The question concerning the whiteness of teeth is a complex one since tooth whiteness will vary from individual to individual, dependent on age and culture, etc. Tooth whitening following treatment may be dependent on the type of whitening system used to whiten the teeth. There are a few side-effects to the process, and these include tooth sensitivity and gingival irritation. Some individuals may experience no pain or sensitivity following the procedure. Purpose: To systematically review the available published literature until 31st December 2021 to identify all relevant studies for inclusion and to determine whether there was any evidence demonstrating that the application of whitening procedures resulted in the tooth sensitivity. Aim: Systematically review the available published works of literature to identify all relevant studies for inclusion and to determine any evidence demonstrating that application of 10% & 15% carbamide peroxide in tooth whitening procedures resulted in tooth sensitivity. Material and Methods: Following a review of 70 relevant papers from searching both electronic databases (OVID MEDLINE and PUBMED) and hand searching of relevant written journals, 49 studies were identified, 42 papers were subsequently excluded, and 7 studies were finally accepted for inclusion. The extraction of data for inclusion was conducted by two reviewers. The main outcome measures were the methodology and assessment used by investigators to evaluate tooth sensitivity in tooth whitening studies. Results: The reported evaluation of tooth sensitivity during tooth whitening procedures was based on the subjective response of subjects rather than a recognized methodology for evaluating. One of the problems in evaluating was the lack of homogeneity in study design. Seven studies were included. The studies included essential features namely: randomized group, placebo controls, doubleblind and single-blind. Drop-out was obtained from two of included studies. Three of the included studies reported sensitivity at the baseline visit. Two of the included studies mentioned the exclusion criteria Conclusions: The results were inconclusive due to: Limited number of included studies, the study methodology, and evaluation of DS reported. Tooth whitening procedures adversely affect both hard and soft tissues in the oral cavity. Sideeffects are mild and transient in nature. Whitening solutions with greater than 10% carbamide peroxide causes more tooth sensitivity. Studies using nightguard vital bleaching with 10% carbamide peroxide reported two side effects tooth sensitivity and gingival irritation, although tooth sensitivity was more prevalent than gingival irritation

Keywords: dentine, sensitivity, bleaching, carbamide peroxde

Procedia PDF Downloads 70

Authors: Chana Pavneet

Abstract:

Background: In more recent years in dentistry, a greater emphasis has been placed on competency-based education (CBE) programmes. Undergraduate and postgraduate curriculums have been reformed to reflect these changes, and adopting a CBE approach has shown to be beneficial to trainees and places an emphasis on continuous lifelong learning. The literature is vast; however, very little work has been done specifically to the assessment of competence in dentistry and even less so in oral surgery. The majority of the literature tends to opinion pieces. Some small-scale studies have been undertaken in this area researching assessment tools which can be used to assess competence in oral surgery. However, there is a lack of general consensus on the preferable assessment methods. The aim of this review is to identify the assessment methods available and their usefulness. Methods: Electronic databases (Medline, Embase, and the Cochrane Database of systematic reviews) were searched. PRISMA guidelines were followed to identify relevant papers. Abstracts of studies were reviewed, and if they met the inclusion criteria, they were included in the review. Papers were reviewed against the critical appraisal skills programme (CASP) checklist and medical education research quality instrument (MERQSI) to assess their quality and identify any bias in a systematic manner. The validity and reliability of each assessment method or tool were assessed. Results: A number of assessment methods were identified, including self-assessment, peer assessment, and direct observation of skills by someone senior. Senior assessment tended to be the preferred method, followed by self-assessment and, finally, peer assessment. The level of training was shown to affect the preferred assessment method, with one study finding peer assessment more useful in postgraduate trainees as opposed to undergraduate trainees. Numerous tools for assessment were identified, including a checklist scale and a global rating scale. Both had their strengths and weaknesses, but the evidence was more favourable for global rating scales in terms of reliability, applicability to more clinical situations, and easier to use for examiners. Studies also looked into trainees’ opinions on assessment tools. Logbooks were not found to be significant in measuring the competence of trainees. Conclusion: There is limited literature exploring the methods and tools which assess the competence of oral surgery trainees. Current evidence shows that the most favourable assessment method and tool may differ depending on the stage of training. More research is required in this area to streamline assessment methods and tools.

