Search results for: cloud radio access network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8438

Search results for: cloud radio access network

2678 Estimating Occupancy in Residential Context Using Bayesian Networks for Energy Management

Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

Abstract:

A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

Procedia PDF Downloads 357
2677 Big Data and Cardiovascular Healthcare Management: Recent Advances, Future Potential and Pitfalls

Authors: Maariyah Irfan

Abstract:

Intro: Current cardiovascular (CV) care faces challenges such as low budgets and high hospital admission rates. This review aims to evaluate Big Data in CV healthcare management through the use of wearable devices in atrial fibrillation (AF) detection. AF may present intermittently, thus it is difficult for a healthcare professional to capture and diagnose a symptomatic rhythm. Methods: The iRhythm ZioPatch, AliveCor portable electrocardiogram (ECG), and Apple Watch were chosen for review due to their involvement in controlled clinical trials, and their integration with smartphones. The cost-effectiveness and AF detection of these devices were compared against the 12-lead ambulatory ECG (Holter monitor) that the NHS currently employs for the detection of AF. Results: The Zio patch was found to detect more arrhythmic events than the Holter monitor over a 2-week period. When patients presented to the emergency department with palpitations, AliveCor portable ECGs detected 6-fold more symptomatic events compared to the standard care group over 3-months. Based off preliminary results from the Apple Heart Study, only 0.5% of participants received irregular pulse notifications from the Apple Watch. Discussion: The Zio Patch and AliveCor devices have promising potential to be implemented into the standard duty of care offered by the NHS as they compare well to current routine measures. Nonetheless, companies must address the discrepancy between their target population and current consumers as those that could benefit the most from the innovation may be left out due to cost and access.

Keywords: atrial fibrillation, big data, cardiovascular healthcare management, wearable devices

Procedia PDF Downloads 122
2676 ICT-Driven Cataloguing and Classification Practical Classes: Perception of Nigerian Library and Information Science Students on Motivational Factors

Authors: Abdulsalam Abiodun Salman, Abdulmumin Isah

Abstract:

The study investigated the motivational factors that could enhance the teaching and understanding of ICT-driven cataloguing and classification (Cat and Class) practical classes among students of library and information science (LIS) in Kwara State Library Schools, Nigeria. It deployed a positivist research paradigm using a quantitative method by deploying the use of questionnaires for data collection. The population of the study is one thousand, one hundred and twenty-five (1,125) which was obtained from the department of each respective library school (the University of Ilorin, Ilorin (Unilorin); Federal Polytechnic Offa, (Fedpoffa); and Kwara State University (KWASU). The sample size was determined using the research advisor table. Hence, the study sample of one hundred and ten (110) was used. The findings revealed that LIS students were averagely motivated toward ICT-driven Cataloguing and Classification practical classes. The study recommended that modern cataloguing and classification tools for practical classes should be made available in the laboratories as motivational incentives for students. It was also recommended that library schools should motivate the students beyond the provision of these ICT-driven tools but also extend the practical class periods. Availability and access to medical treatment in case of injuries during the practical classes should be made available. Technologists/Tutors of Cat and Class practical classes should also be exposed to further training in modern trends, especially emerging digital knowledge and skills in cataloguing and classification. This will keep both the tutors and students abreast of the new development in the technological arena.

Keywords: cataloguing and classification, motivational factors, ICT-driven practical classes, LIS students, Nigeria

Procedia PDF Downloads 114
2675 Fitness Apparel and Body Cathexis of Women Consumers When and after Using Virtual Fitting Room

Authors: Almas Athif Fathin Wiyantoro, Fransiskus Xaverius Ivan Budiman, Fithra Faisal Hastiadi

Abstract:

The growth of clothing and technology as a marketing tool has a great influence on online business owners to know how much the characteristics and psychology of consumers in influencing purchasing decisions made by Indonesian women consumers. One of the most important issues faced by Indonesian women consumers is the suitability of clothing. The suitability of clothing can affect the body cathexis, identity, and confidence. So the thematic analysis of clothing fitness and body cathexis of women consumers when and after using virtual fitting room technology to purchase decision is important to do. This research using group method of pre-post treatment and considers how the recruitment technique of snowball sampling, which uses interpersonal relations and connections between people, both includes and excludes individuals into 39 participants' social networks to access specific populations. The results obtained from the study that the results of body scans and photos of virtual fitting room results can be made an intervention in women consumers in assessing their body cathexis objectively in the process of making purchasing decisions. The study also obtained a regression equation Y = 0.830 + 0.290X1 + 0.292X2, showing a positive relationship between suitability of clothing and body cathexis which influenced purchasing decisions on women consumers and after (personal and psychological factors) using virtual fitting room, meaning that all independent variables influence Positive towards the purchasing decision of the women consumers.

Keywords: body cathexis, clothing fitness, purchasing decision making and virtual fitting room

Procedia PDF Downloads 196
2674 Traffic Accident Risk Assessment on National Roads: A Case Study in East Aceh Regency

Authors: Muksalmina

Abstract:

Transportation plays an important role in people's daily activities but is often marred by traffic accidents. In Indonesia, traffic accidents are the third leading cause of death after coronary heart disease and tuberculosis, according to the World Health Organization (2013). Several roads in East Aceh District are strategic access points for economic growth in the Aceh region. There were 446 traffic accidents in 2023, which is the highest case in the last five years. This study aims to analyze black spot locations on national roads in East Aceh District and evaluate road safety deficiencies in the area. The research methodology began by selecting the locations with the highest accident rates based on data from East Aceh Police from 2019-2023. Next, Average Daily Traffic (ADT) was measured by projecting population growth data. The analysis of road safety deficiencies included measurements of road geometrics, traffic signs and markings, and traffic volumes at black spot locations. The study results showed deficiencies in lane width, shoulder width, and inadequate road safety facilities at several locations. Recommendations for improvements include increasing lane and shoulder widths and adding signs and markings to improve safety. This study is expected to serve as a reference for the government and relevant stakeholders in improving traffic safety in East Aceh District.

Keywords: black spot, traffic accident, severity index, road safety

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2673 Key Challenges Facing the Management of Archaeological and Tourism Sites in Jordan

Authors: Muna Slehat

Abstract:

Jordan is endowed with over 14,500 productive archaeological sites and also a wealth of heritage sites that need to be protected from the pressing threat of destruction and damage. Archaeological sites in Jordan face significant threats, including insensitive development, urbanization, pollution, tourism, and vandalism, therefore an effective management plan is a key element, not only for the conservation of this heritage, but also to address issues such as tourism and sustainable development. This study highlights the obstacles that confront the management of the archaeological and tourism sites in Jordan, prior to and after the launch of the Strategies for Management of Jordan’s Archaeological Heritage by the Department of Antiquities (DoA) 2007-2010 and 2014-2018, as well as the establishment of the Directorate of the Management of Archaeological Sites in 2010, and instructions for the proper use of tourism sites, 2014, by the Ministry of Tourism and Antiquities (MoTA). The study has revealed that the management of the archaeological and tourism sites under the pretext of improvement of services for tourists and visitors to Jordan would allow access to so-called polarization tourism and facilitate tourism development that would be sustainable economically and provide attractive returns. The data required have been collected through conducting interviews with 18 specialists. The main findings of the study are that management is new in Jordan, and has become a vital and dynamic force in Jordan after 2000 but that there have also been many mistakes, with sustainability of the sites being ignored and a lack of awareness among local communities surrounding these sites. Management of the sites has also suffered from a lack of organizational vision, with no instructions for practical application and no legislative provisions which cater for the efficient management of the sites. All of this needs to be amended to remove gaps, overlaps and ambiguities, so that the authorities responsible for the rehabilitation and promotion, development and management of these sites can overcome the problems, such as lack of human resources (specialists) and financial resources.

