Search results for: online learning environments

Authors: Yenisleidy Martinez Martinez, Yannay Casas-Ledon, Jo Dewulf

Abstract:

The ecosystem services (ES) concept has contributed to draw attention to the benefits ecosystems generate for people and how necessary natural resources are for human well-being. The identification and prioritization of the ES constitute the first steps to undertake conservation and valuation initiatives on behalf of people. Additionally, mapping the supply of ES is a powerful tool to support decision making regarding the sustainable management of landscape and natural resources. In this context, the present study aimed to identify, prioritize and map the primary ES in Biobio and Nuble regions using a methodology that combines expert judgment, multi-attribute evaluation methods, and Geographic Information Systems (GIS). Firstly, scores about the capacity of different land use/cover types to supply ES and the importance attributed to each service were obtained from experts and stakeholders via an online survey. Afterward, the ES assessment matrix was constructed, and the weighted linear combination (WLC) method was applied to mapping the overall capacity of supply of provisioning, regulating and maintenance, and cultural services. Finally, prioritized ES for the study area were selected and mapped. The results suggest that native forests, wetlands, and water bodies have the highest supply capacities of ES, while urban and industrial areas and bare areas have a very low supply of services. On the other hand, fourteen out of twenty-nine services were selected by experts and stakeholders as the most relevant for the regions. The spatial distribution of ES has shown that the Andean Range and part of the Coastal Range have the highest ES supply capacity, mostly regulation and maintenance and cultural ES. This performance is related to the presence of native forests, water bodies, and wetlands in those zones. This study provides specific information about the most relevant ES in Biobio and Nuble according to the opinion of local stakeholders and the spatial identification of areas with a high capacity to provide services. These findings could be helpful as a reference by planners and policymakers to develop landscape management strategies oriented to preserve the supply of services in both regions.

Keywords: ecosystem services, expert judgment, mapping, multi-criteria decision making, prioritization

Procedia PDF Downloads 125

Authors: Young Ik Suh, Taewook Chung, Glaucio Scremin, Tywan Martin

Abstract:

In May of 2016, the Philadelphia 76ers announced that StubHub, the ticket resale company, will have advertising on the team’s jerseys beginning in the 2017-18 season. The 76ers and National Basketball Association (NBA) became the first team and league which embraced jersey sponsorships in the four major U.S. professional sports. Even though many professional teams and leagues in Europe, Asia, Africa, and South America have adopted jersey sponsorship actively, this phenomenon is relatively new in America. While the jersey sponsorship provides economic gains for the professional leagues and franchises, sport fans can have different points of view for the phenomenon of jersey sponsorship. For instance, since many sport fans in U.S. are not familiar with ads on jerseys, this movement can possibly cause negative reaction such as the decrease in ticket and merchandise sales. They also concern the small size of ads on jersey become bigger ads, like in the English Premier League (EPL). However, some sport fans seem they do not mind too much about jersey sponsorship because the ads on jersey will not affect their loyalty and fanship. Therefore, the assumption of this study was that the sport fans’ reaction about jersey sponsorship can be possibly different, especially based on different levels of the sport fans’ team identification and various sizes of ads on jersey. Unlike general sponsorship in sport industry, jersey sponsorship has received little attention regarding its potential impact on sport fans attitudes and buying intentions. Thus, the current study sought to identify how the various levels of team identification influence brand attitude and buying intention in terms of jersey sponsorship. In particular, this study examined the effect of team identification on brand attitude and buying intention when there are no ads, small size ads, and large size ads on jersey. 3 (large, small, and no ads) X 3 (Team Identification: high, moderate, low) between subject factorial design was conducted on attitude toward the brand and buying intention of jersey sponsorship. The ads on Philadelphia 76ers jersey were used. The sample of this study was selected from message board users provided by different sports websites (i.e., forums.realgm.com and phillysportscentral.com). A total of 275 respondents participated in this study by responding to an online survey questionnaire. The results showed that there were significant differences between fans with high identification and fans with low identification. The findings of this study are expected to have many theoretical and practical contributions and implications by extending the research and literature pertaining to the relationship between team identification and brand strategy based upon different levels of team identification.