Keywords: competence, oral surgery, assessment, trainees, education

Procedia PDF Downloads 134

Authors: Yufeng Wu, Yifan Gu, Bin Li, Wei Wang

Abstract:

Resource recycling process contains a subsystem with interactions of three dimensions including coupling allocation of primary and secondary resources, responsibility coordination of stakeholders in forward and reverse supply chains, and trans-boundary transfer of hidden resource and environmental responsibilities between regions. Overlap or lack of responsibilities is easy to appear at the intersection of the three management dimensions. It is urgent to make an overall design of the policy system for recycling resources. From theoretical perspective, this paper analyzes the unique external differences of resource and environment in various dimensions and explores the reason why the effects of trans-dimensional policies are strongly correlated. Taking the example of the copper resources contained in the waste electrical and electronic equipment, this paper constructs reduction effect accounting model of resources recycling and set four trans-dimensional policy scenarios including resources tax and environmental tax reform of the raw and secondary resources, application of extended producer responsibility system, promotion of clean development mechanism, and strict entry barriers of imported wastes. In these ways, the paper simulates the impact effect of resources recycling process on resource deduction and emission reduction of waste water and gas, and constructs trans-dimensional policy mix scenario through integrating dominant strategy. The results show that combined application of various dimensional policies can achieve incentive compatibility and the trans-dimensional policy mix scenario can reach a better effect. Compared with baseline scenario, this scenario will increase 91.06% copper resources reduction effect and improve emission reduction of waste water and gas by eight times from 2010 to 2030. This paper further analyzes the development orientation of policies in various dimension. In resource dimension, the combined application of compulsory, market and authentication methods should be promoted to improve the use ratio of secondary resources. In supply chain dimension, resource value, residual functional value and potential information value contained in waste products should be fully excavated to construct a circular business system. In regional dimension, it should give full play to the comparative advantages of manufacturing power to improve China’s voice in resource recycling in the world.

Keywords: resource recycling, trans-dimension, policy design, incentive compatibility, life cycle

Procedia PDF Downloads 126

Authors: Amir Shariffar, Haider Salman, Tanveer Siddique, Omar Manasreh

Abstract:

According to the recent studies on metal-oxide memristors, researchers tend to improve the stability, endurance, and uniformity of resistive switching (RS) behavior in memristors. Specifically, the main challenge is to prevent abrupt ruptures in the memristor’s filament during the RS process. To address this problem, we are proposing a low-cost hybrid structure of metal oxide quantum dots (QDs) and thin films to control the formation of filaments in memristors. We aim to use metal oxide quantum dots because of their unique electronic properties and quantum confinement, which may improve the resistive switching behavior. QDs have discrete energy spectra due to electron confinement in three-dimensional space. Because of Coulomb repulsion between electrons, only a few free electrons are contained in a quantum dot. This fact might guide the growth direction for the conducting filaments in the metal oxide memristor. As a result, it is expected that QDs can improve the endurance and uniformity of RS behavior in memristors. Moreover, we use a hybrid structure of intrinsic n-type quantum dots and p-type thin films to introduce a potential barrier at the junction that can smooth the transition between high and low resistance states. A bottom-up approach is used for fabricating the proposed memristor using different types of metal-oxide QDs and thin films. We synthesize QDs including, zinc oxide, molybdenum trioxide, and nickel oxide combined with spin-coated thin films of titanium dioxide, copper oxide, and hafnium dioxide. We employ fluorine-doped tin oxide (FTO) coated glass as the substrate for deposition and bottom electrode. Then, the active layer composed of one type of quantum dots, and the opposite type of thin films is spin-coated onto the FTO. Lastly, circular gold electrodes are deposited with a shadow mask by using electron-beam (e-beam) evaporation at room temperature. The fabricated devices are characterized using a probe station with a semiconductor parameter analyzer. The current-voltage (I-V) characterization is analyzed for each device to determine the conduction mechanism. We evaluate the memristor’s performance in terms of stability, endurance, and retention time to identify the optimal memristive structure. Finally, we assess the proposed hypothesis before we proceed to the optimization process for fabricating the memristor.

