Search results for: recognition primed decision

Authors: Sarayu Agarwal

Abstract:

This paper aims to teach English (secondary language) by bridging the understanding between the Regional language (primary language) and the English Language (secondary language). Here primary language is the one a person has learned from birth or within the critical period, while secondary language would be any other language one learns or speaks. The paper also focuses on evolving old teaching methods to a contemporary participatory model of learning and teaching. Pilot studies were conducted to gauge an understanding of student’s knowledge of the English language. Teachers and students were interviewed and their academic curriculum was assessed as a part of the initial study. Extensive literature study and design thinking principles were used to devise a solution to the problem. The objective is met using a holistic learning kit/card game to teach children word recognition, word pronunciation, word spelling and writing words. Implication of the paper is a noticeable improvement in the understanding and grasping of English language. With increasing usage and applicability of English as a second language (ESL) world over, the paper becomes relevant due to its easy replicability to any other primary or secondary language. Future scope of this paper would be transforming the idea of participatory learning into self-regulated learning methods. With the upcoming govt. learning centres in rural areas and provision of smart devices such as tablets, the development of the card games into digital applications seems very feasible.

Keywords: English as a second language, vocabulary-building card games, learning through gamification, rural education

Procedia PDF Downloads 246

Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

Abstract:

This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

Procedia PDF Downloads 78

Authors: Brady Manescau, Ilyas Sellami, Khaled Chetehouna, Charles De Izarra, Rachid Nait-Said, Fati Zidani

Abstract:

During a fire in an oil and gas refinery, several thermal accidents can occur and cause serious damage to people and environment. Among these accidents, the BLEVE (Boiling Liquid Expanding Vapor Explosion) is most observed and remains a major concern for risk decision-makers. It corresponds to a violent vaporization of explosive nature following the rupture of a vessel containing a liquid at a temperature significantly higher than its normal boiling point at atmospheric pressure. Their effects on the environment generally appear in three ways: blast overpressure, radiation from the fireball if the liquid involved is flammable and fragment hazards. In order to estimate the potential damage that would be caused by such an explosion, risk decision-makers often use quantitative risk analysis (QRA). This analysis is a rigorous and advanced approach that requires a reliable data in order to obtain a good estimate and control of risks. However, in most cases, the data used in QRA are obtained from the empirical correlations. These empirical correlations generally overestimate BLEVE effects because they are based on simplifications and do not take into account real parameters like the geometry effect. Considering that these risk analyses are based on an assessment of BLEVE effects on human life and plant equipment, more precise and reliable data should be provided. From this point of view, the CFD modeling of BLEVE effects appears as a solution to the empirical law limitations. In this context, the main objective is to develop a numerical tool in order to predict BLEVE thermal effects using the CFD code FDS version 6. Simulations are carried out with a mesh size of 1 m. The fireball source is modeled as a vertical release of hot fuel in a short time. The modeling of fireball dynamics is based on a single step combustion using an EDC model coupled with the default LES turbulence model. Fireball characteristics (diameter, height, heat flux and lifetime) issued from the large scale BAM experiment are used to demonstrate the ability of FDS to simulate the various steps of the BLEVE phenomenon from ignition up to total burnout. The influence of release parameters such as the injection rate and the radiative fraction on the fireball heat flux is also presented. Predictions are very encouraging and show good agreement in comparison with BAM experiment data. In addition, a numerical study is carried out on an operational propane accumulator in an Algerian gas processing plant of SONATRACH company located in the Hassi R’Mel Gas Field (the largest gas field in Algeria).

