Search results for: classification of people

Authors: Jukka Törrönen

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In the article, we examine the interplay between the practices of heavy drinking and exercise among young people as patterned around the ‘social’ and ‘physical health’ approaches. The comparison helps us to clarify why young people are currently drinking less than earlier and how the neoliberal healthism discourse, as well as the feminine tradition of taking care of one’s body, are modifying young people’s heavy drinking practices. The data is based on interviews (n = 56) in Sweden among 15-16-year-olds and 18˗19-year-olds. By drawing on Pierre Bourdieu’s concepts of habitus, field, and capital, we examine what kinds of resources of wellbeing young people accumulate in the fields of heavy drinking and exercise, how these resources carry symbolic value for distinction, and what kind of health-related habitus they imply. The analysis suggests that as heavy drinking is no longer able to stand as a practice through which one may acquire capital that is more valuable than the capital acquired in other fields, this lessens peer pressure to drink among young people. Our analysis further shows that the healthism discourse modifies young people’s heavy drinking practices both from inside and from outside. The interviewees translate the symbolic value of healthism discourse to social vulnerability and deploy it for the purposes of increasing one’s social status among peers. Moreover, our analysis demonstrates that the social spaces and positions in intoxication and exercise are shaped by gendered dualisms of masculine dominance. However, while the interviewees naturalize the gender binaries in intoxication as based on biological drives, they understand gender binaries in exercise as normative social constructions of neoliberal society. As these binaries emphasize the struggle for recognition of the symbolic value of bodily look, they may shift young men’s attention from risk-taking to issues that traditionally have been female concerns.

Keywords: young people, decline in drinking , health, intoxication, exercise, Bourdieu

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Marina Diković

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By giving personal opinions, suggestions and criticism through e-democracy, young people can reinforce the adoption of decisions which they have an impact on. The purpose of this research was to examine the opinion of university students about the possibility of their decision-making by using information and communication technology (ICT). The questionnaire examined young people's values and behaviour associated with e-democracy and the related decision-making. Students are most active online when it comes to finding information connected with their academic responsibilities, but less frequently take part in democratic processes in society, both at the national and local level. E-democracy as a tool can be learned in programmes of Human Rights Education and Citizenship Education. 

Keywords: active citizens, e-democracy, information and communication technology (ICT), university students

Procedia PDF Downloads 228

Authors: Esther Moraleda Sepúlveda, Soraya Delgado Matute, Paula Salido Escudero, Raquel Mimoso García, M Cristina Alcón Lancho

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Although there is some consensus when it comes to establishing the lexicon as one of the strengths of language in people with Down Syndrome (DS), little is known about its evolution throughout development and changes based on age. The objective of this study was to find out if there are differences in receptive vocabulary between adolescence and adulthood. In this research, 30 people with DS between 11 and 40 years old, divided into two age ranges (11-18; 19 - 30) and matched in mental age, were evaluated through the Peabody Vocabulary Test. The results show significant differences between both groups in favor of the group with the oldest chronological age and a direct correlation between chronological age and receptive vocabulary development, regardless of mental age. These data support the natural evolution of the passive lexicon in people with DS.

Keywords: down syndrome, language, receptive vocabulary, adolescents, adults

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Authors: Anyapak Prapannetivuth

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The purpose of this research is to investigate the marketing mix that is perceived to be important for the small sized hotels in Pattaya. Unlike previous studies, this research provides insights through a review of the marketing activities performed by the small sized hotels. Nine owners and marketing manager of small sized hotels and resorts, all local Chonburi people, were selected for an in-depth interview. A snowball sampling process was employed. The research suggests that seven marketing mixes (e.g. Product, Price, Place, Promotion, People, Physical Evidence and Process) were commonly used by these hotels, however, three types – People, price and physical evidence were considered most important by the owners.