Keywords: brand attitude, buying intention, Jersey sponsorship, team identification

Procedia PDF Downloads 247

Authors: Kholod J. Alotaibi, Andrew M. Gravell

Abstract:

A study was conducted in which 212 software developers in higher education institutions in Saudi Arabia were surveyed to gather an indication of their understanding of the concept of usability, their acceptance of its importance, and to see how well its principles are applied. Interviews were then held with 20 of these developers, and a demonstration of Usage-Centred Design was attempted, a highly usability focused software development methodology, at one select institution for its redesign of an e-learning exam system interface during the requirements gathering phase. The study confirms the need to raise awareness of usability and its importance, and for Usage-Centred Design to be applied in its entirety, also need to encourage greater consultation with potential end-users of software and collaborative practices. The demonstration of Usage-Centred Design confirmed its ability to capture usability requirements more completely and precisely than would otherwise be the case, and hence its usefulness for developers concerned with improving software usability. The concluding discussion delves on the challenges for promoting usability and Usage-Centred Design in light of the research results and findings and recommendations are made for the same.

Keywords: usability, usage-centred, applying principles of usage-centred, Saudi Arabia

Procedia PDF Downloads 391

Authors: Aikaterini-Melpomeni Papadopoulou, Kyriaki Apergi, Margarita-Vasiliki Panagopoulou, Olga Malisova

Abstract:

Introduction: Adequate hydration is a vital factor that enhances concentration, memory, and decision-making abilities throughout the workday. Various factors may affect hydration status in workplace settings, and many variables, such as age, gender and activity level affect hydration needs. Employees frequently overlook their hydration needs amid busy schedules and demanding tasks, leading to dehydration that can negatively affect cognitive function, productivity, and overall well-being In addition, dietary habits, including fluid intake and food choices, can either support or hinder optimal hydration. However, factors that affect hydration balance among workers in Greece have not been adequately studied. Objective: This study aims to evaluate the hydration status of the working population in Greece and investigate the various factors that impact hydration status in workplace settings, considering demographic, dietary, and occupational influences in a Greek sample of employees from diverse working environments Materials & Methods: The study included 212 participants (46.2% women) from the working population in Greece. Water intake from both solid and liquid foods was recorded using a semi-quantified drinking frequency questionnaire the validated Water Balance Questionnaire was used to evaluate hydration status. The calculation of water from solid and liquid foods was based on data from the USDA National Nutrient Database. Water balance was calculated subtracting the total fluid loss from the total fluid intake in the body. Furthermore, the questionnaire including additional questions on drinking habits and work-related factors.volunteers answered questions of different categories such as a) demographic socio-economic b) work style characteristics c) health, d) physical activity, e) food and fluid intake, f) fluid excretion and g) trends on fluid and water intake. Individual and multivariate regression analyses were performed to assess the relationships between demographic, work-related factors, and hydration balance. Results: Analysis showed that demographic factors like gender, age, and BMI, as well as certain work-related factors, had a weak and statistically non-significant effect on hydration balance. However, the use of a bottle or water container during work hours (b = 944.93, p < 0.001) and engaging in intense physical activity outside of work (b = -226.28, p < 0.001) were found to have a significant impact. Additionally, the consumption of beverages other than water (b = -416.14, p = 0.059) could negatively impact hydration balance. On average, the total consumption of the sample is 3410 ml of water daily, with men consuming approximately 440 ml / day more water (3470 ml / day) compared to women (3030 ml / day) with this difference also being statistically significant. Finally, the water balance, defined as the difference between water intake and water excretion, was found to be negative on average for the entire sample. Conclusions: This study is among the first to explore hydration status within the Greek working population. Findings indicate that awareness of adequate hydration and individual actions, such as using a water bottle during work, may influence hydration balance.

Keywords: hydration, working population, water balance, workplace behavior

Procedia PDF Downloads 5

Authors: S. Nickolas, Shobha K.

Abstract:

The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 274

Authors: Shiau-Fang Chao, Yu-Chih Chen

Abstract:

Owing to physical limitations and restrained lifestyle, older long-term care (LTC) residents are more likely to be affected by their environment than their community-dwelling counterparts. They also participate fewer activities and experience worse mental health than healthy older adults. This study adopts the ICF model to determine the extent to which the clustered patterns of LTC environment and activity participation are associated with older residents’ mental health. Method: Data were collected from a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis (LPA) and latent class analysis (LCA) were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the relationships among environment profiles, activity profiles, and mental health. Results: LPA identified three mutually exclusive environment profiles (Low-, Moderate-, and High-Support Environment) based on the physical, social, and attitudinal environmental domains, consolidated from 12 environmental measures. LCA constructed two distinct activity profiles (Low- and High-Activity Participation) across seven activity domains (outdoor, volunteer-led leisure, spiritual, household chores, interpersonal exchange, social, and sedentary activity) that were factored from 20 activities. Compared to the Low-Support Environment class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in the Moderate- and High-Support Environment classes were more likely to be in the “High Activity” class, which in turn, exhibited better mental health. Conclusion: This study advances the current knowledge through rigorous methods and study design. The study findings lead to several conclusions. First, this study supports the use of ICF framework to institutionalized older individuals with functional limitations and demonstrates that both measures of environment and activity participation can be refined from multiple indicators. Second, environmental measures that encompass the physical, social, and attitudinal domains would provide a more comprehensive assessment on the place where an older individual embeds. Third, simply counting activities in which an older individual participates or considering a certain type of activity may not capture his or her way of life. Practitioners should not only focus on group or leisure activities within the institutions; rather, more efforts should be made to consider residents’ preferences for everyday life and support their remaining ability by encouraging continuous participation in activities they still willing and capable to perform. Fourth, environment and activity participation are modifiable factors which have greater potential to strengthen older LTC residents’ mental health, and activity participation should be considered in the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.

Keywords: activity, environment, mental health, older LTC residents

Procedia PDF Downloads 197

Authors: Afnan Al-Romi, Iman Al-Momani

Abstract:

The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

Procedia PDF Downloads 322

Authors: David Gottlieb, Jason Yoder

Abstract:

The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

Procedia PDF Downloads 94

Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

Procedia PDF Downloads 111

Authors: K. C. Wong

Abstract:

This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

Procedia PDF Downloads 141

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

Procedia PDF Downloads 400

Authors: Ravi Kant Anand, Nikkey Keshri

Abstract:

The Great Barrier Reef of Australia is known for its beautiful landscapes and seascapes with ecological importance. This site was selected as a World Heritage site in 1981 and popularized internationally for tourism, recreational activities and fishing. But the major environmental hazards such as climate change, pollution, overfishing and shipping are making worst the site of marine ecosystem. Climate change is directly hitting on Great Barrier Reef through increasing level of sea, acidification of ocean, increasing in temperature, uneven precipitation, changes in the El Nino and increasing level of cyclones and storms. Apart from that pollution is second biggest factor which vanishing the coral reef ecosystem. Pollution including over increasement of pesticides and chemicals, eutrophication, pollution through mining, sediment runoff, loss of coastal wetland and oil spills. Coral bleaching is the biggest problem because of the environmental threatening agents. Acidification of ocean water reduced the formation of calcium carbonate skeleton. The floral ecosystem (including sea grasses and mangroves) of ocean water is the key source of food for fishes and other faunal organisms but the powerful waves, extreme temperature, destructive storms and river run- off causing the threat for them. If one natural system is under threat, it means the whole marine food web is affected from algae to whale. Poisoning of marine water through different polluting agents have been affecting the production of corals, breeding of fishes, weakening of marine health and increased in death of fishes and corals. In lieu of World Heritage site, tourism sector is directly affected and causing increasement in unemployment. Fishing sector also affected. Fluctuation in the temperature of ocean water affects the production of corals because it needs desolate place, proper sunlight and temperature up to 21 degree centigrade. But storms, El Nino, rise in temperature and sea level are induced for continuous reduction of the coral production. If we do not restrict the environmental problems of Great Barrier Reef than the best known ecological beauty with coral reefs, pelagic environments, algal meadows, coasts and estuaries, mangroves forests and sea grasses, fish species, coral gardens and the one of the best tourist spots will lost in upcoming years. My research will focus on the different environmental threats, its socio-economic impacts and different conservative measures.

Keywords: climate change, overfishing, acidification, eutrophication

Procedia PDF Downloads 373

Authors: Elias Nemer, Greg Vines

Abstract:

Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

Procedia PDF Downloads 233

Authors: Frederic Jumelle, Kelvin So, Didan Deng

Abstract:

In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

Procedia PDF Downloads 123

Authors: Joann Douziech

Abstract:

Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

Procedia PDF Downloads 66

Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

Abstract:

Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

Procedia PDF Downloads 205

Authors: Nady Farag Faragalla Hanna

Abstract:

In the car dealership industry in Japan, the sales specialist is a key factor in the success of the company. I hypothesize that when a company understands the characteristics of sales professionals in its industry, it is easier to recruit and train salespeople effectively. Lean human resources management ensures the economic success and performance of companies, especially small and medium-sized companies.The purpose of the article is to determine the characteristics of sales specialists for small and medium-sized car dealerships using the chi-square test and the proximate variable model. Accordingly, the results show that career change experience, learning ability and product knowledge are important, while university education, career building through internal transfer, leadership experience and people development are not important for becoming a sales professional. I also show that the characteristics of sales specialists are perseverance, humility, improvisation and passion for business.