Keywords: BLEVE effects, CFD, FDS, fireball, LES, QRA

Procedia PDF Downloads 186

Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

Abstract:

Digital Twins (DT) are an innovative concept of cyber-physical integration of data between an asset and its virtual replica. They have originated in established industries such as manufacturing and aviation and have garnered increasing attention as a potentially transformative technology within the built environment. With the potential to support decision-making, real-time simulations, forecasting abilities and managing operations, DT do not fall under a singular scope. This makes defining and leveraging the potential uses of DT a potential missed opportunity. Despite its recognised potential in established industries, literature on DT in the built environment remains limited. Inadequate attention has been given to the implementation of DT in construction projects, as opposed to its operational stage applications. Additionally, the absence of a standardised definition has resulted in inconsistent interpretations of DT in both industry and academia. There is a need to consolidate research to foster a unified understanding of the DT. Such consolidation is indispensable to ensure that future research is undertaken with a solid foundation. This paper aims to present a comprehensive systematic literature review on the role of DT in the built environment. To accomplish this objective, a review and thematic analysis was conducted, encompassing relevant papers from the last five years. The identified papers are categorised based on their specific areas of focus, and the content of these papers was translated into a through classification of DT. In characterising DT and the associated data processes identified, this systematic literature review has identified 6 DT opportunities specifically relevant to the built environment: Facilitating collaborative procurement methods, Supporting net-zero and decarbonization goals, Supporting Modern Methods of Construction (MMC) and off-site manufacturing (OSM), Providing increased transparency and stakeholders collaboration, Supporting complex decision making (real-time simulations and forecasting abilities) and Seamless integration with Internet of Things (IoT), data analytics and other DT. Finally, a discussion of each area of research is provided. A table of definitions of DT across the reviewed literature is provided, seeking to delineate the current state of DT implementation in the built environment context. Gaps in knowledge are identified, as well as research challenges and opportunities for further advancements in the implementation of DT within the built environment. This paper critically assesses the existing literature to identify the potential of DT applications, aiming to harness the transformative capabilities of data in the built environment. By fostering a unified comprehension of DT, this paper contributes to advancing the effective adoption and utilisation of this technology, accelerating progress towards the realisation of smart cities, decarbonisation, and other envisioned roles for DT in the construction domain.

Keywords: built environment, design, digital twins, literature review

Procedia PDF Downloads 81

Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

Abstract:

In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

Procedia PDF Downloads 126

Authors: Ian Walsh, Terry Nguyen-Khuong, Christopher H. Taron, Pauline M. Rudd

Abstract:

Glycoproteins and their covalently bonded glycans play critical roles in the immune system, cell communication, disease and disease prognosis. Ultra performance liquid chromatography (UPLC) coupled with mass spectrometry is conventionally used to qualitatively and quantitatively characterise glycan structures in a given sample. Exoglycosidases are enzymes that catalyze sequential removal of monosaccharides from the non-reducing end of glycans. They naturally have specificity for a particular type of sugar, its stereochemistry (α or β anomer) and its position of attachment to an adjacent sugar on the glycan. Thus, monitoring the peak movements (both in the UPLC and MS1) after application of exoglycosidases provides a unique and effective way to annotate sugars with high detail - i.e. differentiating positional and linkage isomers. Manual annotation of an exoglycosidase experiment is difficult and time consuming. As such, with increasing sample complexity and the number of exoglycosidases, the analysis could result in manually interpreting hundreds of peak movements. Recently, we have implemented pattern recognition software for automated interpretation of UPLC-MS1 exoglycosidase digestions. In this work, we explain the software, indicate how much time it will save and provide example usage showing the annotation of positional and linkage isomers in Immunoglobulin G, apolipoprotein J, and simple glycan standards.

Keywords: bioinformatics, automated glycan assignment, liquid chromatography, mass spectrometry

Procedia PDF Downloads 200

Authors: Amirhossein Karamoozian, Desheng Wu, Behzad Abbasnejad

Abstract:

Building information modelling (BIM) is a new technology to enhance the efficiency of project management in the construction industry. In addition to the potential benefits of this useful technology, there are various risks and obstacles to applying it in construction projects. In this study, a decision making approach is presented for risk assessment in BIM adoption in construction projects. Various risk factors of exerting BIM during different phases of the project lifecycle are identified with the help of Delphi method, experts’ opinions and related literature. Afterward, Shannon’s entropy and Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) are applied to derive priorities of the identified risk factors. Results indicated that lack of knowledge between professional engineers about workflows in BIM and conflict of opinions between different stakeholders are the risk factors with the highest priority.

