Search results for: psychology for language learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10191

Search results for: psychology for language learning

2451 Sleep Apnea Hypopnea Syndrom Diagnosis Using Advanced ANN Techniques

Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

Abstract:

Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

Procedia PDF Downloads 117
2450 Promoting Compassionate Communication in a Multidisciplinary Fellowship: Results from a Pilot Evaluation

Authors: Evonne Kaplan-Liss, Val Lantz-Gefroh

Abstract:

Arts and humanities are often incorporated into medical education to help deepen understanding of the human condition and the ability to communicate from a place of compassion. However, a gap remains in our knowledge of compassionate communication training for postgraduate medical professionals (as opposed to students and residents); how training opportunities include and impact the artists themselves, and how train-the-trainer models can support learners to become teachers. In this report, the authors present results from a pilot evaluation of the UC San Diego Health: Sanford Compassionate Communication Fellowship, a 60-hour experiential program that uses theater, narrative reflection, poetry, literature, and journalism techniques to train a multidisciplinary cohort of medical professionals and artists in compassionate communication. In the culminating project, fellows design and implement their own projects as teachers of compassionate communication in their respective workplaces. Qualitative methods, including field notes and 30-minute Zoom interviews with each fellow, were used to evaluate the impact of the fellowship. The cohort included both artists (n=2) and physicians representing a range of specialties (n=7), such as occupational medicine, palliative care, and pediatrics. The authors coded the data using thematic analysis for evidence of how the multidisciplinary nature of the fellowship impacted the fellows’ experiences. The findings show that the multidisciplinary cohort contributed to a greater appreciation of compassionate communication in general. Fellows expressed that the ability to witness how those in different fields approached compassionate communication enhanced their learning and helped them see how compassion can be expressed in various contexts, which was both “exhilarating” and “humbling.” One physician expressed that the fellowship has been “really helpful to broaden my perspective on the value of good communication.” Fellows shared how what they learned in the fellowship translated to increased compassionate communication, not only in their professional roles but in their personal lives as well. A second finding was the development of a supportive community. Because each fellow brought their own experiences and expertise, there was a sense of genuine ability to contribute as well as a desire to learn from others. A “brave space” was created by the fellowship facilitators and the inclusion of arts-based activities: a space that invited vulnerability and welcomed fellows to make their own meaning without prescribing any one answer or right way to approach compassionate communication. This brave space contributed to a strong connection among the fellows and reports of increased well-being, as well as multiple collaborations post-fellowship to carry forward compassionate communication training at their places of work. Results show initial evidence of the value of a multidisciplinary fellowship for promoting compassionate communication for both artists and physicians. The next steps include maintaining the supportive fellowship community and collaborations with a post-fellowship affiliate faculty program; scaling up the fellowship with non-physicians (e.g., nurses and physician assistants); and collecting data from family members, colleagues, and patients to understand how the fellowship may be creating a ripple effect outside of the fellowship through fellows’ compassionate communication.

Keywords: compassionate communication, communication in healthcare, multidisciplinary learning, arts in medicine

Procedia PDF Downloads 67
2449 Philippine English: An Exploratory Mixed-Methods Inquiry on Digital Immigrants and Digital Natives' Variety

Authors: Lesley Karen Penera

Abstract:

Despite the countless that has been drawn to investigate Philippine English for a myriad of reasons, none was known to have ventured on a probe of its grammatical features as used in a technology-driven linguistic landscape by two generations in the digital age. Propelled by the assumption of an emerging Philippine English variety, this paper determined the grammatical features that characterize the digital native-immigrants’ Philippine English. It also ascertained whether mistake or deviation instigated the use of the features, and established this variety’s level of comprehensibility. This exploratory mixed-methods inquiry employed some qualitative and quantitative data drawn from a social networking site, the digital native-immigrant group, and the comprehensibility-raters who were selected through non-random purposive sampling. The study yields 8 grammatical features, mostly deemed results of deviation, yet the texts characterized by such features were mostly rated with excellent comprehensibility. This substantiates some of the grammatical features identified in earlier studies, provides evidentiary proof that the digital groups’ Philippine English is not bound by the standard of syntactic accuracy and corroborates the assertion on language’s manipulability as an instrument fashioned to satisfy the users’ need for successful communication in actual instances for use of English past the walls of any university where the variety is cultivated. The same could also be rationalized by some respondents’ position on grammar and accuracy to be less vital than one’s facility to communicate effectively.

