Search results for: mobile network communication

Authors: Amirhossein Chambari

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This article proposes a bi-objective model for the facility location problem subject to congestion (overcrowding). Motivated by implementations to locate servers in internet mirror sites, communication networks, one-server-systems, so on. This model consider for situations in which immobile (or fixed) service facilities are congested (or queued) by stochastic demand to behave as M/M/1/K queues. We consider for this problem two simultaneous perspectives; (1) Customers (desire to limit times of accessing and waiting for service) and (2) Service provider (desire to limit average facility idle-time). A bi-objective model is setup for facility location problem with two objective functions; (1) Minimizing sum of expected total traveling and waiting time (customers) and (2) Minimizing the average facility idle-time percentage (service provider). The proposed model belongs to the class of mixed-integer nonlinear programming models and the class of NP-hard problems. In addition, to solve the model, controlled elitist non-dominated sorting genetic algorithms (Controlled NSGA-II) and controlled elitist non-dominated ranking genetic algorithms (NRGA-I) are proposed. Furthermore, the two proposed metaheuristics algorithms are evaluated by establishing standard multiobjective metrics. Finally, the results are analyzed and some conclusions are given.

Keywords: bi-objective, facility location, queueing, controlled NSGA-II, NRGA-I

Procedia PDF Downloads 563

Authors: Shahrzad Yektatalab, Agrin Mohammadi, Ladan Zarshenas

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Background: Misophonia is a severe emotional response to repetitive sounds. This disorder may limit a person's communication, reduce their ability, or disrupt their social and personal life. This study aims to determine the prevalence of Misophonia and its relationship with obsessive-compulsive disorder, anxiety, and depression in undergraduate students of XXX University of Medical Sciences. Methods: The present study is an analytical descriptive study conducted in October 2020. The study samples are 390 undergraduate students of XXX University of medical sciences. A relative and systematic sampling method was used. In this study, a demographic questionnaire, misophonia questionnaire (A score of 7 or higher is considered as misophonia), Beck anxiety questionnaire, Beck depression questionnaire, and Maudsley questionnaire were used, and the data were analyzed using SPSS 24 software. Due to the non-normality of the data, the Spearman correlation coefficient was used for analyzing data. The significance level was considered less than 0.05. Results: 23.8% of students have misophonia. Of the 390 participants in the study, 93 had experienced misophonia. Among these 93 students, 37 (39.8%) had obsessive-compulsive disorder, 8 (8.6%) had anxiety and 9 (9.7%) had depression. There was a significant and direct relationship between all variables (p <0.001), which means that with the increase of each disorder, the probability of an increase in other disorders increases. Conclusion: Due to the high prevalence of misophonia in students and its direct relationship with obsessive-compulsive disorder, anxiety, and depression, It is recommended that future studies be conducted to identify ways to prevent and reduce the incidence of misophonia.

Keywords: misophonia, obsessive-compulsive disorder, anxiety, depression

Procedia PDF Downloads 44

Authors: Grzegorz Kubinski

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The proposed paper is focused on forms of identity expression in people with disabilities (PWD) in the social networks like Instagram. Theoretical analysis widely proposes using the new media as an assistive tool for improving wellbeing and labour activities of PWD. This kind of use is definitely important and plays a key role in all social inclusion processes. However, Instagram is not a place where PWD only express their own problems, but in the opposite, allows them to construct a new definition of disability. In the paper, the problem how this different than a classical approach to disability is created by PWD will be discussed. This issue will be scrutinized mainly in two points. Firstly, the question of how disability is changed by other everyday activities, like fashion or sport, will be described. Secondly, and this could be seen as more important, the point how PWD redefining their bodies creating a different form of aesthetic will be presented. The paper is based on content analysis of Instagram accounts. About 20 accounts created by PWD were analyzed for 6 month period, taking into account elements like photos, comments and discussions. All those information were studied in relation to 'everyday life' category and 'aesthetic' category. Works by T. Siebers, L. J. Davis or R. McRuer were used as theoretical background. Conclusions and interpretations presented in the proposed paper show that the Internet can be used by PWD not only as prosthetic and assistive tools. PWD willingly use them as modes of expression their independence, agency and identity. The paper proposes that in further research this way of using the Internet communication by PWD should be taken into account as an important part of the understanding of disability.