Keywords: memristor, quantum dot, resistive switching, thin film

Procedia PDF Downloads 122

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 144

Authors: Ana Carolina Kogawa, Selma Gutierrez Antonio, Hérida Regina Nunes Salgado

Abstract:

Rifaximin is an oral antimicrobial, gut - selective and not systemic with adverse effects compared to placebo. It is used for the treatment of hepatic encephalopathy, travelers diarrhea, irritable bowel syndrome, Clostridium difficile, ulcerative colitis and acute diarrhea. The crystalline form present in the rifaximin with minimal systemic absorption is α, being the amorphous form significantly different. Regulators are increasingly attention to polymorphisms. Polymorphs can change the form by altering the drug characteristics compromising the effectiveness and safety of the finished product. International Conference on Harmonization issued the ICH Guidance Q6A, which aim to improve the control of polymorphism in new and existing pharmaceuticals. The objective of this study was to obtain polymorphic forms of rifaximin employing recrystallization processes and characterize them by thermal analysis (thermogravimetry - TG and differential scanning calorimetry - DSC), X-ray diffraction, scanning electron microscopy and solubility test. Six polymorphic forms of rifaximin, designated I to VI were obtained by the crystallization process by evaporation of the solvent. The profiles of the TG curves obtained from polymorphic forms of rifaximin are similar to rifaximin and each other, however, the DTG are different, indicating different thermal behaviors. Melting temperature values of all the polymorphic forms were greater to that shown by the rifaximin, indicating the higher thermal stability of the obtained forms. The comparison of the diffractograms of the polymorphic forms of rifaximin with rifaximin α, β and γ constant in patent indicate that forms III, V and VI are formed by mixing polymorph β and α and form III is formed by polymorph β. The polymorphic form I is formed by polymorph β, but with a significant amount of amorphous material. Already, the polymorphic form II consists of polymorph γ, amorphous. In scanning electron microscope is possible to observe the heterogeneity of morphological characteristics of crystals of polymorphic forms among themselves and with rifaximin. The solubility of forms I and II was greater than the solubility of rifaximin, already, forms III, IV and V presented lower solubility than of rifaximin. Similarly, the bioavailability of the amorphous form of rifaximin is considered significantly higher than the form α, the polymorphic forms obtained in this work can not guarantee the excellent tolerability of the reference medicine. Therefore, studies like these are extremely important and they point to the need for greater requirements by the regulatory agencies competent about polymorphs analysis of the raw materials used in the manufacture of medicines marketed globally. These analyzes are not required in the majority of official compendia. Partnerships between industries, research centers and universities would be a viable way to consolidate researches in this area and contribute to improving the quality of solid drugs.

Keywords: electronic microscopy, polymorphism, rifaximin, solubility, X-ray diffraction

Procedia PDF Downloads 663

Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 150

Authors: Sidra Suleman, Maliha Suleman, Stephen Brindley

Abstract:

Oral rehabilitation of head and neck cancer patients plays a crucial role in the quality of life for such individuals post-treatment. Placement of dental implants or implant-retained prostheses can help restore oral function and aesthetics, which is often compromised following surgery. Conventional prosthodontic techniques can be insufficient in rehabilitating such patients due to their altered anatomy and reduced oral competence. Hence, there is a strong clinical need for the placement of dental implants. With an increasing incidence of head and neck cancer patients, the demand for such treatment is rising. Aim: The aim of the study was to determine the survival rate of dental implants in head and neck cancer patients placed at the Restorative and Maxillofacial Department, Royal Stoke University Hospital (RSUH), United Kingdom. Methodology: All patients who received dental implants between January 1, 2013 to December 31, 2020 were identified. Patients were excluded based on three criteria: 1) non-head and neck cancer patients, 2) no outpatient follow-up post-implant placement 3) provision of non-dental implants. Scanned paper notes and electronic records were extracted and analyzed. Implant survival was defined as fixtures that had remained in-situ / not required removal. Sample: Overall, 61 individuals were recruited from the 143 patients identified. The mean age was 64.9 years, with a range of 35 – 89 years. The sample included 37 (60.7%) males and 24 (39.3%) females. In total, 211 implants were placed, of which 40 (19.0%) were in the maxilla, 152 (72.0%) in the mandible and 19 (9.0%) in autogenous bone graft sites. Histologically 57 (93.4%) patients had squamous cell carcinoma, with 43 (70.5%) patients having either stage IVA or IVB disease. As part of treatment, 42 (68.9%) patients received radiotherapy, which was carried out post-operatively for 29 (69.0%) cases. Whereas 21 (34.4%) patients underwent chemotherapy, 13 (61.9%) of which were post-operative. The Median follow-up period was 21.9 months with a range from 0.9 – 91.4 months. During the study, 23 (37.7%) patients died and their data was censored beyond the date of death. Results: In total, four patients who had received radiotherapy had one implant failure each. Two mandibular implants failed secondary to osteoradionecrosis, and two maxillary implants did not survive as a result of failure to osseointegrate. The overall implant survival rates were 99.1% at three years and 98.1% at both 5 and 7 years. Conclusions: Although this data shows that implant failure rates are low, it highlights the difficulty in predicting which patients will be affected. Future studies involving larger cohorts are warranted to further analyze factors affecting outcomes.