Keywords: comprehensibility, deviation, digital immigrants, digital natives, mistake, Philippine English variety

Procedia PDF Downloads 159
2448 Neuron Efficiency in Fluid Dynamics and Prediction of Groundwater Reservoirs'' Properties Using Pattern Recognition

Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p1), fractured layer (p2), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable gr (gravitational resistance) can be deduced from the elevation and apparent resistivity pa. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 211
2447 A Survey of Mental and Personality Profiles of Malingerer Clients of an Iranian Forensic Medicine Center Based on the Revised NEO Personality Inventory and the Minnesota Multiphasic Personality Inventory Questionnaires

Authors: Morteza Rahbar Taramsari, Arya Mahdavi Baramchi, Mercedeh Enshaei, Ghazaleh Keshavarzi Baramchi

Abstract:

Introduction: Malingering is one of the most challenging issues in the forensic psychology and imposes a heavy financial burden on health care and legal systems. It seems that some mental and personality abnormalities might have a crucial role in developing this condition. Materials and Methods: In this cross-sectional study, we aimed to assess 100 malingering clients of Gilan province general office of forensic medicine, all filled the related questionnaires. The data about some psychometric characteristics were collected through the 71-items version- short form- of Minnesota Multiphasic Personality Inventory (MMPI) questionnaire and the personality traits were assessed by NEO Personality Inventory-Revised (NEO PI-R) - including 240 items- as a reliable and accurate measure of the five domains of personality. Results: The 100 malingering clients (55 males and 45 females) ranged from 23 to 45 (32+/- 5.6) years old. Regarding marital status, 36% were single, 57% were married and 7% were divorced. Almost two-thirds of the participants (64%) were unemployed, 21% were self-employed and the rest of them were employed. The data of MMPI clinical scales revealed that the mean (SD) T score of Hypochondrias (Hs) was 67(9.2), Depression (D) was 87(7.9), Hysteria (Hy) was 74(5.8), Psychopathic Deviate (Pd) was 62(8.5), Masculinity-Feminity (MF) was 76(8.4), Paranoia (Pa) was 62(4.5), Psychasthenia (Pt) was 80(7.9), Schizophrenia (Sc) was 69(6.8), Hypomania (Ma) was 64(5.9)and Social Introversion (Si) was 58(4.3). NEO PI-R test showed five domains of personality. The mean (SD) T score of Neuroticism was 65(9.2), Extraversion was 51(7.9), Openness was 43(5.8), Agreeableness was 35(3.4) and Conscientiousness was 42(4.9). Conclusion: According to MMPI test in our malingering clients, Hypochondriasis (Hs), depression (D), Hysteria (Hy), Muscularity-Feminity (MF), Psychasthenia (Pt) and Schizophrenia (Sc) had high scores (T >= 65) which means pathological range and psychological significance. Based on NEO PI-R test Neuroticism was in high range, on the other hand, Openness, Agreeableness, and Conscientiousness were in low range. Extroversion was in average range. So it seems that malingerers require basic evaluations of different psychological fields. Additional research in this area is needed to provide stronger evidence of the possible positive effects of the mentioned factors on malingering.

Keywords: malingerers, mental profile, MMPI, NEO PI-R, personality profile

Procedia PDF Downloads 260
2446 Reliable Soup: Reliable-Driven Model Weight Fusion on Ultrasound Imaging Classification

Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

Abstract:

It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

Procedia PDF Downloads 83
2445 Introduction of Acute Paediatric Services in Primary Care: Evaluating the Impact on GP Education

Authors: Salman Imran, Chris Healey

Abstract:

