Search results for: social network tools

Authors: Zafer Cakmak, Birol Bulut, Cengiz Taskiran

Abstract:

Technological advances, the world becoming smaller and increasing world population increase our interdependence with individuals that we maybe never meet face to face. It is impossible for the modern individuals to escape global developments and their impact. Furthermore, it is very unlikely for the global societies to turn back from the path they are in. These effects of globalization in fact encumber the humankind at a certain extend. We succumb to these responsibilities for we desire a better future, a habitable world and a more peaceful life. In the present study, global responsibility levels of the participants were measured and the significance of global reactions that individuals have to develop on global issues was reinterpreted under the light of the existing literature. The study was conducted with general survey model, one of the survey methodologies General survey models are surveys conducted on the whole universe or a group, sample or sampling taken from the universe to arrive at a conclusion about the universe, which includes a high number of elements. The study was conducted with data obtained from 350 pre-service teachers attending 2016 spring semester to determine 'Global Social Responsibility' levels of social studies pre-service teachers based on several variables. Collected data were analyzed using SPSS 21.0 software. T-test and ANOVA were utilized in the data analysis.

Keywords: social studies, globalization, global social responsibility, education

Procedia PDF Downloads 390

Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

Abstract:

The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

Procedia PDF Downloads 151

Authors: Zeina Bourhane, Anders Lanzen, Christine Cagnon, Olfa Ben Said, Cristiana Cravo-Laureau, Robert Duran

Abstract:

The anthropogenic pressure in coastal areas increases dramatically with the exploitation of environmental resources. Biomonitoring coastal areas are crucial to determine the impact of pollutants on bacterial communities in soils and sediments since they provide important ecosystem services. However, relevant biomonitoring tools allowing fast determination of the ecological status are yet to be defined. Microbial ecology approaches provide useful information for developing such microbial monitoring tools reporting on the effect of environmental stressors. Chemical and microbial molecular approaches were combined in order to determine microbial bioindicators for assessing the ecological status of soil and river ecosystems around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected along soil/river/lake continuums in three stations around the Ichkeul Lake influenced by different human activities at two seasons (summer and winter). Contaminant pressure indexes (PI), including PAHs (Polycyclic aromatic hydrocarbons), alkanes, and OCPs (Organochlorine pesticides) contents, showed significant differences in the contamination level between the stations with seasonal variation. Bacterial communities were characterized by 16S ribosomal RNAs (rRNA) gene metabarcoding. Although microgAMBI indexes, determined from the sequencing data, were in accordance with contaminant contents, they were not sufficient to fully explain the PI. Therefore, further microbial indicators are still to be defined. The comparison of bacterial communities revealed the specific microbial assemblage for soil, river, and lake sediments, which were significantly correlated with contaminant contents and PI. Such observation offers the possibility to define a relevant set of bioindicators for reporting the effects of human activities on the microbial community structure. Such bioindicators might constitute useful monitoring tools for the management of microbial communities in coastal areas.

Keywords: bacterial communities, biomonitoring, contamination, human impacts, microbial bioindicators

Procedia PDF Downloads 164

Authors: Aghamusa Azizov

Abstract:

This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: solar activity correlation, media sentiment analysis, natural language processing, historical event patterns

Procedia PDF Downloads 77

Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

Abstract:

The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

Procedia PDF Downloads 309

Authors: Panagiotis Pentaris

Abstract:

The issue of social and legal recognition of LGBTQ families is of high importance when exploring the possibility of a family. Of equal importance is the fact that both society and the individual contribute to the overall recognition of LGBTQ families. This paper is a conceptual discussion, by methodology, of both sides; it uses a method of constructive analysis to expound on this issue. This method’s aim is to broaden conceptual theory, and introduce a new relationship between concepts that were previously not associated by evidence. This exploration has found that LGBTQ realities from an international perspective may differ and both legal and social rights are critical toward self-consciousness and the formation of a family. This paper asserts that internalised and historic oppression of LGBTQ individuals, places them, not always and not in all places, in a disadvantageous position as far as engaging with the potential of forming a family goes. The paper concludes that lack of social recognition and internalised oppression are key barriers regarding LGBTQ families.