Keywords: Jordan, management, archaeological sites, tourism, challenges

Procedia PDF Downloads 285
2672 Multi-Level Attentional Network for Aspect-Based Sentiment Analysis

Authors: Xinyuan Liu, Xiaojun Jing, Yuan He, Junsheng Mu

Abstract:

Aspect-based Sentiment Analysis (ABSA) has attracted much attention due to its capacity to determine the sentiment polarity of the certain aspect in a sentence. In previous works, great significance of the interaction between aspect and sentence has been exhibited in ABSA. In consequence, a Multi-Level Attentional Networks (MLAN) is proposed. MLAN consists of four parts: Embedding Layer, Encoding Layer, Multi-Level Attentional (MLA) Layers and Final Prediction Layer. Among these parts, MLA Layers including Aspect Level Attentional (ALA) Layer and Interactive Attentional (ILA) Layer is the innovation of MLAN, whose function is to focus on the important information and obtain multiple levels’ attentional weighted representation of aspect and sentence. In the experiments, MLAN is compared with classical TD-LSTM, MemNet, RAM, ATAE-LSTM, IAN, AOA, LCR-Rot and AEN-GloVe on SemEval 2014 Dataset. The experimental results show that MLAN outperforms those state-of-the-art models greatly. And in case study, the works of ALA Layer and ILA Layer have been proven to be effective and interpretable.

Keywords: deep learning, aspect-based sentiment analysis, attention, natural language processing

Procedia PDF Downloads 124
2671 A Case Study on Indian Translation Ecosystem of Point-Of-Care Solutions

Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

Abstract:

The translation of healthcare technologies is an expensive, complex affair, current healthcare challenges in Asian countries and their efforts to meet Millennium Development Goals (MDGs), necessitates continuous technology advancement to save countless lives, improve the quality of life and for socio-economic development. India’s consistently improving global innovation index (57) demonstrates its innovation potential, but access to health care is asymmetric and lacks priority in India. Therefore, there is utmost need of a robust translation system for point-of-care (POC) solutions, inexpensive, low-maintenance, reliable, and easy-to-use diagnostic technologies. Few cases of POC technologies viz. Elisa based diagnostic kits for regional viral disease, a device for detection of cancerous lesions were studied to understand the process and challenges involved in their translation. Accordingly, the entire translation ecosystem was summarized proposing a nexus of various actors such as technology developer, technology transferor technology receiver, funding entities, government/regulatory bodies and their effect on translation of different medical technologies. This study highlights the role and concerns pertaining to these actors for POC such as unsystematic and unvalidated research roadmap, low profit preposition, unfocused approach of up-scaling, low market acceptability and multiple window regulatory framework, etc. This provides an opportunity to devise solutions to overcome problem areas in translation path.

Keywords: healthcare technologies, point-of-care solutions, public health, translation

Procedia PDF Downloads 159
2670 Temperature Dependence of Relative Permittivity: A Measurement Technique Using Split Ring Resonators

Authors: Sreedevi P. Chakyar, Jolly Andrews, V. P. Joseph

Abstract:

A compact method for measuring the relative permittivity of a dielectric material at different temperatures using a single circular Split Ring Resonator (SRR) metamaterial unit working as a test probe is presented in this paper. The dielectric constant of a material is dependent upon its temperature and the LC resonance of the SRR depends on its dielectric environment. Hence, the temperature of the dielectric material in contact with the resonator influences its resonant frequency. A single SRR placed between transmitting and receiving probes connected to a Vector Network Analyser (VNA) is used as a test probe. The dependence of temperature between 30 oC and 60 oC on resonant frequency of SRR is analysed. Relative permittivities ‘ε’ of test samples for different temperatures are extracted from a calibration graph drawn between the relative permittivity of samples of known dielectric constant and their corresponding resonant frequencies. This method is found to be an easy and efficient technique for analysing the temperature dependent permittivity of different materials.