Traditionally, medical care of children in England and Wales starts from primary care with a referral to secondary care paediatricians who may not investigate further. Many primary care doctors do not undergo a paediatric rotation/exposure in training. As a result, there are many who have not acquired the necessary skills to manage children hence increasing hospital referral. With the current demand on hospitals in the National Health Service managing more problems in the community is needed. One way of handling this is to set up clinics, meetings and huddles in GP surgeries where professionals involved (general practitioner, paediatrician, health visitor, community nurse, dietician, school nurse) come together and share information which can help improve communication and care. The increased awareness and education that paediatricians can impart in this way will help boost confidence for primary care professionals to be able to be more self-sufficient. This has been tried successfully in other regions e.g., St. Mary’s Hospital in London but is crucial for a more rural setting like ours. The primary aim of this project would be to educate specifically GP’s and generally all other health professionals involved. Additional benefits would be providing care nearer home, increasing patient’s confidence in their local surgery, improving communication and reducing unnecessary patient flow to already stretched hospital resources. Methods: This was done as a plan do study act cycle (PDSA). Three clinics were delivered in different practices over six months where feedback from staff and patients was collected. Designated time for teaching/discussion was used which involved some cases from the actual clinics. Both new and follow up patients were included. Two clinics were conducted by a paediatrician and nurse whilst the 3rd involved paediatrician and local doctor. The distance from hospital to clinics varied from two miles to 22 miles approximately. All equipment used was provided by primary care. Results: A total of 30 patients were seen. All patients found the location convenient as it was nearer than the hospital. 70-90% clearly understood the reason for a change in venue. 95% agreed to the importance of their local doctor being involved in their care. 20% needed to be seen in the hospital for further investigations. Patients felt this to be a more personalised, in-depth, friendly and polite experience. Local physicians felt this to be a more relaxed, familiar and local experience for their patients and they managed to get immediate feedback regarding their own clinical management. 90% felt they gained important learning from the discussion time and the paediatrician also learned about their understanding and gaps in knowledge/focus areas. 80% felt this time was valuable for targeted learning. Equipment, information technology, and office space could be improved for the smooth running of any future clinics. Conclusion: The acute paediatric outpatient clinic can be successfully established in primary care facilities. Careful patient selection and adequate facilities are important. We have demonstrated a further step in the reduction of patient flow to hospitals and upskilling primary care health professionals. This service is expected to become more efficient with experience.

Keywords: clinics, education, paediatricians, primary care

Procedia PDF Downloads 162
2444 Learning about the Strengths and Weaknesses of Urban Climate Action Plans

Authors: Prince Dacosta Aboagye, Ayyoob Sharifi

Abstract:

Cities respond to climate concerns mainly through their climate action plans (CAPs). A comprehensive content analysis of the dynamics in existing urban CAPs is not well represented in the literature. This literature void presents a difficulty in appreciating the strengths and weaknesses of urban CAPs. Here, we perform a qualitative content analysis (QCA) on CAPs from 278 cities worldwide and use text-mining tools to map and visualize the relevant data. Our analysis showed a decline in the number of CAPs developed and published following the global COVID-19 lockdown period. Evidently, megacities are leading the deep decarbonisation agenda. We also observed a transition from developing mainly mitigation-focused CAPs pre-COP21 to both mitigation and adaptation CAPs. A lack of inclusiveness in local climate planning was common among European and North American cities. The evidence is a catalyst for understanding the trends in existing urban CAPs to shape future urban climate planning.

Keywords: urban, climate action plans, strengths, weaknesses

Procedia PDF Downloads 94
2443 Chemical Reaction Algorithm for Expectation Maximization Clustering

Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

Procedia PDF Downloads 709
2442 Hybrid Fuzzy Weighted K-Nearest Neighbor to Predict Hospital Readmission for Diabetic Patients

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

Procedia PDF Downloads 184
2441 A Pattern Recognition Neural Network Model for Detection and Classification of SQL Injection Attacks

Authors: Naghmeh Moradpoor Sheykhkanloo

Abstract:

Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

Procedia PDF Downloads 468
2440 Locus of Control and Sense of Happiness: A Mediating Role of Self-Esteem

Authors: Ivanna Shubina

Abstract:

Background/Objectives and Goals: Recent interest in positive psychology is reflected in a plenty of studies conducted on its basic constructs (e.g. self-esteem and happiness) in interrelation with personality features, social rules, business and technology development. The purpose of this study is to investigate the mediating role of self-esteem, exploring the relationships between self-esteem and happiness, self-esteem and locus of control (LOC). It hypothesizes that self-esteem may be interpreted as a predictor of happiness and mediator in the locus of control establishment. A plenty of various empirical studies results have been analyzed in order to collect data for this theoretical study, and some of the analysed results can be considered as arguable or incoherent. However, the majority of results indicate a strong relationship between three considered concepts: self-esteem, happiness, the locus of control. Methods: In particular, this study addresses the following broad research questions: i) Is self-esteem just an index of global happiness? ii) May happiness be possible or realizable without a healthy self-confidence and self-acceptance? iii) To what extent does self-esteem influence on the level of happiness? iv) Is high self-esteem a sufficient condition for happiness? v) Is self-esteem is a strong predictor of internal locus of control maintenance? vi) Is high self-esteem related to internal LOC, while low self-esteem to external LOC? In order to find the answers for listed questions, 60 reliable sources have been analyzed, results of what are discussed more detailed below. Expected Results/Conclusion/Contribution:It is recognized that the relationship between self-esteem, happiness, locus of control is complex: internal LOC is contributing to happiness, but it is not directly related to it; self-esteem is a powerful and important psychological factor in mental health and well-being; the feelings of being worthy and empowered are associated with significant achievements and high self-esteem; strong and appropriate self-esteem (when the discrepancy between “ideal” and “real” self is balanced) is correlated with more internal LOC (when the individual tends to believe that personal achievements depend on possessed features, vigor, and persistence). Despite the special attention paid to happiness, the locus of control and self-esteem, independently, theoretical and empirical equivocations within each literature foreclose many obvious predictions about the nature of their empirical distinction. In terms of theoretical framework, no model has achieved consensus as an ultimate theoretical background for any of the mentioned constructs. To be able to clarify the relationship between self-esteem, happiness, and locus of control more interdisciplinary studies have to take place in order to get data on heterogeneous samples, provided from various countries, cultures, and social groups.

Keywords: happiness, locus of control, self-esteem, mediation

Procedia PDF Downloads 243
2439 Recruitment Strategies and Migration Regulations for International Students in the United States and Canada: A Comparative Study

Authors: Aynur Charkasova

Abstract:

The scientific and economic contributions of international students cannot be underestimated. International education continues to be a competitive global industry, and many countries are seeking to recruit the best and the brightest to reinforce scientific innovations, boost intercultural learning, and bring more funding to the universities and colleges. Substantial changes in international educational policies and migration regulations have been made in the hopes of recruiting global talent. This paper explores and compares recruitment strategies, employment opportunities, and a legal path to permanent residency policies related to international students in the United States of America and Canada. This study will utilize the legal information available by the government websites of both countries, peer-reviewed scholarly articles and will highlight which approach promises a better path in recruiting and retention of international students. The findings from the study will be discussed and recommendations will be provided.

Keywords: international students, current immigration policies, STEM, visa reforms for international students

Procedia PDF Downloads 59
2438 Using 'Know, Want to Know, Learned' Strategy to Enhance the Seventh C Grade Students' Reading Comprehension Achievement at SMPN 1 Mumbulsari

Authors: Abdul Rofiq Badril Rizal M. Z.

Abstract:

Reading becomes one of the most important skills in teaching and learning English. The purpose of this research was to improve the students' active participation, and reading comprehension achievement by using Know, Want to Know, Learned (KWL) strategy. The research design was Classroom Action Research. The area and participants of this research were chosen by using purposive method. The data were collected by observation, a reading comprehension test, interview, and documentation. The results showed that there was significant improvement in Cycle 1 to Cycle 2 of the research. In cycle 1, the students’ active participation increased 49.77% from 28% to 77.77. In addition, in cycle 2, the students’ active participation also increased by 14.17% from 77.77% to 81.94%. The students’ reading comprehension achievement also increased by 52.14% from 25% to 77.14% in Cycle 1 and increased by 5.71% from 77.14% to 82.85% in cycle 2. It indicated that using Know, Want to Know, Learned (KWL) strategy could enhance the Seventh C grade students’ descriptive text reading comprehension achievement, and active participation.