Keywords: family, gay, self-worth, LGBTQ, social rights

Procedia PDF Downloads 125

Authors: Salim Ouchtati, Aissa Belmeguenai, Mouldi Bedda

Abstract:

In this study, we propose an offline system for the recognition of the fragmented handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part; the study is based mainly on the evaluation of neural network performances, trained with the gradient backpropagation algorithm. The used parameters to form the input vector of the neural network are extracted from the binary images of the isolated handwritten digit by several methods: the distribution sequence, sondes application, the Barr features, and the centered moments of the different projections and profiles. Secondly, the study is extended for the reading of the fragmented handwritten numeric chains constituted of a variable number of digits. The vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment) was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits).

Keywords: features extraction, handwritten numeric chains, image processing, neural networks

Procedia PDF Downloads 265

Authors: Harshadkumar Rajgor, Jeff Butterworth

Abstract:

Background: Barretts oesophagus increases the risk of developing oesophageal adenocarcinoma. Over the last 40 years, there has been a 6 fold increase in the incidence of oesophageal adenocarcinoma in the western world and the incidence rates are increasing at a greater rate than cancers of the colon, breast and lung. Endoscopic mucosal resection (EMR) is a relatively new technique being used by 2 centres in the greater midlands cancer network. EMR can be used for curative or staging purposes, for high-grade dysplasia’s and T1 tumours of the oesophagus. EMR is also suitable for those who are deemed high risk for oesophagectomy. EMR has a recurrence rate of 21% according to the Wiesbaden data. Method: A retrospective study of prospectively collected data was carried out involving 24 patients who had EMR for curative or staging purposes. Complications of residual or recurrent disease following EMR that required further treatment were investigated. Results: In 54% of cases residual or recurrent disease was suspected. 96% of patients were given clear and concise information regarding their diagnosis of high-grade dysplasia or T1 tumours. All 24 patients consulted the same specialist healthcare team. Conclusion: EMR is a safe and effective treatment for patients who have high-grade dysplasia and T1NO tumours. In 54% of cases residual or recurrent disease was suspected. Initially, only single resections were undertaken. Multiple resections are now being carried out to reduce the risk of recurrence. Complications from EMR remain low in this series and consisted of a single episode of post procedural bleeding.

Keywords: endoscopic mucosal resection, oesophageal dysplasia, T1 tumours, cancer network

Procedia PDF Downloads 316

Authors: German Hernandez-Alonso, Antonio Lazcano, Arturo Becerra

Abstract:

Until today, viruses remain controversial and poorly understood; about their origin, this problem represents an enigma and one of the great challenges for the contemporary biology. Three main theories have tried to explain the origin of viruses: regressive evolution, escaped host gene, and pre-cellular origin. Under the perspective of the escaped host gene theory, it can be assumed a cellular origin of viral components, like protein RNA-binding domains. These universal distributed RNA-binding domains are related to the RNA metabolism processes, including transcription, processing, and modification of transcripts, translation, RNA degradation and its regulation. In the case of viruses, these domains are present in important viral proteins like helicases, nucleases, polymerases, capsid proteins or regulation factors. Therefore, they are implicated in the replicative cycle and parasitic processes of viruses. That is why it is possible to think that those domains present low levels of divergence due to selective pressures. For these reasons, the main goal for this project is to create a catalogue of the RNA-binding domains found in all the available viral proteomes, using bioinformatics tools in order to analyze its evolutionary process, and thus shed light on the general virus evolution. ProDom database was used to obtain larger than six thousand RNA-binding domain families that belong to the three cellular domains of life and some viral groups. From the sequences of these families, protein profiles were created using HMMER 3.1 tools in order to find distant homologous within greater than four thousand viral proteomes available in GenBank. Once accomplished the analysis, almost three thousand hits were obtained in the viral proteomes. The homologous sequences were found in proteomes of the principal Baltimore viral groups, showing interesting distribution patterns that can contribute to understand the evolution of viruses and their host-virus interactions. Presence of cellular RNA-binding domains within virus proteomes seem to be explained by closed interactions between viruses and their hosts. Recruitment of these domains is advantageous for the viral fitness, allowing viruses to be adapted to the host cellular environment.