Keywords: oncology, dental implants, survival, restorative

Procedia PDF Downloads 233

Authors: J. Yan, B. Pieper, B. Bucsky, H. H. Sievers, B. Nasseri, S. A. Mohamed

Abstract:

In order to optimize the efficacy of medications, the regular follow-up with long-term continuous monitoring of heart rhythmic patterns has been facilitated since clinical introduction of cardiac implantable electronic monitoring devices (CIMD). Extensive analysis of rhythmic circadian properties is capable to disclose the distributions of arrhythmic events, which may support appropriate medication according rate-/rhythm-control strategy and minimize consequent afflictions. 348 patients (69 ± 0.5ys, male 61.8%) with predisposed atrial fibrillation (AF), undergoing primary ablating therapies combined to coronary or valve operations and secondary implantation of CIMDs, were involved and divided into 3 groups such as PAAF (paroxysmal AF) (n=99, male 68.7%), PEAF (persistent AF) (n=94, male 62.8%), and LSPEAF (long-standing persistent AF) (n=155, male 56.8%). All patients participated in three-year ambulant follow-up (3, 6, 9, 12, 18, 24, 30 and 36 months). Burdens of atrial fibrillation recurrence were assessed using cardiac monitor devices, whereby attacks frequencies and their circadian patterns were systemically analyzed. Anticoagulants and regular anti-arrhythmic medications were evaluated and the last were listed in terms of anti-rate and anti-rhythm regimens. Patients in the PEAF-group showed the least AF-burden after surgical ablating procedures compared to both of the other subtypes (p < 0.05). The AF-recurrences predominantly performed such attacks’ property as shorter than one hour, namely within 10 minutes (p < 0.05), regardless of AF-subtypes. Concerning circadian distribution of the recurrence attacks, frequent AF-attacks were mostly recorded in the morning in the PAAF-group (p < 0.05), while the patients with predisposed PEAF complained less attack-induced discomforts in the latter half of the night and the ones with LSPEAF only if they were not physically active after primary surgical ablations. Different AF-subtypes presented distinct therapeutic efficacies after appropriate surgical ablating procedures and recurrence properties in sense of circadian distribution. An optimization of medical regimen and drug dosages to maintain the therapeutic success needs more attention to detailed assessment of the long-term follow-up. Rate-control strategy plays a much more important role than rhythm-control in the ongoing follow-up examinations.

Keywords: atrial fibrillation, CIMD, MAZE, rate-control, rhythm-control, rhythm patterns

Procedia PDF Downloads 156

Authors: Yu-Fong Lin

Abstract:

The main purpose of this study is to explore the impact of different lighting arrangements that create different visual environments in a 3C retail store on the perception, psychology, and shopping tendencies of consumers of different genders. In recent years, the ‘emotional shopping’ model has been widely accepted in the consumer market; in addition to the emotional meaning and value of a product, the in-store ‘shopping atmosphere’ has also been increasingly regarded as significant. The lighting serves as an important environmental stimulus that influences the atmosphere of a store. Altering the lighting can change the color, the shape, and the atmosphere of a space. A successful retail lighting design can not only attract consumers’ attention and generate their interest in various goods, but it can also affect consumers’ shopping approach, behavior, and desires. 3C electronic products have become mainstream in the current consumer market. Consumers of different genders may demonstrate different behaviors and preferences within a 3C store environment. This study tests the impact of a combination of lighting contrasts and color temperatures in a 3C retail store on the visual perception and psychological reactions of consumers of different genders. The research design employs an experimental method to collect data from subjects and then uses statistical analysis adhering to a 2 x 2 x 2 factorial design to identify the influences of different lighting environments. This study utilizes virtual reality technology as the primary method by which to create four virtual store lighting environments. The four lighting conditions are as follows: high contrast/cool tone, high contrast/warm tone, low contrast/cool tone, and low contrast/warm tone. Differences in the virtual lighting and the environment are used to test subjects’ visual perceptions, emotional reactions, store satisfaction, approach-avoidance intentions, and spatial atmosphere preferences. The findings of our preliminary test indicate that female subjects have a higher pleasure response than male subjects in a 3C retail store. Based on the findings of our preliminary test, the researchers modified the contents of the questionnaires and the virtual 3C retail environment with different lighting conditions in order to conduct the final experiment. The results will provide information about the effects of retail lighting on the environmental psychology and the psychological reactions of consumers of different genders in a 3C retail store lighting environment. These results will enable useful practical guidelines about creating 3C retail store lighting and atmosphere for retailers and interior designers to be established.