Keywords: active participation, reading comprehension, classroom action research, Indonesian folktales

Procedia PDF Downloads 132
2437 Archive's Accessibility of University Archive: Case Study at Universitas Gadjah Mada Archives

Authors: Berlian Eka Kurnia, Mohamad Very Setiawan, Rahmat Fadhli

Abstract:

Archives play an important role in organization’s continuity, especially related to the learning activities in the past. Archive management is considered accessible when the archive can be used when needed. University archive can support research activities for institutions, besides, archive management services also have to pay attention to the accessibility that became a barometer of how easy users get the data or information from an archive, use and understand it. This study identifies about the accessibility of archive services at the Universitas Gadjah Mada, with case study method. Universitas Gadjah Mada archives not only provide a service to the academicians, but also for public. Universitas Gadjah Mada archive can be traced online and offline. Online searching archives can be acceessed through an application “SIKS” and offline searching can be accessed by "finding aids" printed. Although Universitas Gadjah Mada Archives has its own procedures to access the archive directly, but they also remain guided by National Archive of Indonesia.

Keywords: archival institution, university archive, archive’s accessibility, archive management

Procedia PDF Downloads 320
2436 Achievement Goal Orientations of Schooling Adolescents in Bayelsa State, Nigeria: Implications for Sustainable Development

Authors: Iniye Irene Wodi, Allen A. Agih

Abstract:

Goal theory perspective as an emerging trend in students’ motivation explores reasons why students engage in achievement related behaviour. While previous research typifies students’ goal orientations into two dimensions of mastery and performance orientations in various other parts of the world, not much has been done in this regard in Nigeria and specifically in Bayelsa state to the best of the researcher’s knowledge. To this end, the study explores the achievement goal orientations of schooling adolescents in Bayelsa State. The sample of the study consists of 220 schooling adolescents drawn from four urban schools in the state. A modified form of the Patterns of Adaptive learning survey (PALS) questionnaire was used to elicit data. Results indicated that schooling adolescents in Bayelsa state are mastery as well as performance oriented. The students also did not differ in goal orientations by gender. The implications of this for sustainable development were highlighted.

Keywords: achievement goals, goal orientations, schooling adolescents, sustainable development

Procedia PDF Downloads 274
2435 Botnet Detection with ML Techniques by Using the BoT-IoT Dataset

Authors: Adnan Baig, Ishteeaq Naeem, Saad Mansoor

Abstract:

The Internet of Things (IoT) gadgets have advanced quickly in recent years, and their use is steadily rising daily. However, cyber-attackers can target these gadgets due to their distributed nature. Additionally, many IoT devices have significant security flaws in their implementation and design, making them vulnerable to security threats. Hence, these threats can cause important data security and privacy loss from a single attack on network devices or systems. Botnets are a significant security risk that can harm the IoT network; hence, sophisticated techniques are required to mitigate the risk. This work uses a machine learning-based method to identify IoT orchestrated by botnets. The proposed technique identifies the net attack by distinguishing between legitimate and malicious traffic. This article proposes a hyperparameter tuning model to improvise the method to improve the accuracy of existing processes. The results demonstrated an improved and more accurate indication of botnet-based cyber-attacks.

Keywords: Internet of Things, Botnet, BoT-IoT dataset, ML techniques

Procedia PDF Downloads 8
2434 Design of Built-Spaces and Enhanced Psychological Wellbeing by Limiting Effect of SBS: An Analytical Study across Students in Indian Universities

Authors: Sadaf H. Khan, Jyoti Kumar

Abstract:

Sick Building Syndrome (SBS) is a situation in which inhabitants of a building develop illness symptoms or get infected with a chronic disease as a result of the building in which they reside or work. Certain symptoms tend to get more severe as an individual spends more time in the building; however, they generally improve with time or even disappear when they leave that space. Though ‘Design of Built-Spaces’ is a crucial factor in regulating these symptoms but it still needs to be identified further as to what specific design features of a ‘Built-Space’ trigger sick building syndrome (SBS). Much of the research work present to date is focused on the physiological or physical sickness caused due to inappropriate built-space design. In this paper, the psychological aspects of sick building syndrome (SBS) will be investigated across the adult population, more specifically graduate students in India trying to settle in back to their previous physical work environments, i.e., campus, classrooms, hostels, after a very long hold which lasted more than a year due to lockdowns during Covid-19 crisis all over the world. The study will follow an analytical approach and the data will be collected through self-reported online surveys. The purpose of this study is to enquire causal agents, diagnosable symptoms and remedial design of built spaces which can enhance the productive level of built environments and better facilitate the inhabitants by improving their psychological wellbeing, which is the most uprising concern. The fact that SBS symptoms can be studied only within the initial few weeks as an occupant starts interacting with a built-environment and leaves as the occupant leaves that space or zone, the post-lockdown incoming of students back to their respective campuses provides an opportunity to clearly draw multiple conclusions of the relationship that exist between the Design of Built-Spaces and Psychological Sickness Syndrome associated with it. The study will be one of a kind approach for understanding and formulating methods to improve psychological wellbeing within a built-setting by better identifying factors associated with these psychological symptoms, including anxiety, mental fatigue, reduced attention span and reduced memory span as refined symptoms of SBS discussed in 1987 by Molhave within his study.