Keywords: bioinformatics tools, distant homology, RNA-binding domains, viral evolution

Procedia PDF Downloads 387

Authors: Huayun Zhai, Quan Hu, Wei-Chih Chiang, Jianjun Du

Abstract:

By applying experimental methodology in the framework of the behavior-perception theory, this paper studies the relationship between information quality of corporates’ social responsibility (CSR) and individual investors’ risk perception, intermediated with individual investors’ perception on CSR. The findings are as follows: In general, the information quality of CSR significantly influences individual investors’ perception on investment risks. Furthermore, certification on CSR can help reinforce such perceptions. The higher the reporting quality of CSR is, accompanied by the certification by an independent third party, the more likely individual investors recognize the responsibilities. The research also found that the perception on CSR not only plays a role of intermediation between information quality about CSR and investors’ perception on investment risk but also intermediates the certification of CSR reports and individual investors’ judgment on investment risks. The main contributions of the research are in two folds. The first is that it supplements the research on CSR from the perspective of investors’ perceptions. The second is that the research provides theoretical and experimental evidence for enterprises to implement and improve reports on their social responsibilities.

Keywords: information quality, corporate social responsibility, report certification, individual investors’ perception on risk, perception of corporate social responsibility

Procedia PDF Downloads 74

Authors: Mestawot Beyene Tafese, Erika Kopp

Abstract:

Sustainable development, aimed at meeting current needs while safeguarding the needs of future generations, is a global imperative. Higher education stands as a pivotal force in fostering sustainable values and behaviors. However, most scholars and governments primarily focus on environmental and economic aspects. Consequently, this study examines the distribution patterns of higher education for social sustainability. The study highlights overall annual scientific production trends, leading journals and countries in scientific publication, most researched topics, and frequently used keywords. The study utilized a bibliometric method with the aid of the R Studio program. The analysis reveals Sustainability (Switzerland) as the leading journal, with 292 articles published, followed by the International Journal of Sustainability in Higher Education, which published 186 articles. Additionally, the USA is identified as the leading country, with Spain ranking second in producing research related to higher education for socially sustainable development. Among the 54 African countries, only South Africa ranks 13th, contributing fifty-nine scientific articles. Furthermore, higher education for sustainability, sustainable education, sustainable development goals, etc., emerge as the most researched topics, while the term "higher education" is prevalent in 29% and "sustainability" in 28% of the documents. Notably, according to the analysis, social sustainability is the focus of only 3% of articles. This suggests that academics researching sustainable development and higher education have overlooked social sustainability, a crucial human component of sustainable development. Consequently, the researchers concluded that social academics who are interested in studying sustainable development and higher education should give priority to social sustainability.

Keywords: higher education, bibliometric analysis, social sustainability, sustainable development

Procedia PDF Downloads 61

Authors: Yuanjin Liu

Abstract:

Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

Procedia PDF Downloads 74

Authors: Rana I. Abdulghani, Amera I. Melhum

Abstract:

With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

Procedia PDF Downloads 382

Authors: Babar Rasheed

Abstract:

The organizations are in continuous effort to increase their yield and to retain their associates, employees. Technology is considered an integral part of attaining apposite work practices, work environment, and employee engagement. Unconsciously, these advanced practices like work from home, personalized intra-network are disturbing employee work-life balance which ultimately increases psychological pressure on employees. The smart work practice is to develop business models and organizational practices with enhanced employee engagement, minimum trouncing of organization resources with persistent revenue and positive addition in global societies. Need of smart work practices comes from increasing employee turnover rate, global economic recession, unnecessary job pressure, increasing contingent workforce and advancement in technologies. Current practices are not enough elastic to tackle global changing work environment and organizational competitions. Current practices are causing many reciprocal problems among employee and organization mechanically. There is conscious understanding among business sectors smart work practices that will deal with new century challenges with addressing the concerns of relevant issues. It is aimed in this paper to endorse customized and smart work practice tools along knowledge framework to manage the growing concerns of employee engagement, use of technology, orgaization concerns and challenges for the business. This includes a Smart Management Information System to address necessary concerns of employees and combine with a framework to extract the best possible ways to allocate companies resources and re-align only required efforts to adopt the best possible strategy for controlling potential risks.

Keywords: employees engagement, management information system, psychological pressure, current and future HR practices

Procedia PDF Downloads 184

Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

Abstract:

Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

Procedia PDF Downloads 173

Authors: Khulood Miliany

Abstract:

This study examines the media habits of young people in Saudi Arabia, in particular their use of the Internet and television in the domestic sphere, and how use of the Internet impacts upon other activities. In order to address the research questions, focus group interviews were conducted with Saudi university students. The study found that television has become a central part of social life within the household where television represents a main source for family time, particularly in Ramadan while the Internet is a solitary activity where it is used in more private spaces. Furthermore, Saudi females were also more likely to have their Internet access monitored and circumscribed by family members, with parents controlling the location and the amount of time spent using the Internet.