Keywords: 3C retail store, environmental stimuli, lighting, virtual reality

Procedia PDF Downloads 390

Authors: Krisztina Bohacs, Klaudia Markus

Abstract:

To author’s best knowledge we are in absence of studies on cognitive program evaluation and we are certainly short of programs that prove to have high effect sizes with strong retention results. The purpose of our study was to investigate the effectiveness of a comprehensive cognitive training program, namely BrainRx. This cognitive rehabilitation program target and remediate seven core cognitive skills and related systems of sub-skills through repeated engagement in game-like mental procedures delivered one-on-one by a clinician, supplemented by digital training. A larger sample of children with learning disability were given pretest and post-test cognitive assessments. The experimental group completed a twenty-week cognitive training program in a BrainRx center. A matched control group received another twenty-week intervention with Feuerstein’s Instrumental Enrichment programs. A second matched control group did not receive training. As for pre- and post-test, we used a general intelligence test to assess IQ and a computer-based test battery for assessing cognition across the lifespan. Multiple regression analyses indicated that the experimental BrainRx treatment group had statistically significant higher outcomes in attention, working memory, processing speed, logic and reasoning, auditory processing, visual processing and long-term memory compared to the non-treatment control group with very large effect sizes. With the exception of logic and reasoning, the BrainRx treatment group realized significantly greater gains in six of the above given seven cognitive measures compared to the Feuerstein control group. Our one-year retention measures showed that all the cognitive training gains were above ninety percent with the greatest retention skills in visual processing, auditory processing, logic, and reasoning. The BrainRx program may be an effective tool to establish long-term cognitive changes in case of students with learning disabilities. Recommendations are made for treatment centers and special education institutions on the cognitive training of students with special needs. The importance of our study is that targeted, systematic, progressively loaded and intensive brain training approach may significantly change learning disabilities.

Keywords: cognitive rehabilitation training, cognitive skills, learning disability, permanent structural cognitive changes

Procedia PDF Downloads 202

Authors: Iryna Biskub

Abstract:

The interdisciplinary approach to modern linguistic studies is exemplified by the merge of various research methods, which sometimes causes complications related to the verification of the research results. This methodological confusion can be resolved by means of creating new techniques of linguistic analysis combining several scientific paradigms. Modern linguistics has developed really productive and efficient methods for the investigation of cognitive and communicative phenomena of which language is the central issue. In the field of discourse studies, one of the best examples of research methods is the method of Critical Discourse Analysis (CDA). CDA can be viewed both as a method of investigation, as well as a critical multidisciplinary perspective. In CDA the position of the scholar is crucial from the point of view exemplifying his or her social and political convictions. The generally accepted approach to obtaining scientifically reliable results is to use a special well-defined scientific method for researching special types of language phenomena: cognitive methods applied to the exploration of cognitive aspects of language, whereas communicative methods are thought to be relevant only for the investigation of communicative nature of language. In the recent decades discourse as a sociocultural phenomenon has been the focus of careful linguistic research. The very concept of discourse represents an integral unity of cognitive and communicative aspects of human verbal activity. Since a human being is never able to discriminate between cognitive and communicative planes of discourse communication, it doesn’t make much sense to apply cognitive and communicative methods of research taken in isolation. It is possible to modify the classical CDA procedure by means of mapping human cognitive procedures onto the strategic communicative planning of discourse communication. The analysis of the electronic petition 'Block Donald J Trump from UK entry. The signatories believe Donald J Trump should be banned from UK entry' (584, 459 signatures) and the parliamentary debates on it has demonstrated the ability to map cognitive and communicative levels in the following way: the strategy of discourse modeling (communicative level) overlaps with the extraction of semantic macrostructures (cognitive level); the strategy of discourse management overlaps with the analysis of local meanings in discourse communication; the strategy of cognitive monitoring of the discourse overlaps with the formation of attitudes and ideologies at the cognitive level. Thus, the experimental data have shown that it is possible to develop a new complex methodology of discourse analysis, where cognition would meet communication, both metaphorically and literally. The same approach may appear to be productive for the creation of computational models of human-computer interaction, where the automatic generation of a particular type of a discourse could be based on the rules of strategic planning involving cognitive models of CDA.

Keywords: cognition, communication, discourse, strategy

Procedia PDF Downloads 253