Keywords: marketing mix, marketing tools, small sized hotels, pattaya

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Majid A. AlSayari

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The study reported here investigated social cognitive theory (SCT) in the context of Vocational Rehab (VR) for people with disabilities. The prime purpose was to increase knowledge of VR phenomena and make recommendations for improving VR services. The sample consisted of 242 persons with Spinal Cord Injuries (SCI) who completed questionnaires. A further 32 participants were Trainers. Analysis of questionnaire data was carried out using factor analysis, multiple regression analysis, and thematic analysis. The analysis suggested that, in motivational terms, and consistent with research carried out in other academic contexts, self-efficacy was the best predictor of VR performance. The author concludes that that VR self-efficacy predicted VR training performance.

Keywords: people with physical disabilities, social cognitive theory, self-efficacy, vocational training

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Authors: Ali̇ Si̇nan Soğanci

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The cement stabilization is one of the ground improvement method applied worldwide to increase the strength of clayey soils. The using of cement has got lots of advantages compared to other stabilization methods. Cement stabilization can be done quickly, the cost is low and creates a more durable structure with the soil. Cement can be used in the treatment of a wide variety of soils. The best results of the cement stabilization were seen on silts as well as coarse-grained soils. In this study, blocks of clay were taken from the Apa-Hotamış conveyance channel route which is 125km long will be built in Konya that take the water with 70m3/sec from Mavi tunnel to Hotamış storage. Firstly, the index properties of clay samples were determined according to the Unified Soil Classification System. The experimental program was carried out on compacted soil specimens with 0%, 7 %, 15% and 30 % cement additives and the results of unconfined compression strength were discussed. The results of unconfined compression tests indicated an increase in strength with increasing cement content.

Keywords: cement stabilization, unconfined compression test, clayey soils, unified soil classification system.

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Authors: Aijing Luo, Zirui Xin, Yifeng Yuan

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Background: With the rapid development of the online health community, more and more patients or families are seeking health information on the Internet. Objective: This study aimed to discuss how to fully reveal the health information needs expressed by hypertensive patients in their questions in the online environment. Methods: This study randomly selected 1,000 text records from the question data of hypertensive patients from 2008 to 2018 collected from the website www.haodf.com and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning the intention of each hypertensive patient based on the patient’s question and used co-occurrence network analysis to explore the features of the health information needs of hypertensive patients. Results: The classification system for health information needs of patients with hypertension is composed of 9 parts: 355 kinds of drugs, 395 kinds of symptoms and signs, 545 kinds of tests and examinations , 526 kinds of demographic data, 80 kinds of diseases, 37 kinds of risk factors, 43 kinds of emotions, 6 kinds of lifestyles, 49 kinds of questions. The characteristics of the explored online health information needs of the hypertensive patients include: i)more than 49% of patients describe the features such as drugs, symptoms and signs, tests and examinations, demographic data, diseases, etc. ii) these groups are most concerned about treatment (77.8%), followed by diagnosis (32.3%); iii) 65.8% of hypertensive patients will ask doctors online several questions at the same time. 28.3% of the patients are very concerned about how to adjust the medication, and they will ask other treatment-related questions at the same time, including drug side effects, whether to take drugs, how to treat a disease, etc.; secondly, 17.6% of the patients will consult the doctors online about the causes of the clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, medication, and examinations. Conclusion: In the online environment, the health information needs expressed by Chinese hypertensive patients to doctors are personalized; that is, patients with different background features express their questioning intentions to doctors. The classification system constructed in this study can guide health information service providers in the construction of online health resources, to help solve the problem of information asymmetry in communication between doctors and patients.