Keywords: risk, BIM, fuzzy TOPSIS, construction projects

Procedia PDF Downloads 229

Authors: Lubos Rojka

Abstract:

The common perception of morally responsible behavior is that it presupposes freedom of choice, and that free decisions and actions are not determined by natural events, but by a person. In other words, the moral agent has the ability and the possibility of doing otherwise when making morally responsible decisions, and natural causal determinism cannot fully account for morally significant freedom. The incompatibility between a person’s morally significant freedom and causal determinism appears to be a natural position. Nevertheless, some of the most influential philosophical theories on moral responsibility are compatibilist or semi-compatibilist, and they exclude the requirement of alternative possibilities, which contradicts the claims of classical incompatibilism. The compatibilists often employ Frankfurt-style thought experiments to prove their theory. The goal of this paper is to examine the role of imaginary Frankfurt-style examples in compatibilist accounts. More specifically, the compatibilist accounts defended by John Martin Fischer and Michael McKenna will be inserted into the broader understanding of a person elaborated by Harry Frankfurt, Robert Kane and Walter Glannon. Deeper analysis reveals that the exclusion of alternative possibilities based on Frankfurt-style examples is problematic and misleading. A more comprehensive account of moral responsibility and morally significant (source) freedom requires higher order complex theories of human will and consciousness, in which rational and self-creative abilities and a real possibility to choose otherwise, at least on some occasions during a lifetime, are necessary. Theoretical moral reasons and their logical relations seem to require a sort of higher-order agent-causal incompatibilism. The ability of theoretical or abstract moral reasoning requires complex (strongly emergent) mental and conscious properties, among which an effective free will, together with first and second-order desires. Such a hierarchical theoretical model unifies reasons-responsiveness, mesh theory and emergentism. It is incompatible with physical causal determinism, because such determinism only allows non-systematic processes that may be hard to predict, but not complex (strongly) emergent systems. An agent’s effective will and conscious reflectivity is the starting point of a morally responsible action, which explains why a decision is 'up to the subject'. A free decision does not always have a complete causal history. This kind of an emergentist source hyper-incompatibilism seems to be the best direction of the search for an adequate explanation of moral responsibility in the traditional (merit-based) sense. Physical causal determinism as a universal theory would exclude morally significant freedom and responsibility in the traditional sense because it would exclude the emergence of and supervenience by the essential complex properties of human consciousness.

Keywords: consciousness, free will, determinism, emergence, moral responsibility

Procedia PDF Downloads 164

Authors: Piamsiri Sawaisorn, Tienrat Tangchaikeeree, Waraporn Chan-On, Chaniya Leepiyasakulchai, Rachanee Udomsangpetch, Suradej Hongeng, Kulachart Jangpatarapongsa

Abstract:

Human Vγ9Vδ2 T lymphocytes are regarded as promising effector cells for cancer immunotherapy since they have the ability to eliminate several tumor cells through non-peptide antigen recognition and non-major histocompatibility complex (MHC) restriction. An issue of recent interest is the capability to activate γδ T cells by use of a group of drugs, such as pamidronate, that cause accumulation of phosphoantigen which is recognized by γδ T cell receptors. Moreover, their antigen presenting cell-like phenotype and function have been confirmed in many clinical trials. In this study, Vγ9Vδ2 T cells derived from normal peripheral blood mononuclear cells were activated with pamidronate and the expanded Vγ9Vδ2 T cells can recognize and kill chronic myeloid leukemia (CML) cells treated with pamidronate through their cytotoxic activity. To support the strong role played by Vγ9Vδ2 T cells against cancer, we provide the evidence that Vγ9Vδ2 T cells activated with CML cell lysate antigen can efficiently express antigen presenting cell (APC) phenotype and function. In conclusion, pamidronate can be used in intentional activation of human Vγ9Vδ2 T cells and can increase the susceptibility of CML cells to cytotoxicity of Vγ9Vδ2 T cells. The activated Vγ9Vδ2 T cells by cancer cells lysate can show their APC characteristics, and so greatly increase the interest in exploring their therapeutic potential in hematologic malignancy.