Keywords: body, disability, identity, new media

Procedia PDF Downloads 122

Authors: Gulnaz Erkomaishvili

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Introduction: The pandemic and the current economic crisis have created problems for entrepreneurship and, therefore for start-up entrepreneurs. The paper presents the challenges of start-up entrepreneurs in Georgia in the time of pandemic and the analysis of the state economic policy measures. Despite many problems, the study found that in 54.2% of start-ups surveyed under the pandemic, innovation opportunities were growing. It can be stated that the pandemic was a good opportunity to increase the innovative capacity of the enterprise. 52% of the surveyed start-up entrepreneurs managed to adapt to the current situation and increase the sale of their products/services through remote channels. As for the assessment of state support measures by start-up entrepreneurs, a large number of Georgian start-ups do not assess the measures implemented by the state positively. Methodology: The research process uses methods of analysis and synthesis, quantitative and qualitative, interview/survey, grouping, relative and average values, graphing, comparison, data analysis, and others. Main Findings: Studies have shown that for the start-up entrepreneurs, the main problem remains: inaccessible funding, workers' qualifications gap, inflation, taxes, regulation, political instability, inadequate provision of infrastructure, amount of taxes, and other factors. Conclusions: The state should take the following measures to support business start-ups: create an attractive environment for investment, availability of soft loans, creation of an insurance system, infrastructure development, increase the effectiveness of tax policy (simplicity of the tax system, clarity, optimal tax level ); promote export growth (develop strategy for opening up international markets, build up a broad marketing network, etc.).

Keywords: start-up entrepreneurs, startups, start-up entrepreneurs support programs, start-up entrepreneurs support economic policy

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Authors: Sreetama Ghosh, Sundara Ramaprabhu

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Carbon dioxide gas has been a major cause for the worldwide increase in green house effect, which leads to climate change and global warming. So CO₂ capture & sequestration has become an effective way to reduce the concentration of CO₂ in the environment. One such way to capture CO₂ in porous materials is by adsorption process. A potential material in this aspect is porous hexagonal boron nitride or 'white graphene' which is a well-known two-dimensional layered material with very high thermal stability. It had been investigated that the sample with hierarchical pore structure and high specific surface area shows excellent performance in capturing carbon dioxide gas and thereby mitigating the problem of environmental pollution to the certain extent. Besides, the presence of sulfur as well as nitrogen in the sample synergistically helps in the increase in adsorption capacity. In this work, a cost effective single step synthesis of highly porous boron nitride nanosheets doped with sulfur had been demonstrated. Besides, the CO₂ adsorption-desorption studies were carried on using a pressure reduction technique. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Thermodynamic studies suggest that the adsorption takes place mainly through physisorption. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Further, the surface modification of the highly porous nano sheets carried out by incorporating ionic liquids had further enhanced the capturing capability of CO₂ gas in the nanocomposite, revealing that this particular material has the potential to be an excellent adsorbent of carbon dioxide gas.

Keywords: CO₂ capture, hexagonal boron nitride nanosheets, porous network, sulfur doping

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: B. Lokuketagoda, M. Weerakoon, U. Madushan, A. N. Senaratne, K. Y. Abeywardena

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Ransomware has become a common threat in past few years and the recent threat reports show an increase of growth in Ransomware infections. Researchers have identified different variants of Ransomware families since 2015. Lack of knowledge of the user about the threat is a major concern. Ransomware detection methodologies are still growing through the industry. Email is the easiest method to send Ransomware to its victims. Uninformed users tend to click on links and attachments without much consideration assuming the emails are genuine. As a solution to this in this paper R-Killer Ransomware detection tool is introduced. Tool can be integrated with existing email services. The core detection Engine (CDE) discussed in the paper focuses on separating suspicious samples from emails and handling them until a decision is made regarding the suspicious mail. It has the capability of preventing execution of identified ransomware processes. On the other hand, Sandboxing and URL analyzing system has the capability of communication with public threat intelligence services to gather known threat intelligence. The R-Killer has its own mechanism developed in its Proactive Monitoring System (PMS) which can monitor the processes created by downloaded email attachments and identify potential Ransomware activities. R-killer is capable of gathering threat intelligence without exposing the user’s data to public threat intelligence services, hence protecting the confidentiality of user data.