Keywords: electronics engineering, marketing, sales, E-commerce digitalization, interactive systems, sales process ARIMA models, sales demand forecasting, time series, R codetraits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

Procedia PDF Downloads 51

Authors: Agne Jucyte Cicine, Vytautas Abromaitis, Zita Rasuole Gasiunaite, I. Vybernaite-Lubiene, D. Overlinge, K. Vilke

Abstract:

Pharmaceutical pollution in aquatic environments has become a growing concern. Various active pharmaceutical ingredient (API) residues, hormones, antibiotics, or/and psychiatric drugs, have already been discovered in different environmental compartments. Due to existing ineffective wastewater treatment technologies to remove APIs, an underestimated amount can enter the ecosystem by discharged treated wastewater. Especially, psychiatric compounds, such as carbamazepine (CBZ) and venlafaxine (VNX), persist in effluent even post-treatment. Therefore, these pharmaceuticals usually exceed safe environmental levels and pose risks to the aquatic environment, particularly to sensitive ecosystems such as the Baltic Sea. CBZ, known for its chemical stability and long biodegradation time, accumulates in the environment, threatening aquatic life and human health through the food chain. As the use of medication rises, there is an urgent need for advanced wastewater treatment to reduce pharmaceutical contamination and meet future regulatory requirements. In this study, we tested advanced oxidation technology using ozone to remove two commonly used psychiatric drugs (carbamazepine and venlafaxine) from biologically treated wastewater effluent. Additionally, general water quality parameters (suspended matter (SPM), dissolved organic carbon (DOC), chemical oxygen demand (COD), and bacterial presence were analyzed. Three wastewater treatment plants (WWTPs) representing different anthropogenic pressures were selected: 1) resort, 2) resort and residential, and 3) residential, industrial, and resort. Wastewater samples for the experiment were collected during the summer season after mechanical and biological treatment and ozonated for 5, 10, and 15 minutes. The initial dissolved ozone concentration of 7,3±0,7 mg/L was held constant during all the experiments. Pharmaceutical levels in this study exceeded the predicted no-effect concentration (PNEC) of 500 and 90 ng L⁻¹ for CBZ and VNX, respectively, in all WWTPs, except CBZ in WWTP 1. Initial CBZ contamination was found to be lower in WWTP 1 (427.4 ng L⁻¹), compared with WWTP 2 (1266.5 ng L⁻¹) and 3 (119.2 ng L⁻¹). VNX followed a similar trend with concentrations of 341.2 ng L⁻¹, 361.4 ng L⁻¹, and 390.0 ng L⁻¹, respectively, for WWTPs 1, 2, and 3. It was determined that CBZ was not detected in the effluent after 5 minutes of ozonation in any of the WWTPs. Contrarily, VNX was still detected after 5, 10, and 15 minutes of treatment with ozone, however, under the limits of quantification (LOD) (<5ng L⁻¹). Additionally, general pollution of SPM, DOC, COD, and bacterial contamination was reduced notably after 5 minutes of treatment with ozone, while no bacterial growth was obtained. Although initial pharmaceutical levels exceeded PNECs, indicating ongoing environmental risks, ozonation demonstrated high efficiency in reducing pharmaceutical and general contamination in wastewater with different pollution matrices.

Keywords: Baltic Sea, ozonation, pharmaceuticals, wastewater treatment plants

Procedia PDF Downloads 19

Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

Abstract:

In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

Procedia PDF Downloads 469

Authors: Ovidiu Domşa, Nicolae Bold

Abstract:

Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

Procedia PDF Downloads 324

Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

Procedia PDF Downloads 101

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

Procedia PDF Downloads 37

Authors: Deepika Christopher, Garima Anand

Abstract:

To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

Procedia PDF Downloads 56

Authors: Vahid Bayrami Rad

Abstract:

In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

Procedia PDF Downloads 52

Authors: Lee Bih Ni, Kiu Su Na

Abstract:

This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.