Keywords: γδ T lymphocytes, antigen-presenting cells, chronic myeloid leukemia, cancer, immunotherapy

Procedia PDF Downloads 186

Authors: Somchai Buaroong

Abstract:

This research attempted to study information system success in dimensions of the user satisfaction level and to find the association between the independent factors of the user experiences, user knowledge, and user attitude. The study sample was selected using simple random sampling that comprised of 190 users who had used the Bangkok HIS. The data were reported from 165 questionnaires. The results found that the user satisfaction was at a moderate level, user satisfaction on the information quality and system quality was at a moderate level, while satisfaction on service quality was at a high level. The computer knowledge of the user was at a moderate level, and the user attitude was at a positive level. The participation of the user was at a low level and the participation in decision and in evaluation was at a low level; however participation in implementation and in benefit was at a moderate.

Keywords: information system success, hospital information system, user attitude, user satisfaction

Procedia PDF Downloads 320

Authors: Gyongyver Csapo, Andrea Czibor

Abstract:

Machiavellianism is a personality trait based on the exploitation and deception of others. Machiavellian individuals are motivated to gain and to maintain power with the help of their strategic thinking, manipulation tactics, and interpersonal skills. Consequently, Machiavellianism is treated as a personality trait that can affect an individual’s career and work-related behavior. The aim of our research is to provide a narrative psychological approach to Machiavellianism in order to get a more comprehensive picture about the attitudes, values, and work-related behaviors of Machiavellian individuals. In this study, semi-structured interviews were made with employees (N=275) about their work-related experiences. Additionally, participants completed questionnaires about their turnover intention and perceived stress. The interviews were examined with narrative psychological content analysis and thematic analyzes. Based on the thematic analysis, mentioning of two topics (recognition at work and control) were associated with Machiavellianism. Scientific narrative psychological content analysis showed a negative association between Machiavellianism and positive emotions. Turnover intention and the magnitude of perceived work-related stress showed a significant positive correlation with Machiavellianism. In this study, qualitative and quantitative methodologies were combined in order to get a deeper insight of Machiavellianism from an organizational psychological perspective. Our research can contribute to a better understanding of this personality trait and provides an excellent basis for further investigations.

Keywords: machiavellianism, narrative psychology, turnover intention, work-related stress

Procedia PDF Downloads 134

Authors: Michael Mederle, Heinz Bernhardt

Abstract:

The Management of machine fleets or autonomous vehicle control will considerably increase efficiency in future agricultural production. Especially entire process chains, e.g. harvesting complexes with several interacting combine harvesters, grain carts, and removal trucks, provide lots of optimization potential. Organization and pre-planning ensure to get these efficiency reserves accessible. One way to achieve this is to optimize infield path planning. Particularly autonomous machinery requires precise specifications about infield logistics to be navigated effectively and process optimized in the fields individually or in machine complexes. In the past, a lot of theoretical optimization has been done regarding infield logistics, mainly based on field geometry. However, there are reasons why farmers often do not apply the infield strategy suggested by mathematical route planning tools. To make the computational optimization more useful for farmers this study focuses on these influencing factors by expert interviews. As a result practice-oriented navigation not only to the field but also within the field will be possible. The survey study is intended to cover the entire range of German agriculture. Rural mixed farms with simple technology equipment are considered as well as large agricultural cooperatives which farm thousands of hectares using track guidance and various other electronic assistance systems. First results show that farm managers using guidance systems increasingly attune their infield-logistics on direction giving obstacles such as power lines. In consequence, they can avoid inefficient boom flippings while doing plant protection with the sprayer. Livestock farmers rather focus on the application of organic manure with its specific requirements concerning road conditions, landscape terrain or field access points. Cultivation of sugar beets makes great demands on infield patterns because of its particularities such as the row crop system or high logistics demands. Furthermore, several machines working in the same field simultaneously influence each other, regardless whether or not they are of the equal type. Specific infield strategies always are based on interactions of several different influences and decision criteria. Single working steps like tillage, seeding, plant protection or harvest mostly cannot be considered each individually. The entire production process has to be taken into consideration to detect the right infield logistics. One long-term objective of this examination is to integrate the obtained influences on infield strategies as decision criteria into an infield navigation tool. In this way, path planning will become more practical for farmers which is a basic requirement for automatic vehicle control and increasing process efficiency.

Keywords: autonomous vehicle control, infield logistics, path planning, process optimizing

Procedia PDF Downloads 233

Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

Abstract:

The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

Procedia PDF Downloads 107

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

Abstract:

Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

Procedia PDF Downloads 123

Authors: Yekini N. Asafe, Haastrup A. Victor, Lawal N. Olawale, Okikiola F. Mercy

Abstract:

Recent increase in access to personal computer and networking systems have made it feasible to perform much of cumbersome and costly paper-based administration in all organization. Desktop computers, networking systems, high capacity storage devices and telecommunications system is currently allowing the transfer of various format of data to be processed, stored and dissemination for the purpose of decision making. Going paperless is more of benefits compare to full paper-based office. This paper proposed a model for design and implementation of e-administration system (paperless campus) for an institution of learning. If this model is design and implemented it will reduced cost and complexity of educational administration also eliminate menaces and environmental hazards attributed to paper-based administration within schools and colleges.

Keywords: e-administration, educational administration, paperless campus, paper-based administration

Procedia PDF Downloads 379

Authors: Bassant Eyada, Hanan Atef Kamal Eldin

Abstract:

Advertising has witnessed a diffusion and development in technology to promote products and services, increasingly relying on the interactivity between the consumer and the advertisement. Consumers seek, self-select, process, use and respond to the information provided, hence, providing the potential to increase consumers’ efficiency, involvement, trustworthiness, response, and satisfaction towards the advertised product or service. The power of interactive personalized messages shifts the focus of traditional advertising to more concentrated consumers, sending out tailored messages with more specific individual needs and preferences, defining the importance and relevance that consumers attach to the advertisement, therefore, enhancing the ability to persuade, and the quality of decision making. In this paper, the researchers seek to discuss and explore innovative interactive advertising, its’ effectiveness on consumers and the benefits the advertisements provide, through designing an interactive ad to be placed at the international airports promoting tourism in Egypt.

Keywords: advertising, effectiveness, interactivity, Egypt

Procedia PDF Downloads 316

Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

Abstract:

Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM

Procedia PDF Downloads 190

Authors: Sasala Taiban

Abstract:

This paper explores the process and reflections on the restoration of traditional slate houses in the Rukai tribe's old settlement of Kucapungane. Designated as a "Class II Historical Site" by the Ministry of the Interior in 1991 and listed by UNESCO's World Monuments Fund in 2016, Kucapungane holds significant historical and cultural value. However, due to government neglect, tribal migration, and the passing of elders, the traditional knowledge and techniques for constructing slate houses face severe discontinuity. Over the past decades, residents have strived to preserve and transmit these traditional skills through the restoration and reconstruction of their homes. This study employs a qualitative methodology, combining ethnographic fieldwork, historical analysis, and participatory observation. The research includes in-depth interviews, focus group discussions, and hands-on participation in restoration activities to gather comprehensive data. The paper reviews the historical evolution of Kucapungane, the restoration process, and the challenges encountered, such as insufficient resources, technical preservation issues, material acquisition problems, and lack of community recognition. Furthermore, it highlights the importance of house restoration in indigenous consciousness and cultural revival, proposing strategies to address current issues and promote preservation. Through these efforts, the cultural heritage of the Rukai tribe can be sustained and carried forward into the future.