Keywords: online health community, health information needs, hypertensive patients, doctor-patient communication

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Authors: Yu-Min Chang, Kuo-Sheng Tsai, Hung-Te Tsai, Chia-Hsin Li

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This paper presents the early-warning lights classification management system for industrial parks promoted by the Taiwan Environmental Protection Administration (EPA) since 2011, including the definition of each early-warning light, objectives, action program and accomplishments. All of the 151 industrial parks in Taiwan were classified into four early-warning lights, including red, orange, yellow and green, for carrying out respective pollution management according to the monitoring data of soil and groundwater quality, regulatory compliance, and regulatory listing of control site or remediation site. The Taiwan EPA set up a priority list for high potential polluted industrial parks and investigated their soil and groundwater qualities based on the results of the light classification and pollution potential assessment. In 2011-2013, there were 44 industrial parks selected and carried out different investigation, such as the early warning groundwater well networks establishment and pollution investigation/verification for the red and orange-light industrial parks and the environmental background survey for the yellow-light industrial parks. Among them, 22 industrial parks were newly or continuously confirmed that the concentrations of pollutants exceeded those in soil or groundwater pollution control standards. Thus, the further investigation, groundwater use restriction, listing of pollution control site or remediation site, and pollutant isolation measures were implemented by the local environmental protection and industry competent authorities; the early warning lights of those industrial parks were proposed to adjust up to orange or red-light. Up to the present, the preliminary positive effect of the soil and groundwater quality management system for industrial parks has been noticed in several aspects, such as environmental background information collection, early warning of pollution risk, pollution investigation and control, information integration and application, and inter-agency collaboration. Finally, the work and goal of self-initiated quality management of industrial parks will be carried out on the basis of the inter-agency collaboration by the classified lights system of early warning and management as well as the regular announcement of the status of each industrial park.

Keywords: industrial park, soil and groundwater quality management, early-warning lights classification, SOP for reporting and treatment of monitored abnormal events

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Authors: Maya Kagan, Michal Itzick, Patricia Tal-Katz

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Social workers hold a variety of roles and practices, and one of these involves the care, treatment, and rehabilitation of disabled people. The current study assesses the association between demographic factors, attitudes towards social workers, the stigma attached to seeking social worker help, perceived social support, and psychological distress - and the self-reported likelihood of seeking social worker help, among people with physical disabilities (PWPD) in Israel. Data collection utilized structured questionnaires, administered to a sample of 435 PWPD. Statistical analyses were done using SPSS software. The findings suggest that women, older respondents, people with more positive attitudes towards social workers, with higher levels of psychological distress and of social support, and with a lower level of stigma, reported a greater likelihood of seeking social worker help. The study's conclusion is that there are certain avoidance factors among PWPD that might discourage them from seeking professional social worker help. Therefore, it is important that social workers identify these factors and develop interventions aimed at encouraging PWPD to seek professional social worker help in case of need, and also develop practices adjusted to PWPD's unique needs.

Keywords: attitudes towards social workers, people with physical disabilities, perceived social support, psychological distress, seeking help, stigma

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Authors: Ikhsan Fahmi, Hasti Amanda Ilmi Putri

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The COVID-19 pandemic caused large scale social restrictions which have an impact on aspects of the nation’s life, such as the level of poverty. One of the causes of poverty is the lack level of public health. The calculation of poverty is seen as an inability from an economic side of basic food and nonfood needs, which is measured from the expenditure side, one of which is health expenditure. The purpose of this study is to analyze the effect of health subsidies on society on the level of poverty in 2020 in Indonesia. The main source used is the National Socio-Economic Survey of Consumption Expenditure and Cor, March 2020. From the result of the analysis, it was found that the percentage of poor people increased from the previous 9.78 percent to 9,92 percent, or there were 391,000 people who were previously not poor people who became poor when the health subsidies were revoked. There is a pattern of distribution of provinces in Indonesia between the average cost of health subsidies per capita per month if the government does not provide health subsidies and the increase in the percentage of poor people. This indicates that government intervention related to health subsidised is important in terms of poverty alleviation in Indonesia.