Keywords: metamaterials, negative permeability, permittivity measurement techniques, split ring resonators, temperature dependent dielectric constant

Procedia PDF Downloads 391
2669 Study on the Spatial Vitality of Waterfront Rail Transit Station Area: A Case Study of Main Urban Area in Chongqing

Authors: Lianxue Shi

Abstract:

Urban waterfront rail transit stations exert a dual impact on both the waterfront and the transit station, resulting in a concentration of development elements in the surrounding space. In order to more effectively develop the space around the station, this study focuses on the perspective of the integration of station, city, and people. Taking Chongqing as an example, based on the Arc GIS platform, it explores the vitality of the site from the three dimensions of crowd activity heat, space facilities heat, and spatial accessibility. It conducts a comprehensive evaluation and interpretation of the vitality surrounding the waterfront rail transit station area in Chongqing. The study found that (1) the spatial vitality in the vicinity of waterfront rail transit stations is correlated with the waterfront's functional zoning and the intensity of development. Stations situated in waterfront residential and public spaces are more likely to experience a convergence of people, whereas those located in waterfront industrial areas exhibit lower levels of vitality. (2) Effective transportation accessibility plays a pivotal role in maintaining a steady flow of passengers and facilitating their movement. However, the three-dimensionality of urban space in mountainous regions is a notable challenge, leading to some stations experiencing limited accessibility. This underscores the importance of enhancing the optimization of walking space, particularly the access routes from the station to the waterfront area. (3) The density of spatial facilities around waterfront stations in old urban areas lags behind the population's needs, indicating a need to strengthen the allocation of relevant land and resources in these areas.

Keywords: rail transit station, waterfront, influence area, spatial vitality, urban vitality

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2668 A Literature Review on the Barriers in Incorporating Universal Design in Public Transportation Projects: Southeast Asian Countries

Authors: Oscar Conrad Pili De Jesus

Abstract:

In consonance with the UN Convention on Rights for People with Disabilities, countries are mandated to provide a barrier-free environment through adherence to universal design and full participation of persons with disabilities (PWDs) in planning and implementation, but there is little action in incorporating universal design in the public environment. Travelling freely and independently is paramount to the needs of the PWDs to participate in daily activities ahead of them, and it contributes to the advancement of their inclusion in society, in which universal design is a catalyst to provide seamless access and mobility. This study aims to determine the barriers to incorporating the concept of universal design in transportation projects in Southeast Asian countries. Based on a literature review and using the accessible journey chain as a framework, barriers are identified and categorized in the components of public transport within the context of utilization of the transport mode, the built environment within the transport infrastructure, and the first and last miles of travel. Some findings in the study which constitute solutions to creating a barrier-free environment were identified as information to guide the future research agenda in efficiently incorporating universal design in transportation projects in Southeast Asian countries. The study reflected that the focus of most literature is on the built environment, noting that there is a need for future studies to investigate universal design in the context of the public transport component in the active journey chain.

Keywords: public transportation, barriers, universal design, persons with disabilities, accessible journey chain

Procedia PDF Downloads 117
2667 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification

Authors: Anita Kushwaha

Abstract:

We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

Procedia PDF Downloads 256
2666 The Using of Liquefied Petroleum Gas (LPG) on a Low Heat Loss Si Engine

Authors: Hanbey Hazar, Hakan Gul

Abstract:

In this study, Thermal Barrier Coating (TBC) application is performed in order to reduce the engine emissions. Piston, exhaust, and intake valves of a single-cylinder four-cycle gasoline engine were coated with chromium carbide (Cr3C2) at a thickness of 300 µm by using the Plasma Spray coating method which is a TBC method. Gasoline engine was converted into an LPG system. The study was conducted in 4 stages. In the first stage, the piston, exhaust, and intake valves of the gasoline engine were coated with Cr3C2. In the second stage, gasoline engine was converted into the LPG system and the emission values in this engine were recorded. In the third stage, the experiments were repeated under the same conditions with a standard (uncoated) engine and the results were recorded. In the fourth stage, data obtained from both engines were loaded on Artificial Neural Networks (ANN) and estimated values were produced for every revolution. Thus, mathematical modeling of coated and uncoated engines was performed by using ANN. While there was a slight increase in exhaust gas temperature (EGT) of LPG engine due to TBC, carbon monoxide (CO) values decreased.