Keywords: rukai, kucapungane, slate house restoration, cultural heritage

Procedia PDF Downloads 37

Authors: Syarif Hidayat

Abstract:

As millions of people with different backgrounds perform hajj every year in Saudi Arabia, it brings out several problems. Missing people is among many crucial problems need to be encountered. Some people might have had insufficient knowledge of using tracking system equipment. Other might become a victim of an accident, lose consciousness, or even died, prohibiting them to perform certain activity. For those reasons, people could not send proper SOS message. The major contribution of this paper is the application of the diverse alert method in pilgrims tracking system. It offers a simple yet robust solution to send SOS message by pilgrims during Hajj. Knowledge of context aware computing is assumed herein. This study presents four methods that could be utilized by pilgrims to send SOS. The first method is simple mobile application contains only a button. The second method is based on behavior analysis based off GPS location movement anomaly. The third method is by introducing pressing pattern to smartwatch physical button as a panic button. The fourth method is by identifying certain accelerometer pattern recognition as a sign of emergency situations. Presented method in this paper would be an important part of pilgrims tracking system. The discussion provided here includes easy to use design whilst maintaining tracking accuracy, privacy, and security of its users.

Keywords: context aware computing, emergency alert system, GPS, hajj pilgrim tracking, location-based services

Procedia PDF Downloads 216

Authors: Ouzayr Rabhi, Ibtissam Arrassen

Abstract:

To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

Procedia PDF Downloads 160

Authors: Ayman M. Mansour

Abstract:

In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: fuzzy logic, inference system, monitoring system, multi-agent system

Procedia PDF Downloads 608

Authors: Kolade Olawande Owoeye, George R. S. Weir

Abstract:

The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

Procedia PDF Downloads 145

Authors: Andrew Ka Pok Tam

Abstract:

Kierkegaard has been misinterpreted as an anti-social philosopher for a long time until in recent years when there are more discussions on his concept of community in Journals and Papers inspired by Karl Bayer. Community which is based upon an individual's relations to others is different from the crowd or the public where the numerical or the majority make decisions. As a result, authenticity is only possible in the community. But Kierkegaard did not explain how we can preserve the individual's authenticity by establishing a community instead of a public in the reality. Kierkegaard was against the democratic reform in 1848 Denmark because he thought all elections mean the majority wins and the authenticity of a single individual would be suppressed. However, Kierkegaard himself does not suggest an alternative political system that may preserve the authenticity of individual. This paper aims to evaluate the possibility for us to establish a Kierkegaadian community in practice so as to preserve every individual's authenticity. This paper argues that the practicality of Kierekegaadian community is limited. In order to have effective communications and relations among individuals, a Kierkegaardian community must be small and inefficient as every individual's must remain authentic in all political decision for the whole community.

Keywords: authenticity, community, individual, kierkegaard

Procedia PDF Downloads 361

Authors: Fahimeh Hooshyar, Seyyed Mojtaba Abtahi

Abstract:

Democracy which is, in its greek roots, consisted of “Demo” (People) and “Kratic” (people) is referring to governing of the people or governing by the people. in its widest definition it refers to a common lifestyle in which all the people has the equal potentials for social participating. But in political perspective, democracy is looking for the equal participation right of the citizens in political decision-making process. in this viewpoint, the democracy is solely a political construct or a social-political style in which all the values are relative. In this definition of the democracy emphasis is on equality of the people based on the governing rule and the natural social and political rights of every member of humankind. This notion of democracy by no means is a self reliant idea and the need of an ideological basis for approaching to this idea is inevitable. In this paper we are trying to define the inter-relations of democracy and its philosophical basis to Islamic fundamental ideas. Our approach to this topic would be a philosophical ideological one.