Keywords: poverty, health, subsidy, expenditure

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Authors: B. Poorna Chander

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Urban centre is one of the most important parts of the city where all the community activities take place. They are the active zones which enhance the structure of a city. The structure of the city refers to its form, mobility patterns, and concentration of people and lifestyles of people. The purpose of the research paper is to study how does the character or structure of city changes when a new centre is established. An attempt has been made to understand this by studying how the formation of centre has been changing the form or the structure of the city since the ancient times, what are the notions of a city and a centre by various architects, by studying the various models of the future city proposed by them. And then the data has been linked to how the formation of the new centres is changing the city. As the demands of the city are increasing, it also regulates how the new centres are formed. So both, the city and the centre are interdependent on each other.

Keywords: centre, activities, lifestyles, people, form

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: Liu Haitao, Wang Hengyong

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This paper attempts to kayak, Zhaoqing City, the annual training program for young men, the deconstruction and analysis, describe the characteristics of their training load, Young people to extract the key issues for training kayak, kayak training young people to clarify in Zhaoqing City, and the cause of the bottlenecks. On one hand, scientifically arranging for the coaches to adjust training load and provide the basis for periodic structure, for young people to provide practical reference kayak athletes. On the other hand, through their training load research, enrich the theoretical system kayak training project for junior kayak athletes to provide a theoretical basis.

Keywords: juniors, kayak, training programs, full year

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Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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Authors: H. E. Amb. Terry Earthwind Nichols

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Over the years Ambassador Nichols observed that successful companies all have one thing in common - belief in people. His observations of people in many companies, industries, and countries have also concluded one thing - groups of achievers far exceed the expectations and timelines of their superiors. His experience with achieving this has brought forth a model for the 21st century that will not only exceed expectations of companies, but it will also set visions for the future of business globally. It is time for real discussion around the future of work and the business model that will set the example for the world. Methodologies: In-person observations over 40 years – Ambassador Nichols present during the observations. Audio-visual observations – TV, Cinema, social media (YouTube, etc.), various news outlet Reading the autobiography of some of successful leaders over the last 75 years that lead their companies from a distinct perspective your people are your commodity. Major findings: People who believe in the leader’s vision for the company so much so that they remain excited about the future of the company and want to do anything in their power to ethically achieve that vision. People who are achieving regularly in groups, division, companies, etcetera: Live more healthfully lowering both sick time off and on-the-job accidents. Cannot wait to physically get to work as much as they can to feed off the high energy present in these companies. They are fully respected and supported resulting in near zero attrition. Simply put – they do not “Burn Out”. Conclusion: To the author’s best knowledge, 20th century practices in business are no longer valid and people are not going to work in those environments any longer. The average worker in the post-covid world is better educated than 50 years ago and most importantly, they have real-time information about any subject and can stream injustices as they happen. The Consortium Model is just the model for the evolution of both humankind and business in the 21st century.

Keywords: business model, future of work, people, paradigm shift, business management

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: G. Hafner

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A method developed at the University of Stuttgart will be presented: ‘Analysis, Evaluation and Optimization of Food Management’. A major focus is represented by quantification of food losses and food waste as well as their classification and evaluation regarding a system optimization through waste prevention. For quantification and accounting of food, food losses and food waste along the food chain, a clear definition of core terms is required at the beginning. This includes their methodological classification and demarcation within sectors of the food value chain. The food chain is divided into agriculture, industry and crafts, trade and consumption (at home and out of home). For adjustment of core terms, the authors have cooperated with relevant stakeholders in Germany for achieving the goal of holistic and agreed definitions for the whole food chain. This includes modeling of sub systems within the food value chain, definition of terms, differentiation between food losses and food wastage as well as methodological approaches. ‘Food Losses’ and ‘Food Wastes’ are assigned to individual sectors of the food chain including a description of the respective methods. The method for analyzing, evaluation and optimization of food management systems consist of the following parts: Part I: Terms and Definitions. Part II: System Modeling. Part III: Procedure for Data Collection and Accounting Part. IV: Methodological Approaches for Classification and Evaluation of Results. Part V: Evaluation Parameters and Benchmarks. Part VI: Measures for Optimization. Part VII: Monitoring of Success The method will be demonstrated at the example of an invesigation of food losses and food wastage in the Federal State of Bavaria including an extrapolation of respective results to quantify food wastage in Germany.