Keywords: ransomware, deep learning, recurrent neural networks, email, core detection engine

Procedia PDF Downloads 191

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

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It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

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Authors: M. Touhidul Islam Sarker, Mohammod Abul Kashem

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The purpose of this paper is to improve the e-learning system and digitize the learning method in the educational sector. The learner will login into e-learning platform and easily access the digital content, the content can be downloaded and take an assessment for evaluation. Learner can get access to these digital resources by using tablet, computer, and smart phone also. E-learning system can be defined as teaching and learning with the help of multimedia technologies and the internet by access to digital content. E-learning replacing the traditional education system through information and communication technology-based learning. This paper has designed and implemented integrated e-learning system architecture with University Management System. Moodle (Modular Object-Oriented Dynamic Learning Environment) is the best e-learning system, but the problem of Moodle has no school or university management system. In this research, we have not considered the school’s student because they are out of internet facilities. That’s why we considered the university students because they have the internet access and used technologies. The University Management System has different types of activities such as student registration, account management, teacher information, semester registration, staff information, etc. If we integrated these types of activity or module with Moodle, then we can overcome the problem of Moodle, and it will enhance the e-learning system architecture which makes effective use of technology. This architecture will give the learner to easily access the resources of e-learning platform anytime or anywhere which digitizes the learning method.

Keywords: database, e-learning, LMS, Moodle

Procedia PDF Downloads 165

Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

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Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

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Authors: Jonas Hamann, Siavash Saki, Tobias Hagen

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Discretization of urban areas is a crucial aspect in many spatial analyses. The process of discretization of space into subspaces without overlaps and gaps is called tessellation. It helps understanding spatial space and provides a framework for analyzing geospatial data. Tessellation methods can be divided into two groups: regular tessellations and irregular tessellations. While regular tessellation methods, like squares-grids or hexagons-grids, are suitable for addressing pure geometry problems, they cannot take the unique characteristics of different subareas into account. However, irregular tessellation methods allow the border between the subareas to be defined more realistically based on urban features like a road network or Points of Interest (POI). Even though Python is one of the most used programming languages when it comes to spatial analysis, there is currently no library that combines different tessellation methods to enable users and researchers to compare different techniques. To close this gap, we are proposing TessPy, an open-source Python package, which combines all above-mentioned tessellation methods and makes them easily accessible to everyone. The core functions of TessPy represent the five different tessellation methods: squares, hexagons, adaptive squares, Voronoi polygons, and city blocks. By using regular methods, users can set the resolution of the tessellation which defines the finesse of the discretization and the desired number of tiles. Irregular tessellation methods allow users to define which spatial data to consider (e.g., amenity, building, office) and how fine the tessellation should be. The spatial data used is open-source and provided by OpenStreetMap. This data can be easily extracted and used for further analyses. Besides the methodology of the different techniques, the state-of-the-art, including examples and future work, will be discussed. All dependencies can be installed using conda or pip; however, the former is more recommended.

Keywords: geospatial data science, geospatial data analysis, tessellations, urban studies

Procedia PDF Downloads 112

Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

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Authors: Armend Kelmendi, Adnan Ahmeti

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The purpose of our study was to assess the impact of soccer in the overall wealth fare (education, health, and economic prosperity) of youth in Kosovo (age: 7-18). The research conducted measured a number of parameters (training methodologies, conditions, community leadership impact) in a sample consisting of 6 different football clubs’ academies across the country. Fifty (50) male and female football youngsters volunteered in this study. To generate more reliable results, the analysis was conducted with the help of a set of effective project management tools and techniques (Gantt chart, Logic Network, PERT chart, Work Breakdown Structure, and Budgeting Analysis). The interviewees were interviewed under a specific lens of categories (impact in education, health, and economic prosperity). A set of questions were asked i.e. what has football provided to you and the community you live in?; Did football increase your confidence and shaped your life for better?; What was the main reason you started training in football? The results generated explain how a single sport, namely that of football in Kosovo can make a huge social change, improving key social factors in a society. There was a considerable difference between the youth clubs as far as training conditions are concerned. The study found out that despite financial constraints, two out of six clubs managed to produce twice as more talented players that were introduced to professional primary league teams in Kosovo and Albania, including other soccer teams in the region, Europe, and Asia. The study indicates that better sports policy must be formulated and associated with important financial investments in soccer for it to be considered fruitful and beneficial for players of 18 plus years of age, namely professionals.