Keywords: a second language, Chinese language teaching, immersion teaching, instructional strategies

Procedia PDF Downloads 450

Authors: Leah Plocharczyk, Matthew Conner

Abstract:

This paper analyzes the relatively new trend of PSE programs which seek to provide education, vocational training, and a college experience to individuals with an intellectual and developmental disability (IDD). Specifically, the paper examines the degree of interaction between PSE programs and the libraries of their college campuses. Using ThinkCollege, a clearinghouse and advocate for PSE programs, the researchers identified 293 programs throughout the country. These were all contacted with an email survey asking them about the nature of their involvement, if any, with the academic libraries on their campus. Where indicated by the responses, the libraries of PSE programs were contacted for additional information about their programming. Responses to the survey questions were tabulated and analyzed quantitatively. Written comments were analyzed for themes which were then tabulated. This paper presents the results of this study. They show obvious preferences for library programming, such as group formal instruction, individual liaisons, embedded reference, and various instructional designs. These are discussed in terms of special education principles of mainstreaming, level of restriction, training demands and cost effectiveness. The work serves as a foundation for best practices that can advance the field.

Keywords: disability studies, instructional design, universal design for learning, assessment methodology

Procedia PDF Downloads 68

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

Procedia PDF Downloads 83

Authors: Tahsina Sadeque Kapil Ahmed

Abstract:

Context: The tobacco epidemic is one of the biggest public health threats the world has ever faced. Tobacco use is a widespread phenomenon in Bangladesh, and that causes numerous deaths and disabilities in a year. The studies conducted elsewhere have strengthened the evidence that mass media campaigns conducted in the context of comprehensive tobacco control programs can promote quitting and reduce smoking, as well as smokeless tobacco prevalence. Awareness building campaigns in mass-media against tobacco use should be prioritized more, and this paper will be an initiative towards enhancing mass-media’s role in controlling tobacco in Bangladesh. Objective: the main objective of this study is to investigate the role of mass-media in controlling tobacco in Bangladesh. Methods: This is a qualitative study and both primary, as well as secondary data were used where information gathered through the Key Informant Interviews (KIIs) and media contents. The employees of media houses (five national papers, two online news portals and six TV channels) were selected as study respondent. Media Content Analysis is used through the broad range of ‘texts’ from transcripts of interviews and discussions along with the materials like reports, footages, advertisements, talk-shows, articles etc. Results: The study result documented several opinions of discussants where Mass media was found to play a strong role in support of the amended tobacco control law and its implication that could be created public support against tobacco farming, exposing to companies’ tactics and other tobacco control activities. The study results also revealed that in controlling tobacco supply and demand effectively, media has been assisting the government and anti-tobacco activities productively. Majority of the Key Informants opined spontaneously on tobacco control program publicity, organizational interference, and influence of other activities on media. They also emphasized role of media for activities of anti-tobacco organizations, awareness building actions, popularization of tobacco control law and its amendment. Conclusion and Recommendation: The study shows evidence that mass media coverage of tobacco control issues is influencing the context of comprehensive tobacco control programs. To reduce tobacco consumption, along with strict enforcement efforts, media should be used to assist with the implementation of the tobacco control law. A sustained nationwide campaign to educate the masses against the dangers of smoking and smokeless tobacco is needed, and media can play an important role in creating further awareness about the dangers associated with tobacco consumption.

Keywords: Bangladesh media, mass media, role of media, tobacco control

Procedia PDF Downloads 212

Authors: Douglas Shabe

Abstract:

The world of the performing musician is one of high pressure that comes from the expected high standards they have to live up to and that they expect from themselves. The pressure that musicians put themselves under can manifest itself in physical problems such as focal dystonia. Knowledge of the contributing factors and potential rehabilitation strategies cannot only give players hope for recovery but also the information to prevent it from happening in the first place. This dissertation presents a multiple case study of two performing brass musicians who developed focal dystonia of the embouchure, also known as embouchure dystonia, combined with an autoethnography of the author’s experience of battling embouchure dystonia and our attempts at recovery. Extensive research into the current state of focal dystonia research was done to establish a base of knowledge. That knowledge was used to develop interview questions for the two participants and interpret the findings of the qualitative data collected. The research knowledge, as well as the qualitative data from the case studies, was also used to interpret the author’s experience. The author determined that behavioral, environmental, and psychological factors were of prime importance in the subjects’ development of focal dystonia and that modifications of those factors are essential for the best chance at recovery.

Keywords: focal dystonia, embouchure dystonia, music teaching and learning, music education

Procedia PDF Downloads 83

Authors: Raphael Palucci Rosa, Giuseppe Rosace

Abstract:

Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

Procedia PDF Downloads 126