Keywords: LPG fuel, thermal barrier coating, artificial neural network, mathematical modelling

Procedia PDF Downloads 414
2665 Analyzing Factors Impacting COVID-19 Vaccination Rates

Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

Abstract:

Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated its population within its first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. The results of these correlations identify countries with stronger health indicators, such as lower mortality rates, lower age dependency ratios, and higher rates of immunization to other diseases, displaying higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: data mining, Pearson correlation, COVID-19, vaccination rates and hesitancy

Procedia PDF Downloads 99
2664 Performance Analysis of Elliptic Curve Cryptography Using Onion Routing to Enhance the Privacy and Anonymity in Grid Computing

Authors: H. Parveen Begam, M. A. Maluk Mohamed

Abstract:

Grid computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using Virtual Organization (VO). Security is a critical issue due to the open nature of the wireless channels in the grid computing which requires three fundamental services: authentication, authorization, and encryption. The privacy and anonymity are considered as an important factor while communicating over publicly spanned network like web. To ensure a high level of security we explored an extension of onion routing, which has been used with dynamic token exchange along with protection of privacy and anonymity of individual identity. To improve the performance of encrypting the layers, the elliptic curve cryptography is used. Compared to traditional cryptosystems like RSA (Rivest-Shamir-Adelman), ECC (Elliptic Curve Cryptosystem) offers equivalent security with smaller key sizes which result in faster computations, lower power consumption, as well as memory and bandwidth savings. This paper presents the estimation of the performance improvements of onion routing using ECC as well as the comparison graph between performance level of RSA and ECC.

Keywords: grid computing, privacy, anonymity, onion routing, ECC, RSA

Procedia PDF Downloads 384
2663 Identification and Prioritisation of Students Requiring Literacy Intervention and Subsequent Communication with Key Stakeholders

Authors: Emilie Zimet

Abstract:

During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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2662 Chronic Cognitive Impacts of Mild Traumatic Brain Injury during Aging

Authors: Camille Charlebois-Plante, Marie-Ève Bourassa, Gaelle Dumel, Meriem Sabir, Louis De Beaumont

Abstract:

To the extent of our knowledge, there has been little interest in the chronic effects of mild traumatic brain injury (mTBI) on cognition during normal aging. This is rather surprising considering the impacts on daily and social functioning. In addition, sustaining a mTBI during late adulthood may increase the effect of normal biological aging in individuals who consider themselves normal and healthy. The objective of this study was to characterize the persistent neuropsychological repercussions of mTBI sustained during late adulthood, on average 12 months prior to testing. To this end, 35 mTBI patients and 42 controls between the ages of 50 and 69 completed an exhaustive neuropsychological assessment lasting three hours. All mTBI patients were asymptomatic and all participants had a score ≥ 27 at the MoCA. The evaluation consisted of 20 standardized neuropsychological tests measuring memory, attention, executive and language functions, as well as information processing speed. Performance on tests of visual (Brief Visuospatial Memory Test Revised) and verbal memory (Rey Auditory Verbal Learning Test and WMS-IV Logical Memory subtest), lexical access (Boston Naming Test) and response inhibition (Stroop) revealed to be significantly lower in the mTBI group. These findings suggest that a mTBI sustained during late adulthood induces lasting effects on cognitive function. Episodic memory and executive functions seem to be particularly vulnerable to enduring mTBI effects.