Keywords: youth, prosperity, conditions, investments, growth, free movement

Procedia PDF Downloads 228

Authors: Longtao He, Han Wu

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Summary: As the need for elder care increases in China due to a growing aging population and, in particular, rising cancer rates, it becomes increasingly important to also support family caregivers, who are often the main source of care. We used a qualitative meta-synthesis to systematically evaluate and integrate the caregiving experiences of family caregivers of elderly cancer patients as revealed by articles published in Chinese journals. Findings: Nine studies are included in the final analysis. The caregiver experiences they describe are synthesized into three primary themes: care needs, care burden, and care gains, with numerous secondary themes. Besides the findings that seem to align with other findings across cultures, we have highlighted three main discoveries from the synthesis that may be quite specific to the Chinese context: 1. more sub-themes related to specific caregiving skills caregivers of cancer patients; 2. a call for health professionals to improve their communication skills with family caregivers; 3. the important role of filial piety. Applications: Our findings can be used to help health social workers and relevant policymakers in China support family caregivers by identifying the education and training required for caregivers, ways to make the most of potential care gains, and ways to ease care burdens.

Keywords: cancer, Chinese family caregivers, caregiving skills, care burden, care gains, health social work

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Authors: C. W. F. Che Wan Putra, M. Alshawi, M. S. Al Ahbabi, M. Jabakhanji

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Much of the waste that is generated throughout the life-cycle of a building is mainly related to project stakeholders not having access to information that others have created. This results in waste and high costs. Over the past decade, however, the industry reacted to these challenges by adopting effective procurement approaches, such as partnering and design and build, to improve collaboration and communication among projects’ stakeholders. Most recently, there is a focus on creating and reusing digital project information of stakeholders throughout the life-cycle to facilitate the exchange of information among partners. This shift is based around BIM (Building Information Modelling) and collaborative environment (IPD). The power of collaborative BIM goes beyond improving efficiency. Sustainability, perhaps the most important challenge for the design and construction community, is at the intersection of BIM and collaborative project delivery, drawing strength from both. Due to these benefits, a research study has been carried out to investigate the need of BIM and IPD, on a large scale construction project which is procured on a traditional approach, i.e. design-bid-build. A qualitative research work including a semi-structured interview with project partners was conducted on a typical project in the UAE, whereby the selected project suffered from severe delays and cost overrun. This paper aims to bring about clear evidence to what most likely to happen to a typical construction project in spite of employing very good consultants, project manager and contractors and how these problems could have been avoided if BIM and IPD were deployed.

Keywords: building information modelling (BIM), integrated project delivery (IPD), collaborative environment, case study

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

Procedia PDF Downloads 42

Authors: Garance Liaboeuf, Alain Le Bot, Ali Daouadji, Antoine Martinet, Mohamed Bouteldja, Nicolas Grignard, Damien Pilet

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As every French road operator, Autoroutes et Tunnel du Mont Blanc (ATMB) conducts annual inspections of its infrastructures. Significant loss of skid resistance has been observed on some sections of his network, sometimes on recent pavements. In the way of making the mechanisms and factors that can lead to this loss of grip more understandable, ATMB has launched a study aimed at identifying the causes and developing solutions to prevent this phenomenon. To quantify the deterioration of different road surfaces subjected to controlled scraping with steel blades of snow removal machines, a field campaign was conducted. These operations are carried out during the winter period according to a strict protocol. In order to correct the skid-resistance values, a control panel is set up. In this way, only the effect of the scraping is taken into account. It allows us to exclude the influence of the environment (temperature, humidity, etc.) and of the surface state on the skid resistance values measured during the different sessions. Skid measurements after eight years of scraping cycles showed a 7% to 13% decrease in microtexture and a 2% to 12% decrease in macrotexture adhesion. These reductions are attributed to the phenomenon of polishing road surfaces by using steel blades. Also, regeneration phenomena occur after a certain number of blades pass. Differences in steel scraper blade resistance appear related to the intrinsic properties of the aggregate used in the pavement formulation and its type. Finally, the results of this campaign will allow the determination of the resistance characteristics of the pavement damage by the steel blade of snow plows. An evolution law of the surface condition as a function of the scraping operations will also be developed from this study.