Keywords: built-environment psychology, built-space design, healthcare architecture, psychological wellbeing

Procedia PDF Downloads 172
2433 Implementation of a Distant Learning Physician Assistant Program in Northern Michigan to Address Health Care Provider Shortage: Importance of Evaluation

Authors: Theresa Bacon-Baguley, Martina Reinhold

Abstract:

Introduction: The purpose of this paper is to discuss the importance of both formative and summative evaluation of a Physician Assistant (PA) program with a distant campus delivered through Interactive Television (ITV) to assure equity of educational experiences. Methodology: A needs assessment utilizing a case-control design determined the need and interest in expanding the existing PA program to northern Michigan. A federal grant was written and funded, which supported the hiring of two full-time faculty members and support staff at the distant site. The strengths and weaknesses of delivering a program through ITV were evaluated using weekly formative evaluation, and bi-semester summative evaluation. Formative evaluation involved discussion of lecture content to be delivered, special ITV needs, orientation of new lecturers to the system, student concerns, support staff updates, and scheduling of student/faculty traveling between the two campuses. The summative evaluation, designed from a literature review of barriers to ITV, included 19 statements designed to evaluate the following items: quality of technology (audio, video, etc.), confidence in the ITV system, quality of instruction and instructor interaction between the two locations, and availability of resources at each location. In addition, students were given the opportunity to write qualitative remarks for each course delivered between the two locations. This summative evaluation was given to all students at mid-semester and at the end of the semester. The goal of the summative evaluation was to have 80% or greater of the students respond favorably (‘Very Good’ or ‘Good’) to each of the 19 statements. Results: Prior to the start of the first cohort at the distant campus, the technology was tested. During this time period, the formative evaluations identified key components needing modification, which were rapidly addressed: ability to record lectures, lighting, sound, and content delivery. When the mid-semester summative survey was given to the first cohort of students, 18 of the 19 statements in the summative evaluation met the goal of 80% or greater in the favorable category. When the summative evaluation statements were stratified by the two cohorts, the summative evaluation identified that students at the home location responded that they did not have adequate access to printers, and students at the expansion location responded that they did not have adequate access to library resources. These results allowed the program to address the deficiencies through contacting informational technology for additional printers, and to provide students with knowledge on how to access library resources. Conclusion: Successful expansion of programs to a distant site utilizing ITV technology requires extensive monitoring using both formative and summative evaluation. The formative evaluation allowed for quick identification of issues that could immediately be addressed, both at the planning and developing stage, as well as during implementation. Through use of the summative evaluation the program is able to monitor the success/ effectiveness of the expansion and identify specific needs of students at each location.

Keywords: assessment, distance learning, formative feedback, interactive television (ITV), student experience, summative feedback, support

Procedia PDF Downloads 245
2432 Significance of Architectural Conservation Today, For a Better Tomorrow

Authors: Sneha Manjunath

Abstract:

Architecture is a continuous process of evolution that keeps changing and evolving through time and gives rise to various design solutions based on the purpose of change and the present function of the space. This evolution in design has been happening for a long time and hence a variety of climate-responsive, context-responsive and human-responsive developments in habitats are witnessed. India has been one of the hot spots for the conservation of heritage and architecture. Buildings ranging from Indus-valley civilization to modern contemporary dwellings have all evolved in one or the other way. Various historical sites such as Hampi in Karnataka, Taj Mahal in Agra and various temples in Southern India are identified and preserved under the Archeological Survey of India. The main objective of such preservation is to help in protecting, preserving and keeping it intact for the future. Study of such heritage-rich buildings and building techniques helps us in understanding the psychology, lifestyle and socio-cultural impacts it had on the complete urban fabric that developed in a region. It also gives an insight into the occupation, economic status and religious beliefs that gave rise to a pattern in an urban form that was more inclusive and appropriate as per the need of the users. Today’s generation draws various inspirations from history with respect to space planning, building services such as lighting, ventilation and sanitation systems and elevation treatments. It is important to know and understand the importance of certain urban planning techniques used to develop ancient towns or cities in a radial pattern, square pattern, or checkered pattern depending on the need of the administrative set-up of the respective town or city. It is believed that every element of design undergoes evolution and it is important for a designer to know, respect and develop the same for the future so as to acknowledge and conserve every aspect of heritage that has been a backbone in urban form generation even today. Hampi in the Karnataka state of India is a very good example of how the monuments and dwellings from 14th Century still stand strong. Temples from North India, such as Kedarnath Temple, survived heavy floods because of their building techniques. Such building materials and construction techniques are to be revived and reused for a better perspective towards space planning in urbanized cities.

Keywords: architecture, urban form, heritage, town planning

Procedia PDF Downloads 115
2431 The Effectiveness of Online Learning in the Wisconsin Technical College System

Authors: Julie Furst-Bowe

Abstract:

Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

Procedia PDF Downloads 133
2430 Learning through Gaming with Mobile Devices

Authors: Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander, Alberto Lamadrid Alvarez, Héctor Fernando Valencia Pérez

Abstract:

Financial education is among the areas of opportunity in the Spanish-speaking from an early age to high school, through mobile devices such as cell phones and tablets using ludic and fun applications like interactive games, children can learn money management and investment through time, thereby fostering the habit of saving and/or sound management of cash and family business resources, having interaction with an uncontrolled environment such as the involvement of other players in the external decisions of the environment in which the game is play. The application proposed in Phase 1 (design and development) was designed in multi-user environments, under methodologies of hybrid programming for any platform on the market and designed under CMMI standards that allow for quality production over time, following up on these improvements counting with continuous user feedback and usage statistics.

Keywords: mobile educational games, ludic games, children, multiuser, design and software development

Procedia PDF Downloads 381
2429 Financial Reports and Common Ownership: An Analysis of the Mechanisms Common Owners Use to Induce Anti-Competitive Behavior

Authors: Kevin Smith

Abstract:

Publicly traded company in the US are legally obligated to host earnings calls that discuss their most recent financial reports. During these calls, investors are able to ask these companies questions about these financial reports and on the future direction of the company. This paper examines whether common institutional owners use these calls as a way to indirectly signal to companies in their portfolio to not take actions that could hurt the common owner's interests. This paper uses transcripts taken from the earnings calls of the six largest health insurance companies in the US from 2014 to 2019. This data is analyzed using text analysis and sentiment analysis to look for patterns in the statements made by common owners. The analysis found that common owners where more likely to recommend against direct price competition and instead redirect the insurance companies towards more passive actions, like investing in new technologies. This result indicates a mechanism that common owners use to reduce competition in the health insurance market.

Keywords: common ownership, text analysis, sentiment analysis, machine learning

Procedia PDF Downloads 73
2428 A Memristive Device with Intrinsic Rectification Behavior and Performace of Crossbar Arrays

Authors: Yansong Gao, Damith C.Ranasinghe, Siad F. Al-Sarawi, Omid Kavehei, Derek Abbott

Abstract:

Passive crossbar arrays is in principle the simplest functional electrical circuit, together with memristive device in cross-point, holding great promise in future high-density, non-volatile memories. However, the greatest problem of crossbar array is the sneak path current. In this paper, we investigate one type of memristive device with intrinsic rectification behavior to address the sneak path currents. Firstly, a SPICE behavior model written in Verilog-A language of the memristive device is presented to fit experimental data published in literature. Next, systematic performance simulations including read margin and power consumption of crossbar array, which uses the self-rectifying memristive device as storage element at cross-point, with respect to different crossbar sizes, interconnect resistance, ratio of HRS/LRS (High Resistance State/ Low Resistance State), rectification ratio and different read schemes are conducted. Subsequently, Trade-offs among reading margin, power consumption, and reading schemes are analyzed to provide guidelines for circuit design. Finally, performance comparison between the memristive device with/without intrinsic rectification behavior is given to show the worthiness of this intrinsic rectification behavior.