Keywords: Islam, democracy, democracy’s philosophical basis, secularism, fundamentalism

Procedia PDF Downloads 446

Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

Abstract:

The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

Procedia PDF Downloads 463

Authors: Dana Kristalova

Abstract:

This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

Procedia PDF Downloads 462

Authors: Zahow Muoftah

Abstract:

Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

Procedia PDF Downloads 106

Authors: Shamsu Abdullahi, Nazir Yusuf, Hazrina Sofian, Abubakar Zakari, Amina Nura, Salisu Suleiman

Abstract:

Requirements negotiation process models help in resolving conflicting requirements of the heterogeneous stakeholders in the software development industry. This is to achieve a shared vision of software projects to be developed by the industry. Negotiating stakeholder agreements is a serious and difficult task in the software development process. There are many requirements negotiation process models that effectively negotiate stakeholder agreements that have been proposed by the research community. Other issues in the requirements negotiation research domain include stakeholder communication, decision-making, lack of negotiation interoperability, and managing requirement changes and analysis. This study highlights the current state of the art in the existing software requirements negotiation process models. The study also describes the issues and limitations in the software requirements negotiations process models.

Keywords: requirements, negotiation, stakeholders, agreements

Procedia PDF Downloads 197

Authors: Laxuman Thakuri

Abstract:

Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

Procedia PDF Downloads 536

Authors: Veli Durmus, Mert Uydaci

Abstract:

Every patient who needs to get a medical treatment should share health-related personal data with healthcare providers. Therefore, personal health data plays an important role to make health decisions and identify health threats during every encounter between a patient and caregivers. In other words, health data can be defined as privacy and sensitive information which is protected by various health laws and regulations. In many cases, the data are an outcome of the confidential relationship between patients and their healthcare providers. Globally, almost all nations have own laws, regulations or rules in order to protect personal data. There is a variety of instruments that allow authorities to use the health data or to set the barriers data sharing across international borders. For instance, Directive 95/46/EC of the European Union (EU) (also known as EU Data Protection Directive) establishes harmonized rules in European borders. In addition, the General Data Protection Regulation (GDPR) will set further common principles in 2018. Because of close policy relationship with EU, this study provides not only information on regulations, directives but also how they play a role during the legislative process in Turkey. Even if the decision is controversial, the Board has recently stated that private or public healthcare institutions are responsible for the patient call system, for doctors to call people waiting outside a consultation room, to prevent unlawful processing of personal data and unlawful access to personal data during the treatment. In Turkey, vast majority private and public health organizations provide a service that ensures personal data (i.e. patient’s name and ID number) to call the patient. According to the Board’s decision, hospital or other healthcare institutions are obliged to take all necessary administrative precautions and provide technical support to protect patient privacy. However, this application does not effectively and efficiently performing in most health services. For this reason, it is important to draw a legal framework of personal health data by stating what is the main purpose of this regulation and how to deal with complicated issues on personal health data in Turkey. The research is descriptive on data protection law for health care setting in Turkey. Primary as well as secondary data has been used for the study. The primary data includes the information collected under current national and international regulations or law. Secondary data include publications, books, journals, empirical legal studies. Consequently, privacy and data protection regimes in health law show there are some obligations, principles and procedures which shall be binding upon natural or legal persons who process health-related personal data. A comparative approach presents there are significant differences in some EU member states due to different legal competencies, policies, and cultural factors. This selected study provides theoretical and practitioner implications by highlighting the need to illustrate the relationship between privacy and confidentiality in Personal Data Protection in Health Law. Furthermore, this paper would help to define the legal framework for the health law case studies on data protection and privacy.

Keywords: data protection, personal data, privacy, healthcare, health law

Procedia PDF Downloads 224