Keywords: pavement, skid, surface, snow plow

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Authors: Michael Gerges, Ograbe Ahiakwo, Martin Jaeger, Ahmad Asaad

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Recent advances of Building Information Modeling (BIM) especially in the Middle East have increased remarkably. Dubai has been taking a lead on this by making it mandatory for BIM to be adopted for all projects that involve complex architecture designs. This is because BIM is a dynamic process that assists all stakeholders in monitoring the project status throughout different project phases with great transparency. It focuses on utilizing information technology to improve collaboration among project participants during the entire life cycle of the project from the initial design, to the supply chain, resource allocation, construction and all productivity requirements. In view of this trend, the paper examines the extent of applying BIM in the State of Kuwait, by exploring practitioners’ perspectives on BIM, especially their perspectives on main barriers and main advantages. To this end structured interviews were carried out based on questionnaires and with a range of different construction professionals. The results revealed that practitioners perceive improved communication and mitigated project risks by encouraged collaboration between project participants. However, it was also observed that the full implementation of BIM in the State of Kuwait requires concerted efforts to make clients demanding BIM, counteract resistance to change among construction professionals and offer more training for design team members. This paper forms part of an on-going research effort on BIM and its application in the State of Kuwait and it is on this basis that further research on the topic is proposed.

Keywords: building information modeling, BIM, construction industry, Kuwait

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Authors: Pichamon Chansuchai

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The study of Thai consumer behavior toward buying goods on the Internet is a survey research. The five-level rating scale and open-ended questionnaire are applied for this research procedure, which has more than 400 random sampling of Thai people aged between 15-40 years old. The summary findings are: The analysis of respondents profile were female 55.3% and male 44.8% , 35.3% aged between 20-30 years old, had been employed 29.5% with average income up to 11,000 baht/month 50.2% and expenditure more than 11,000 baht per month 29.3%. The internet usage behavior of respondents mostly found that objectives of the internet usage are: 1) Communication 93.3% 2) the categories of websites usage was trading 42.8% 3) The marketing mix effected to trading behavior via internet which can be analyzed in term of marketing factor as following: Product focused on product quality was the most influenced factor with average value 4.75. The cheaper price than overview market was the most effect factor to internet shopping with mean value 4.53. The average value 4.67 of the available place that could reduce spending time for shopping. The effective promotion of the buy 1 get 1 was the stimulus factor for internet shopping with mean value 4.60. For hypothesis testing, the different sex has relationship with buying decision. It presented that male and female have vary purchasing decision via internet with value of significant difference 0.05. Furthermore, the variety occupations of respondents related to the use of selected type of website. It also found that the vary of personal occupation effected to the type of website selection dissimilar with value of significant difference 0.05.

Keywords: behavior, internet, consumer, goods

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Authors: Mohamed Zellagui, Heba Ahmed Hassan

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This paper proposes a new approach for the calculation of short-circuit parameters in the presence of Pulse Width Modulated based Series Compensator (PWMSC). PWMSC is a newly Flexible Alternating Current Transmission System (FACTS) device that can modulate the impedance of a transmission line through applying a variation to the duty cycle (D) of a train of pulses with fixed frequency. This results in an improvement of the system performance as it provides virtual compensation of distribution line impedance by injecting controllable apparent reactance in series with the distribution line. This controllable reactance can operate in both capacitive and inductive modes and this makes PWMSC highly effective in controlling the power flow and increasing system stability in the system. The purpose of this work is to study the impact of fault resistance (RF) which varies between 0 to 30 Ω on the fault current calculations in case of a ground fault and a fixed fault location. The case study is for a medium voltage (MV) Algerian distribution line which is compensated by PWMSC in the 30 kV Algerian distribution power network. The analysis is based on symmetrical components method which involves the calculations of symmetrical components of currents and voltages, without and with PWMSC in both cases of maximum and minimum duty cycle value for capacitive and inductive modes. The paper presents simulation results which are verified by the theoretical analysis.