Keywords: cognitive function, late adulthood, mild traumatic brain injury, neuropsychology

Procedia PDF Downloads 158
2661 Individuals’ Inner Wellbeing during the COVID-19 Pandemic: A Quantitative Comparison of Social Connections and Close Relationships between the UK and India

Authors: Maria Spanoudaki, Pauldy C. J. Otermans, Dev Aditya

Abstract:

Relationships form an integral part of our everyday wellbeing. In this study, the focus is on Inner Wellbeing which can be described as an individuals' thoughts and feelings about what they can do and be. Relationships can come in many forms and can be divided into Social Connections (thoughts and feelings about the social network people can establish and rely on), and Close Relationships (thoughts and feeling about the emotional support people can receive from significant others or their close, intimate circle). The purpose of this study is to compare the Social Connections and Close Relationship dimensions of Inner Wellbeing during the COVID-19 pandemic between the UK and India. 392 participants in the UK and 205 participants India completed an online questionnaire using the Inner Wellbeing scale. Factor analyses showed that the construct of Inner Wellbeing can be described as one factor for the UK sample whereas it can be described as two factors (one focusing on positive items and one focusing on negative items) for the Indian sample. Results showed that Social Connections were significantly during COVID-19 in the UK compared to India, whereas there is no significant difference for Close Relationships. The implications on relationships and wellbeing are discussed in detail.

Keywords: social networks, relationship maintenance, relationship satisfaction, COVID-19

Procedia PDF Downloads 145
2660 Navigating Construction Project Outcomes: Synergy Through the Evolution of Digital Innovation and Strategic Management

Authors: Derrick Mirindi, Frederic Mirindi, Oluwakemi Oshineye

Abstract:

The ongoing high rate of construction project failures worldwide is often blamed on the difficulties of managing stakeholders. This highlights the crucial role of strategic management (SM) in achieving project success. This study investigates how integrating digital tools into the SM framework can effectively address stakeholder-related challenges. This work specifically focuses on the impact of evolving digital tools, such as Project Management Software (PMS) (e.g., Basecamp and Wrike), Building Information Modeling (BIM) (e.g., Tekla BIMsight and Autodesk Navisworks), Virtual and Augmented Reality (VR/AR) (e.g., Microsoft HoloLens), drones and remote monitoring, and social media and Web-Based platforms, in improving stakeholder engagement and project outcomes. Through existing literature with examples of failed projects, the study highlights how the evolution of digital tools will serve as facilitators within the strategic management process. These tools offer benefits such as real-time data access, enhanced visualization, and more efficient workflows to mitigate stakeholder challenges in construction projects. The findings indicate that integrating digital tools with SM principles effectively addresses stakeholder challenges, resulting in improved project outcomes and stakeholder satisfaction. The research advocates for a combined approach that embraces both strategic management and digital innovation to navigate the complex stakeholder landscape in construction projects.

Keywords: strategic management, digital tools, virtual and augmented reality, stakeholder management, building information modeling, project management software

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2659 3D Virtualization through Data Collected from Measurements of Mobile Signal Reception Power Levels (LTE) Band at Escuela Superior Politécnica de Chimborazo in Riobamba-Ecuador

Authors: Sandra Cuenca, Steven Chango, Fabian Chamba, Alexandra Vaca

Abstract:

This project addresses a representation of a virtual environment based on the analysis of the RSRP (Reference Signal Received Power) obtained by the Network Cell Info Lite application at the Escuela Superior Politécnica de Chimborazo (ESPOCH) considering the open areas of the Business Administration Department in the 4G LTE Frequency (band 2) of Claro Telephony at a frequency of 1967. 5 MHz, where measurements were performed from 17:00 UTC-05:00. The indicators required for the simulation of the environment designed in sketchup were focused especially on the power levels obtained where it was possible to represent the scenario with real power values obtained in each concentric radius of a total of 3 campaigns of 200 samples each, where the values vary between 84.6 dBm to 115.5 dBm having average power values for each of the 23 radiuses which are introduced in a virtual environment, allowing users to immerse themselves in it, where they can explore 3D virtual environments, generating a color scale from 0 to 10 with red being the weakest signal and green the signal with the best intensity.