Keywords: memristive device, memristor, crossbar, RRAM, read margin, power consumption

Procedia PDF Downloads 435
2427 An Accurate Computer-Aided Diagnosis: CAD System for Diagnosis of Aortic Enlargement by Using Convolutional Neural Networks

Authors: Mahdi Bazarganigilani

Abstract:

Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

Procedia PDF Downloads 160
2426 Clothes Identification Using Inception ResNet V2 and MobileNet V2

Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

Abstract:

To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

Procedia PDF Downloads 186
2425 Vehicle Timing Motion Detection Based on Multi-Dimensional Dynamic Detection Network

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

Procedia PDF Downloads 129
2424 The Neuroscience Dimension of Juvenile Law Effectuates a Comprehensive Treatment of Youth in the Criminal System

Authors: Khushboo Shah

Abstract:

Categorical bans on the death penalty and life-without-parole sentences for juvenile offenders in a growing number of countries have established a new era in juvenile jurisprudence. This has been brought about by integration of the growing knowledge in cognitive neuroscience and appreciation of the inherent differences between adults and adolescents over the last ten years. This evolving understanding of being a child in the criminal system can be aptly reflected through policies that incorporate the mitigating traits of youth. First, the presentation will delineate the structures in cognitive neuroscience and in particular, focus on the prefrontal cortex, the amygdala, and the basal ganglia. These key anatomical structures in the brain are linked to three mitigating adolescent traits—an underdeveloped sense of responsibility, an increased vulnerability to negative influences, and transitory personality traits—that establish why juveniles have a lessened culpability. The discussion will delve into the details depicting how an underdeveloped prefrontal cortex results in the heightened emotional angst, high-energy and risky behavior characteristic of the adolescent time period or how the amygdala, the emotional center of the brain, governs different emotional expression resulting in why teens are susceptible to negative influences. Based on this greater understanding, it is incumbent that policies adequately reflect the adolescent physiology and psychology in the criminal system. However, it is important to ensure that these views are appropriately weighted while considering the jurisprudence for the treatment of children in the law. To ensure this balance is appropriately stricken, policies must incorporate the distinctive traits of youth in sentencing and legal considerations and yet refrain from the potential fallacies of absolving a juvenile offender of guilt and culpability. Accordingly, three policies will demonstrate how these results can be achieved: (1) eliminate housing of juvenile offenders in the adult prison system, (2) mandate fitness hearings for all transfers of juveniles to adult criminal court, and (3) use the post-disposition review as a type of rehabilitation method for juvenile offenders. Ultimately, this interdisciplinary approach of science and law allows for a better understanding of adolescent psychological and social functioning and can effectuate better legal outcomes for juveniles tried as adults.

Keywords: criminal law, Juvenile Justice, interdisciplinary, neuroscience

Procedia PDF Downloads 325
2423 The Relationship among EFL Learners’ Creativity, Emotional Intelligence and Self-Efficacy

Authors: Behdoukht Mall Amiri, Zohreh Gheydar

Abstract:

The thrust of the current study was to investigate the relationship among EFL learners' creativity (CR), emotional intelligence (EI), and self-efficacy (SE). To this end, a group of 120 male and female learners, between the ages of 19 and 35 studying BA in English Translation and MA in Teaching English at Islamic Azad University, Central Tehran were selected using convenient sampling and were given three questionnaires: Bar-On’s EQ-I questionnaire by Bar-On (1997), the General Self-Efficacy Scale questionnaire (SGSES) by Sherer et al. (1982), and a questionnaire of creativity (CR) by O'Neil, Abedi, and Spielberger (1992). Analysis of the results through Pearson Moment Correlation Coefficient showed that there was not a significant relationship between students’ CR and EI, and EI and SE. In addition, CR and SE were correlated significantly but negatively. Multiple regressions revealed that CR could significantly predict SE. Regarding the findings of the study, the obtained results may help EFL teachers, teacher trainers, materials developers, and educational policy makers to possess a broader perspective and heightened degree knowledge toward the TEFL practice and to take practical steps toward the attainments of the desired objectives of the profession.

Keywords: creativity, emotional intelligence, self-efficacy, learning

Procedia PDF Downloads 447
2422 Simulation of Government Management Model to Increase Financial Productivity System Using Govpilot

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 87