Keywords: pulse width modulated series compensator (pwmsc), duty cycle, distribution line, short-circuit calculations, ground fault, symmetrical components method

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Authors: A. F. Alves, L. Schmidt, J. Ferrao

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Portugal is one of the more vulnerable European countries to the impacts of climate change. These include: temperature increase; coastal sea level rise; desertification and drought in the countryside; and frequent and intense extreme weather events. Hence, adaptation strategies to climate change are of great importance. This is what was addressed by ClimAdaPT.Local. This policy-oriented project had the main goal of developing 26 Municipal Adaptation Strategies for Climate Change, through the identification of local specific present and future vulnerabilities, the training of municipal officials, and the engagement of local communities. It is intended to be replicated throughout the whole territory and to stimulate the creation of a national network of local adaptation in Portugal. Supported by methodologies and tools specifically developed for this project, our paper is based on the surveys, training and stakeholder engagement workshops implemented at municipal level. In an 'adaptation-as-learning' process, these tools functioned as a social-learning platform and an exercise in knowledge and policy co-production. The results allowed us to explore the nature of local vulnerabilities and the exposure of gaps in the context of reappraisal of both future climate change adaptation opportunities and possible dysfunctionalities in the governance arrangements of municipal Portugal. Development issues are highlighted when we address the sectors and social groups that are both more sensitive and more vulnerable to the impacts of climate change. We argue that a pluralistic dialogue and a common framing can be established between them, with great potential for transformational adaptation. Observed climate change, present-day climate variability and future expectations of change are great societal challenges which should be understood in the context of the sustainable development agenda.

Keywords: adaptation, ClimAdaPT.Local, climate change, Portugal, sustainable development

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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Authors: Gamalath M. B. P. Abeysekara

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Primary objective of any organization is to enhance the bottom line profit. Strategic procurement is one of the prominent aspects in view of receiving this ultimate objective. Strategic procurement is an activity used in each and every organization in their operations. Pharmaceutical procurement is an especially significant task for any organizations, particularly state sector concerned. The whole pharmaceutical procurement requirement of the country is procured through the State Pharmaceutical Corporation (SPC) of Sri Lanka. They follow Pharmaceutical Procurement Guideline of 2006 as the procurement principle. The main objective of this project is to identify the importance of State Pharmaceutical Corporation supplier selection criteria and critical analysis of pharmaceutical procurement procedure. State Pharmaceutical Corporations applied net price, product quality, past performance, and delivery of suppliers’ as main criteria for the selection suppliers. Data collection for this study was taken place through a questionnaire, given to fifty doctors within the Colombo district attached to five main state hospitals. Data analysis is carried out with mean and standard deviation functions. The ultimate outcomes indicated product quality, net price, and delivery of suppliers’ are the most important criteria behind the selection of suppliers. Critical analysis proved State Pharmaceutical Corporation should focus on net price reduction, improving laboratory testing facilities and effective communication between up and down stream of supply chain.

Keywords: government procurement procedure, pharmaceutical procurement supplier selection criteria, importance of SPC supplier selection criteria

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Authors: Thomas, Daniel Tajo, Kish

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Sight is primarily associated with the function of gathering and processing near and extended spatial information which is largely used to support self-determined interaction with the environment through self-directed movement and navigation. By contrast, hearing is primarily associated with the function of gathering and processing sequential information which may typically be used to support self-determined communication through the self-directed use of music and language. Blindness or the lack of vision is traditionally characterized by a lack of capacity to access spatial information which, in turn, is presumed to result in a lack of capacity for self-determined interaction with the environment due to limitations in self-directed movement and navigation. However, through a specific protocol of FlashSonar education developed by World Access for the Blind, the function of hearing can be expanded in blind people to carry out some of the functions normally associated with sight, that is to access and process near and extended spatial information to construct three-dimensional acoustic images of the environment. This perceptual education protocol results in a significant restoration in blind people of self-determined environmental interaction, movement, and navigational capacities normally attributed to vision - a new way to see. Thus, by expanding the function of hearing to process spatial information to restore self-determined movement, we are not only changing the meaning of blindness, and what it means to be blind, but we are also recasting the meaning of vision and what it is to see.