Keywords: virtualization, LTE, radios, power intensity levels colors, mobile signal reception power

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2658 In Search of Seaplanes in Andhra Pradesh: In View of UDAN

Authors: Priyadarshini Alok

Abstract:

The present situation in India envisages that because of the surge in population and the economy, cities are expected to spill over to hinterland areas. The consumption-led factors such as land, labor, etc. will be boosted. Hence, the need for regional connectivity becomes obligatory. But, there is enormous pressure upon the land; proving itself through rising traffic congestion, roads, and railway accidents. Air transport is practical, but due to decreasing availability of land, this will not be a wise solution. What with the introduction of seaplanes in the country which was once the vital asset in the world prior to Second World War. Maldives has proved it. Seaplanes offer natural landing site and are time and cost-efficient. Seaplanes in accordance with UDAN can prove to be the solution in linking various regions with other states. This research paper aims to offer the feasibility analysis along with site justification of the potential areas in the state of Andhra Pradesh, India; for the operation of seaplanes. The standards are taken from the US Department of Transportation, Federal Aviation Administration for the analysis. The conflation of Seaplanes with UDAN will offer an alternate mode of air connectivity, strengthen the transport network by simulation of connectivity to unserved and under-served areas and boost the nation's economy.

Keywords: connectivity, seaplanes, transport, UDAN

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2657 Reasons for Adhesion of Membership: A Case Study of Brazilian Soccer Team

Authors: Alexandre Olkoski, Marcelo Curth

Abstract:

Football in Brazil is considered a passion, being the most popular sport in the country, both by the consumer public and by the means of communication that divulge it individually, when compared with other sports modalities. In the last two decades, the soccer teams have given greater importance to the management, since they understood that the same should be managed as a company, but with peculiarities related to the business. In this sense, Brazilian soccer clubs started to make bigger investments for the adhesion of fans in their social frames, allowing a greater need of understanding about the profile of this group of fans/clients. Thus, this work aims to understand the reasons that cause the fans to join the club and identify variables present in the process of intention to join the club. For that, a qualitative exploratory research was conducted, in which thirty-one membership of a soccer club from southern Brazil were interviewed. Based on the interviews, five categories were classified as emotional aspects (passion and love), cognitive aspects (easy access to the stadium and promotional values in tickets), external influences (family and friends), situational aspects (club moment) and aspects related to the event (engagement by modality). As results found in the analysis, it can be highlighted that the motivation of the majority of the respondents to become a member of the analyzed club, is related to the emotional aspects, such as passion and love. Thus, it is perceived that sport, in the case of soccer, generates in the involved ones (fans and leaders) different manifestations, suggesting that the management of this type of business has great complexity and should not be observed only by the spectrum of the club like a business.

Keywords: consumer behavior, marketing, membership, soccer

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2656 Galtung’s Violence Triangle: We Need to Be Thinking Upside Down

Authors: Michael Fusi Ligaliga

Abstract:

Peace and Conflict Studies (PACS), despite being a new pedagogical discipline, is a growing interdisciplinary academic field that has expanded its presence from the traditional lens of war, conflict, and violence to addressing various social issues impacting society. Family and domestic violence (FDV) has seldom been explored through the PACS lens despite some studies showing that “on average, nearly 20 people per minute are physically abused by an intimate partner in the United States. Over one year, this equates to more than 10 million women and men.” In the Pacific, FDV rates are some of the highest in the world. The friction caused by cultural practices reinforcing patriarchy and male impunity, compounded by historical colonial experiences, as well as the impact of Christianity on the Pacific region, creates a complex social landscape when thinking about and addressing FDV in the Pacific. This paper seeks to re-examine Johan Galtung’s violence triangle (GVT) theory and its application to understanding FDV in the Pacific. Galtung argues that there are three forms of violence – direct, structural, and cultural. Direct violence (DV) is behaviors that threaten life itself or diminishes the ability of a person to meet his or her basic needs. This form of violence is visible because it is manifested in behaviors such as killing, maiming, sexual assault, etc. Structural violence (SV) exists when people do not get equal access to goods and services (health, education, justice) that enable them to reach their full potential. When ideologies embedded in cultural norms and practices are used to justify and advocate acts of violence by shifting the moral parameters from being wrong to right or acceptable, this, according to Galtung, is referred to as Cultural violence (CV).