Keywords: food losses, food waste, resource management, waste management, system analysis, waste minimization, resource efficiency

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Authors: Mohammed Riyas Pp

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This study aimed at investigating major issues in translating the Arabic Hadith terminologies into English, focusing on choosing the most appropriate translation for each, reviewing major Hadith works in English. This study is confined to twenty terminologies with regard to classification of Hadith based on authority, strength, number of transmitters and connections in Isnad. Almost all available translations are collected and analyzed to find the most proper translation based on linguistic and translational values. To the researcher, many translations lack precise understanding of either Hadith terminologies or English language and varieties of methodologies have influence on varieties of translations. This study provides a classification of translational and conceptual issues. Translational issues are related to translatability of these terminologies and their equivalence. Conceptual issues provide a list of misunderstandings due to wrong translations of terminologies. This study ends with a suggestion for unification in translating terminologies based on convention of Muslim scholars having good understanding of Hadith terminologies and English language.

Keywords: english language, hadith terminologies, equivalence in translation, problems in translation

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Authors: Gyozo Molnar, Nancy Spencer-Cavaliere

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Research in the area of physical activity and sport, while becoming multidisciplinary, is still dominated by post-positivist approaches that have the tendency to position the researcher as an expert and the participant as subordinate thereby perpetuating an unequal balance of power. Despite physical activity’s and sport’s universal appeal, their historic practices have excluded particular groups of people who assumed lesser forms of human capital. Adapted physical activity (APA) is a field that has responded to those segregations with specific application and relevance to people with impairments. Nevertheless, to date, similar to physical activity and sport, research in APA is still dominated by post-positivist epistemology. Stemming from this, there is gradually growing criticism within the field related to the abundance of research ‘on’ people with impairments and lack of research ‘with’ and ‘by’ people with impairments. Furthermore, research questions in the field are most often pursued from a single axis of analysis and constructed by non-disabled researchers. Concurrently, while calls for interdisciplinary approaches to understanding disability are growing in popularity, there is also a clear need to take an intersectionality-informed research methodology to understanding physical activity and sport and power (im)balances therein. In other words, impairment needs to be considered in conjunction with other socially and politically constructed and historically embedded differences such as gender, race, class, etc. when analyzing physical activity and sport experiences for people with impairments. Moreover, it is reasonable to argue that non-disabled researchers must recognize and theorize ableism in its complicated intersectional manifestation to show the structural constraints that disabled scholars face in the field. Consequently, this presentation will offer an alternative approach that acknowledges and prioritizes the perspectives and experiences of people with impairments to expand the field of APA. As such, the importance of broadening epistemologies in APA and prioritizing an appreciation for multiple bits of knowledge of people with impairments through intersections of social locations (e.g., gender, race, class) will be considered.

Keywords: adapted physical activity, disability, intersectionality, post-positivist, power imbalances

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Rudranil Das

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Wrapping is a basic textile technique; it is having a great quality of decorative view. Since long back it has been embellishing life of people and their culture in different forms. It links cultures, beliefs, thoughts, technology, and above all, people. Through etymology we can study the movement of the word power of wrapping undoubtedly but in depth analyze it could provide many concepts of structural ability. Only in India, more than 105 different processes exist in the way of saree [a type of women attire] wrapping. Then many more other clothing we found in allover world which connects this technique and construction too. One of the main objectives of this study is to enrich wrapping explanation and come up with surfaces by this technique. The deliberate more fragile and stretchable structural framework makes it more appropriate in different users according to their necessity. Developments of design and technology could create new industry segment and generate a marginalized employment for the people too.