Keywords: domestication of technology, internet, social context, television, young people

Procedia PDF Downloads 300

Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

Abstract:

In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

Procedia PDF Downloads 146

Authors: Mohammed Al-Khadher

Abstract:

Currently, we are witnessing rapid advancements in the field of information and communications technology, forcing us, as psychologists, to combat the psychological and social effects of such developments. It also drives us to continually look for the development and preparation of measurement tools compatible with the changes brought about by the digital revolution. In this context, the current study aimed to identify the factor analysis of the Smartphone Addiction Inventory (SPAI) in the Republic of Yemen. The sample consisted of (1920) university students (1136 males and 784 females) who answered the inventory, and the data was analyzed using the statistical software (AMOS V25). The factor analysis results showed a goodness-of-fit of the data five-factor model with excellent indicators, as RMSEA-(.052), CFI-(.910), GFI-(.931), AGFI-(.915), TLI-(.897), NFI-(.895), RFI-(.880), and RMR-(.032). All within the ideal range to prove the model's fit of the scale’s factor analysis. The confirmatory factor analysis results showed factor loading in (4) items on (Time Spent), (4) items on (Compulsivity), (8) items on (Daily Life Interference), (5) items on (Craving), and (3) items on (Sleep interference); and all standard values of factor loading were statistically significant at the significance level (>.001).

Keywords: smartphone addiction inventory (SPAI), confirmatory factor analysis (CFA), yemeni students, people at risk of smartphone addiction

Procedia PDF Downloads 94

Authors: Rahaf Suleiman Altallaa

Abstract:

City planning involves making plans, organizing and dealing with the cities urban areas. It attempts to organize socio-spatial relationships at exceptional ranges of governance Urban planning offers the social, monetary and environmental effects of defining spatial obstacles and the influence on the spatial distribution of resources. The dreams and methods of reaching such dissemination vary extensively traditionally and geographically and are often challenged through traditional strategies that expose the political nature of application interventions and the bounds of technical know-how claims. Space, network, argument, and postcolonial debates address how present-day socio-spatial organization is formed, what needs to or should not trade, and the way it underscores whether or not a good plan will contribute to a given situation. Inside the absence of an agreed-upon technical justification for the planning exercise, the planning idea has a tendency to focus on normative processes, positioning making plans as an area for participatory democracy.

Keywords: environmental governance, environmental planning, environmental management, sustainable competitiveness, sustainability

Procedia PDF Downloads 122

Authors: Avi Shrivastava

Abstract:

In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

Procedia PDF Downloads 72

Authors: Ruth Gerritsen-McKane, Mimi Sodhi, Lisa Gray, Donette Considine, Henry Kronner, Tameca Harris-Jackson

Abstract:

During these extraordinary times amid a global pandemic, political/civil unrest, and natural disasters, the need for appropriately trained professional social workers has never been stronger. Needs do not diminish but are heightened during such remarkable times. All too often, “developed” countries see the crisis in developing countries as uniquely theirs; 2020 has shown, there are no “others”; there is only us. Consequently, engaging in meaningful collaboration worldwide is essential! This presentation speaks to the fundamentals of global collaboration and, more importantly, how an in these trying times, the development of strong international partnerships can create opportunities for social work students across the planet to engage in meaningful field education opportunities. Accomplished by multiple modalities, a deeper understanding and response to social work students becoming formidable global citizens can be achieved.

Keywords: global citizens, global crisis, global collaboration, modalities

Procedia PDF Downloads 221

Authors: Ethan James

Abstract:

Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 181

Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule

Abstract:

Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.

Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing

Procedia PDF Downloads 139

Authors: Patraporn Kaewkhanitarak, Weerawan Marangkun

Abstract:

The objective of this study was to explore the establishment and to investigate the relationship between the gender (male or female) of SME owner-managers/ entrepreneurs and their risk perception in business activity. The study examines the data by interviewing 76 SME owner-managers/entrepreneurs’ responses (37 males, 39 females) in manufacturing, finance, human resources and marketing sector in the economic regions of Songkhla province, Thailand. This study found that four tools which were operation, cash flow, staff, and new market were perceived by the SME owner-managers/entrepreneurs at high level. However, male and female SME owner-managers/entrepreneurs perceived some factors such as the age of SME owner-managers/entrepreneurs, the duration of firm operation, type of firm, and type of business without significant differences. In contrast, the gender affected the risk perception about increasing cost, fierce competition, leapfrog development of firm, substandard staff, namely that male and female perceived these factors with significant differences. According to the research, SME owner-managers/entrepreneurs should develop their risk management competency to deal with the risk efficiently. Secondly, SME firms should gather into groups. Furthermore, it was shown that the five key tools used to manage these risky situations were the use of managerial competencies and clustering.

Keywords: risk perception, owner-managers/entrepreneurs, SME, Songkhla, Thailand

Procedia PDF Downloads 436

Authors: Ahmadreza Hakiminejad, Changfeng Fu, Hamideh Mohammadzadeh Titkanlou

Abstract:

For decades, sustainable development has been an imperative concern in the process of urban development of the world’s developed countries. Despite the fact that the concept of sustainability, primarily, emerged by virtue of warning over global environmental catastrophes, it subsequently led to the ongoing debates not only over environmental, but also economic and sociocultural issues involved. This study, particularly, discusses the constituents of social sustainability– as one of the three pillars of sustainable development– and its situation within an urban context. It tries to investigate the interrelationships between the elements of social sustainability and the quality of physical environment. The paper, firstly, depicts a theoretical overview of the notions of social sustainability and urban form. Secondly, it will discuss the interrelationship between the two. And lastly, it will investigate and analyse this interrelationship through the historical transformation of Iranian cities. The research aims to answer this very question that how the urban form within the context of the built environment can influence the social behaviors so as to achieve a more sustainable society. It is to examine how and why compact, high-density and mixed-use urban patterns are environmentally sound, efficient for transport, socially beneficial and economically viable. The methodology used in this paper is desk research. Thus, the documents from different urban related disciplines including urban planning, urban design, urban sociology and urban policy have been reviewed. The research has also applied a comparative approach to discuss and analyse the impacts of different urban forms on the elements of social sustainability within the context of modern and traditional Iranian cities. The paper concludes with an examination of possible future directions of Iranian cities with consideration to socio-cultural concepts and the challenges that will have to be overcome to make progress towards social sustainability.

Keywords: social sustainability, urban form, compact city, Iranian cities

Procedia PDF Downloads 411

Authors: Xiao Hu

Abstract:

Children’s social and emotional development is critical for developing their future relationships and behaviors, and poor social skills may result in serious emotional externalizations such as anxiety, distress and aggression. Recent research has emphasized the role of family socio-economic status on children’s emotional development, and this study contributes to this academic discussion by reviewing how socio-economic status affects children at three critical development stages: infancy (0-3months), pre-school (4 months-5 years) and school aged (6-10 years). Results show a consensus in the research literature on a positive relationship between family socio-economic status and children’s emotional development. Socialization, a crucial development milestone, is highly affected by a family’s socio-economic status, as families with higher incomes have access to improved social environments, healthier parenting styles and greater access to social capital and peer support. In contrast, families with lower income and SES (socio-economic status) have lower access to these benefits and are frequently ignored within social environments. This review concludes with a critical discussion on how family income affects children’s social environment, highlighting the important role that “permanent” income plays in children’s development. Consequently, the review suggests that future governments should provide temporary economic support for lower-income families, allowing children to be raised in a healthy social environment with limited economic fluctuation.

Keywords: family socio-economic status, parenting style, children’s emotional development, family permanent income

Procedia PDF Downloads 141

Authors: Arash Khosravi, Mohamad Nazir Ahmad

Abstract:

Today’s economy is a knowledge-based economy in which knowledge is a crucial facilitator to individuals, as well as being an instigator of success. Due to the impact of globalization, universities face new challenges and opportunities. Accordingly, they ought to be more innovative and have their own competitive advantages. One of the most important goals of universities is the promotion of students as professional knowledge workers. Therefore, knowledge sharing and transferring at tertiary level between students and supervisors is vital in universities, as it decreases the budget and provides an affordable way of doing research. Knowledge-sharing impact factors can be categorized into three groups, namely: organizational, individual and technical factors. There are some individual barriers to knowledge sharing, namely: lack of time and trust, lack of communication skills and social networks. IT systems such as e-learning, blogs and portals can increase knowledge sharing capability. However, it must be stated that IT systems are only tools and not solutions. Individuals are still responsible for sharing information and knowledge. This paper proposes new research model to examine the effect of individual factors and organisational factors, namely: learning strategy, trust culture, supervisory support, as well as technological factor on knowledge sharing in a research supervision process at the University of Technology Malaysia.