Keywords: direct violence, cultural violence, structural violence, indigenous peacebuilding, samoa

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2655 Flood Susceptibility Assessment of Mandaluyong City Using Analytic Hierarchy Process

Authors: Keigh D. Guinto, Ma. Romina M. Santos

Abstract:

One of the most catastrophic natural disasters in the Philippines is floods. Twelve (12) million people reside in Metro Manila, National Capital Region (NCR), prone to flooding. A flood can cause widespread devastation resulting in damaged properties and infrastructures and loss of life. By using the analytical hierarchy process, six (6) parameters were selected, namely elevation, slope, lithology, distance from the river, river network density, and flow accumulation. Ranking of these parameters demonstrates that distance from the river with 25.31% and river density with 17.30% ranked the highest causative factor to flooding. This is followed by flow accumulation with 16.72%, elevation with 15.33%, slope with 13.53%, and the least flood causative factor is lithology with 11.8%. The generated flood susceptibility map of Mandaluyong has three (3) classes: high susceptibility, moderate susceptibility, and low susceptibility. The flood susceptibility map generated in this study can be used as an aid for planning flood mitigation, land use planning, and general public awareness. This study can also be used for emergency management and can be applied in the disaster risk management of Mandaluyong.

Keywords: analytical hierarchy process, assessment, flood, geographic information system

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2654 3D Plant Growth Measurement System Using Deep Learning Technology

Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

Abstract:

The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

Procedia PDF Downloads 261
2653 Transdisciplinarity Research Approach and Transit-Oriented Development Model for Urban Development Integration in South African Cities

Authors: Thendo Mafame

Abstract:

There is a need for academic research to focus on solving or contributing to solving real-world societal problems. Transdisciplinary research (TDR) provides a way to produce functional and applicable research findings, which can be used to advance developmental causes. This TDR study explores ways in which South Africa’s spatial divide, entrenched through decades of discriminatory planning policies, can be restructured to bring about equitable access to places of employment, business, leisure, and service for previously marginalised South Africans. It does by exploring the potential of the transit-orientated development (TOD) model to restructure and revitalise urban spaces in a collaborative model. The study focuses, through a case study, on the Du Toit station precinct in the town of Stellenbosch, on the peri-urban edge of the city of Cape Town, South Africa. The TOD model is increasingly viewed as an effective strategy for creating sustainable urban redevelopment initiatives, and it has been deployed successfully in other parts of the world. The model, which emphasises development density, diversity of land-use and infrastructure and transformative design, is customisable to a variety of country contexts. This study made use of case study approach with mixed methods to collect and analyse data. Various research methods used include the above-mentioned focus group discussions and interviews, as well as observation, transect walks This research contributes to the professional development of TDR studies that are focused on urbanisation issues.

Keywords: case study, integrated urban development, land-use, stakeholder collaboration, transit-oriented development, transdisciplinary research

Procedia PDF Downloads 119
2652 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

Procedia PDF Downloads 491
2651 1D Convolutional Networks to Compute Mel-Spectrogram, Chromagram, and Cochleogram for Audio Networks

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 215
2650 Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies

Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

Procedia PDF Downloads 64
2649 A New Learning Automata-Based Algorithm to the Priority-Based Target Coverage Problem in Directional Sensor Networks

Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

Abstract:

Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

Procedia PDF Downloads 393