Keywords: concept, existence, philosophical attachment, technological advancement

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Authors: Debarati Bhaumik, Diptish Dey

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Multilevel models, increasingly deployed in industries such as insurance, food production, and entertainment within functions such as marketing and supply chain management, need to be transparent and ethical. Applications usually result in binary classification within groups or hierarchies based on a set of input features. Using open-source datasets, we demonstrate that popular explainability methods, such as SHAP and LIME, consistently underperform inaccuracy when interpreting these models. They fail to predict the order of feature importance, the magnitudes, and occasionally even the nature of the feature contribution (negative versus positive contribution to the outcome). Besides accuracy, the computational intractability of SHAP for binomial classification is a cause of concern. For transparent and ethical applications of these hierarchical statistical models, sound audit frameworks need to be developed. In this paper, we propose an audit framework for technical assessment of multilevel regression models focusing on three aspects: (i) model assumptions & statistical properties, (ii) model transparency using different explainability methods, and (iii) discrimination assessment. To this end, we undertake a quantitative approach and compare intrinsic model methods with SHAP and LIME. The framework comprises a shortlist of KPIs, such as PoCE (Percentage of Correct Explanations) and MDG (Mean Discriminatory Gap) per feature, for each of these three aspects. A traffic light risk assessment method is furthermore coupled to these KPIs. The audit framework will assist regulatory bodies in performing conformity assessments of AI systems using multilevel binomial classification models at businesses. It will also benefit businesses deploying multilevel models to be future-proof and aligned with the European Commission’s proposed Regulation on Artificial Intelligence.

Keywords: audit, multilevel model, model transparency, model explainability, discrimination, ethics

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Nikhil A. Gavhane, Sachin Shah, Ishant S. Mahajan, Pawan D. Bahekar

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Introduction: Millions of people are affected with dengue fever every year, which drives up healthcare expenses in many low-income countries. Organ failure and other serious symptoms may result. Another worldwide public health problem is sickle cell anaemia, which is most prevalent in Africa, the Caribbean, and Europe. Dengue epidemics have reportedly occurred in locations with a high frequency of sickle cell disease, compounding the health problems in these areas. Aims and Objectives: This study examines dengue infection in sickle cell disease-afflicted pre-schoolers. Method:This Retrospective cohort study examined paediatric patients. Young people with sickle cell disease (SCD), dengue infection, and a control group without SCD or dengue were studied. Data on demographics, SCD consequences, medical treatments, and laboratory findings were gathered to analyse the influence of SCD on dengue severity and clinical outcomes, classified as severe or non-severe by the 2009 WHO classification. Using fever or admission symptoms, the research estimated acute illness duration. Result: Table 1 compares haemoglobin genotype-based dengue episode features in SS, SC, and controls. Table 2 shows that severe dengue cases are older, have longer admission delays, and have particular symptoms. Table 3's multivariate analysis indicates SS genotype's high connection with severe dengue, multiorgan failure, and acute pulmonary problems. Table 4 relates severe dengue to greater white blood cell counts, anaemia, liver enzymes, and reduced lactate dehydrogenase. Conclusion: This study is valuable but confined to hospitalised dengue patients with sickle cell illness. Small cohorts limit comparisons. Further study is needed since findings contradict predictions.

Keywords: dengue, chills, headache, severe myalgia, vomiting, nausea, prostration

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Authors: Naufal Ahmad Rijalul Alam

Abstract:

This article presents a quality of education for the poor people in Indonesia and the offering of strategy to be done. It also investigates the influence of Islamic Education which stands behind the religious values in developing effort of government to respond the problem with using humanities approaches in medium society. The offering strategy resulted in four agenda: 1) building a shared commitment, 2) encouraging the improvement of the quality of public and private schools, 3) encouraging the use of 'the indicator of disaffection' for gifted children, and 4) encouraging the enlargement of vocational training centers and polytechnics. The conclusion is that the quality of education can be increased with these four agenda, although they are not too easy because it deals with other factors such as the economy, politics, and culture which is happening in the country.

Keywords: quality education, poor people, strategy of Islamic education, medium community

Procedia PDF Downloads 482