Keywords: knowledge management, knowledge sharing, research supervision, knowledge transferring

Procedia PDF Downloads 445

Authors: Seyedeh Rozhano Azimi Hashemi

Abstract:

There is no doubt that ‘Art’ is a social phenomena and cinema is the most social kind of art. Hence, it’s clear that we can analyze the relation’s of cinema and art from different aspects. In this paper sociological cinema will be investigated which, is a subdivision of sociological art. This term will be discussed by two main approaches. One of these approaches is focused on the effects of cinema on the society, which is known as “Effects Theory” and the second one, which is dealing with the reflection of social issues in cinema is called ” Reflection Theory”. "Reflect theory" approach, unlike "Effects theory" is considering movies as documents, in which social life is reflected, and by analyzing them, the changes and tendencies of a society are understood. Criticizing these approaches to cinema and society doesn’t mean that they are not real. Conversely, it proves the fact that for better understanding of cinema and society’s relation, more complicated models are required, which should consider two aspects. First, they should be bilinear and they should provide a dynamic and active relation between cinema and society, as for the current concept social life and cinema have bi-linear effects on each other, and that’s how they fit in a dialectic and dynamic process. Second, it should pay attention to the role of inductor elements such as small social institutions, marketing, advertisements, cultural pattern, art’s genres and popular cinema in society. In the current study, image of middle class in cinema of Iran and changing the role of women in cinema and society which were two bold issue that cinema and society faced since 1979 revolution till 80s are analyzed. Films as an artwork on one hand, are reflections of social changes and with their effects on the society on the other hand, are trying to speed up the trends of these changes. Cinema by the illustration of changes in ideologies and approaches in exaggerated ways and through it’s normalizing functions, is preparing the audiences and public opinions for the acceptance of these changes. Consequently, audience takes effect from this process, which is a bi-linear and interactive process.

Keywords: Iranian Cinema, Cinema and Society, Middle Class, Woman’s Role

Procedia PDF Downloads 340

Authors: Julia Rey Perez, Victoria Dominguez Ruiz

Abstract:

The phenomenon of depopulation puts the authorities at risk of abandoning a number of rural-urban areas of significant cultural value, affecting their architecture and intangible cultural heritage. The purpose of this research is to present a methodology created according to the UNESCO Recommendation on the Historic Urban Landscape (HUL), which through the identification of cultural values and attributes, leads to ´Strategic Plans´ build upon the culture and heritage. This methodology is based on the analysis of the town from three perspectives: 1) from the public administration, 2) from the discipline of architecture, and 3) from citizen perception. In order to be able to work on the development of a diagnosis from three very different approaches, collaborative cartographies have been used as working tools. The methodology discussed was applied in Valverde de Burguillos, in Spain, leading to the construction of an inclusive ‘Strategic Plan’ that integrates the management of the town within the overall territorial development plan. The importance of incorporating culture and heritage as a conductor for sustainable urban development through the HUL approach has allowed the local authorities to assume these new tools for heritage conservation, acknowledging community participation as the main element for the ´Strategic Plan” elaboration.

Keywords: rural heritage, citizen participation, inclusiveness, urban governance, UNESCO

Procedia PDF Downloads 139

Authors: Ilef Ketata, Mohamed Khalil Baazaoui, Robert Fromm, Ahmad Fakhfakh, Faouzi Derbel

Abstract:

The integration of wireless communication, e. g. in real-or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, latency, quality of service, and reliability. To minimize the latency without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works. Low-noise amplifiers (LNAs) are introduced to improve the WuRx sensitivity but increase the supply current severely. Different WuRx approaches exist with always-on, power-gated, or duty-cycled receiver designs. This paper presents a comparative study for improving communication range and decreasing the energy consumption of wireless sensor nodes.

Keywords: wireless sensor network, wake-up receiver, duty-cycled, low-noise amplifier, envelope detector, range study

Procedia PDF Downloads 113