Keywords: echolocation, changing, sensory, function

Procedia PDF Downloads 137

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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Authors: Lethola Tshikose, Munyaradzi Katurura

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Information and Communication Technology (ICT) plays a critical role in improving daily healthcare processes. The South African healthcare organizations have adopted Information Systems to integrate their patient records. This has made it much easier for healthcare organizations because patient information can now be accessible at any time. The primary purpose of this research study was to investigate the best practices that can be applied to enhance patient security and confidentiality when using e-health systems in South Africa. Security and confidentiality are critical in healthcare organizations as they ensure safety in EHRs. The research study used an inductive research approach that included a thorough literature review; therefore, no data was collected. The research paper’s scope included patient data and possible security threats associated with healthcare systems. According to the study, South African healthcare organizations discovered various patient data security and confidentiality issues. The study also revealed that when it comes to handling patient data, health professionals sometimes make mistakes. Some may not be computer literate, which posed issues and caused data to be tempered with. The research paper recommends that healthcare organizations ensure that security measures are adequately supported and promoted by their IT department. This will ensure that adequate resources are distributed to keep patient data secure and confidential. Healthcare organizations must correctly use standards set up by IT specialists to solve patient data security and confidentiality issues. Healthcare organizations must make sure that their organizational structures are adaptable to improve security and confidentiality.

Keywords: E-health, EHR, security, confidentiality, healthcare

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

Procedia PDF Downloads 252

Authors: Q. R. Cheah, Y. F. Tan

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In modern times, the push for a low carbon footprint entails achieving carbon neutrality as a goal for future generations. One possible step towards carbon footprint reduction is the use of more durable materials with longer lifespans, for example, silicone data cableswhich show at least double the lifespan of similar plastic products. By having greater durability and longer lifespans, silicone data cables can reduce the amount of trash produced as compared to plastics. Furthermore, silicone products don’t produce micro contamination harmful to the ocean. Every year the electronics industry produces an estimated 5 billion data cables for USB type C and lightning data cables for tablets and mobile phone devices. Material usage for outer jacketing is 6 to 12 grams per meter. Tests show that the product lifespan of a silicone data cable over plastic can be doubled due to greater durability. This can save at least 40,000 tonnes of material a year just on the outer jacketing of the data cable. The facility in this study specialises in compounding of liquid silicone rubber (LSR) material for the extrusion process in jacketing for the silicone data cable. This study analyses the carbon emissions from the facility, which is presently capable of producing more than 1,000 tonnes of LSR annually. This study uses guidelines from the World Business Council for Sustainable Development (WBCSD) and World Resources Institute (WRI) to define the boundaries of the scope. The scope of emissions is defined as 1. Emissions from operations owned or controlled by the reporting company, 2. Emissions from the generation of purchased or acquired energy such as electricity, steam, heating, or cooling consumed by the reporting company, and 3. All other indirect emissions occurring in the value chain of the reporting company, including both upstream and downstream emissions. As the study is limited to the compounding facility, the system boundaries definition according to GHG protocol is cradle-to-gate instead of cradle-to-grave exercises. Malaysia’s present electricity generation scenario was also used, where natural gas and coal constitute the bulk of emissions. Calculations show the LSR produced for the silicone data cable with high fire retardant capability has scope 1 emissions of 0.82kg CO2/kg, scope 2 emissions of 0.87kg CO2/kg, and scope 3 emissions of 2.76kg CO2/kg, with a total product carbon footprint of 4.45kg CO2/kg. This total product carbon footprint (Cradle-to-gate) is comparable to the industry and to plastic materials per tonne of material. Although per tonne emission is comparable to plastic material, due to greater durability and longer lifespan, there can be significantly reduced use of LSR material. Suggestions to reduce the calculated product carbon footprint in the scope of emissions involve 1. Incorporating the recycling of factory silicone waste into operations, 2. Using green renewable energy for external electricity sources and 3. Sourcing eco-friendly raw materials with low GHG emissions.

Keywords: carbon footprint, liquid silicone rubber, silicone data cable, Malaysia facility

Procedia PDF Downloads 83