Search results for: learning using labeled and unlabelled data
7540 Non Inmersive Virtual Reality for Improving Teaching Processes
Authors: Galeano R. Katherine, Rincon L. David, Luengas. Lely, Guevara. Juan Carlos
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The following paper shows an interactive tool which main purpose is to teach how to play a flute. It consists of three stages the first one is the instruction and teaching process through a software application, the second is the practice part when the user starts to play the flute (hardware specially designed for this application) this flute is capable of capturing how is being played the flute and the final stage is the one in which the data captured are sent to the software and the user is evaluated in order to give him / she a correction or an acceptanceKeywords: acoustoelectric devices, computer applications, learning systems, music, technological innovation, virtual reality
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16297539 Higher Plants Ability to Assimilate Explosives
Authors: G. Khatisashvili, M. Gordeziani, G. Adamia, E. Kvesitadze, T. Sadunishvili, G. Kvesitadze
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The ability of agricultural and decorative plants to absorb and detoxify TNT and RDX has been studied. All tested 8 plants, grown hydroponically, were able to absorb these explosives from water solutions: Alfalfa > Soybean > Chickpea> Chikling vetch >Ryegrass > Mung bean> China bean > Maize. Differently from TNT, RDX did not exhibit negative influence on seed germination and plant growth. Moreover, some plants, exposed to RDX containing solution were increased in their biomass by 20%. Study of the fate of absorbed [1-14ðí]-TNT revealed the label distribution in low and high-molecular mass compounds, both in roots and above ground parts of plants, prevailing in the later. Content of 14ðí in lowmolecular compounds in plant roots are much higher than in above ground parts. On the contrary, high-molecular compounds are more intensively labeled in aboveground parts of soybean. Most part (up to 70%) of metabolites of TNT, formed either by enzymatic reduction or oxidation, is found in high molecular insoluble conjugates. Activation of enzymes, responsible for reduction, oxidation and conjugation of TNT, such as nitroreductase, peroxidase, phenoloxidase and glutathione S-transferase has been demonstrated. Among these enzymes, only nitroreductase was shown to be induced in alfalfa, exposed to RDX. The increase in malate dehydrogenase activities in plants, exposed to both explosives, indicates intensification of Tricarboxylic Acid Cycle, that generates reduced equivalents of NAD(P)H, necessary for functioning of the nitroreductase. The hypothetic scheme of TNT metabolism in plants is proposed.Keywords: Higher plants, TNT, RDX, transformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17167538 Efficient Web-Learning Collision Detection Tool on Five-Axis Machine
Authors: Chia-Jung Chen, Rong-Shine Lin, Rong-Guey Chang
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As networking has become popular, Web-learning tends to be a trend while designing a tool. Moreover, five-axis machining has been widely used in industry recently; however, it has potential axial table colliding problems. Thus this paper aims at proposing an efficient web-learning collision detection tool on five-axis machining. However, collision detection consumes heavy resource that few devices can support, thus this research uses a systematic approach based on web knowledge to detect collision. The methodologies include the kinematics analyses for five-axis motions, separating axis method for collision detection, and computer simulation for verification. The machine structure is modeled as STL format in CAD software. The input to the detection system is the g-code part program, which describes the tool motions to produce the part surface. This research produced a simulation program with C programming language and demonstrated a five-axis machining example with collision detection on web site. The system simulates the five-axis CNC motion for tool trajectory and detects for any collisions according to the input g-codes and also supports high-performance web service benefiting from C. The result shows that our method improves 4.5 time of computational efficiency, comparing to the conventional detection method.
Keywords: Collision detection, Five-axis machining, Separating axis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21867537 Spatial Econometric Approaches for Count Data: An Overview and New Directions
Authors: Paula Simões, Isabel Natário
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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.Keywords: Spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27137536 Age and Second Language Acquisition: A Case Study from Maldives
Authors: Aaidha Hammad
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The age a child to be exposed to a second language is a controversial issue in communities such as the Maldives where English is taught as a second language. It has been observed that different stakeholders have different viewpoints towards the issue. Some believe that the earlier children are exposed to a second language, the better they learn, while others disagree with the notion. Hence, this case study investigates whether children learn a second language better when they are exposed at an earlier age or not. The spoken and written data collected confirm that earlier exposure helps in mastering the sound pattern and speaking fluency with more native-like accent, while a later age is better for learning more abstract and concrete aspects such as grammar and syntactic rules.Keywords: Age, development of language skills, fluency, second language acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36547535 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine
Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour
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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.
Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12477534 MATLAB-Based Graphical User Interface (GUI) for Data Mining as a Tool for Environment Management
Authors: M. Awawdeh, A. Fedi
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The application of data mining to environmental monitoring has become crucial for a number of tasks related to emergency management. Over recent years, many tools have been developed for decision support system (DSS) for emergency management. In this article a graphical user interface (GUI) for environmental monitoring system is presented. This interface allows accomplishing (i) data collection and observation and (ii) extraction for data mining. This tool may be the basis for future development along the line of the open source software paradigm.
Keywords: Data Mining, Environmental data, Mathematical Models, Matlab Graphical User Interface.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47467533 Educase – Intelligent System for Pedagogical Advising Using Case-Based Reasoning
Authors: Elionai Moura, José A. da Cunha, César Analide
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This paper introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.
Keywords: Case-based Reasoning, Pedagogical Advising, Educational Data-Mining (EDM), Machine Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20907532 Experimental Studies of Position Control of Linkage based Robotic Finger
Authors: N. Z. Azlan, H. Yamaura
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The experimental study of position control of a light weight and small size robotic finger during non-contact motion is presented in this paper. The finger possesses fingertip pinching and self adaptive grasping capabilities, and is made of a seven bar linkage mechanism with a slider in the middle phalanx. The control system is tested under the Proportional Integral Derivative (PID) control algorithm and Recursive Least Square (RLS) based Feedback Error Learning (FEL) control scheme to overcome the uncertainties present in the plant. The experiments conducted in Matlab Simulink and xPC Target environments show that the overall control strategy is efficient in controlling the finger movement.Keywords: Anthropomorphic finger, position control, feedback error learning, experimental study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15847531 Combining the Deep Neural Network with the K-Means for Traffic Accident Prediction
Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota
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Understanding the causes of a road accident and predicting their occurrence is key to prevent deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.
Keywords: Accident risks estimation, artificial neural network, deep learning, K-mean, road safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9977530 Hearing Aids Maintenance Training for Hearing-Impaired Preschool Children with the Help of Motion Graphic Tools
Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz
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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.
Keywords: Hearing-impaired children, hearing aids, hearing aids maintenance skill, and motion graphics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5917529 Principal Component Analysis using Singular Value Decomposition of Microarray Data
Authors: Dong Hoon Lim
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A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.
Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32577528 Knowledge Reactor: A Contextual Computing Work in Progress for Eldercare
Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams
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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.Keywords: Ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10527527 A Laboratory Assistance Module
Authors: Konstantinos E. Evangelidis, Evangelos Kehris, Theodore H. Kaskalis
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We propose that Virtual Learning Environments (VLEs) should be designed by taking into account the characteristics, the special needs and the specific operating rules of the academic institutions in which they are employed. In this context, we describe a VLE module that extends the support of the organization and delivery of course material by including administration activities related to the various stages of teaching. These include the co-ordination, collaboration and monitoring of the course material development process and institution-specific course material delivery modes. Our specialized module, which enhances VLE capabilities by Helping Educators and Learners through a Laboratory Assistance System, is willing to assist the Greek tertiary technological sector, which includes Technological Educational Institutes (T.E.I.).Keywords: Virtual learning environments, Teachingcoordination, Laboratorial education, Technological institutes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13757526 The Potential Benefits of Multimedia Information Representation in Enhancing Students’ Critical Thinking and History Reasoning
Authors: Ang Ling Weay, Mona Masood
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This paper discusses the potential benefits of an interactive multimedia information representation in enhancing students’ critical thinking aligned with history reasoning in learning history amongst Secondary School students in Malaysia. Two modes of multimedia information representation were implemented; chronologic and thematic information representations. A qualitative study of an unstructured interview was conducted among two history teachers, one history education lecturer, two i-think experts, and five students from Form Four secondary school. The interview was to elicit their opinions on the implementation of thinking maps and interactive multimedia information representation in history learning. The key elements of the interactive multimedia (e.g. multiple media, user control, interactivity and use of timelines and concept maps) were then considered to improve the learning process. Findings of the preliminary investigation reveal that the interactive multimedia information representations have the potential benefits to be implemented as an instructional resource in enhancing students’ higher order thinking skills (HOTs). This paper concludes by giving suggestions for future work.
Keywords: Multimedia Information Representation, Critical Thinking, History Reasoning, Chronological and Thematic Information Representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23987525 Changes in Behavior and Learning Ability of Rats Intoxicated with Lead
Authors: Amira, A. Goma, U. E. Mahrous
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Measuring the effect of perinatal lead exposure on learning ability of offspring is considered as a sensitive and selective index for providing an early marker for central nervous system damage produced by this toxic metal. A total of 35 Sprague-Dawley adult rats were used to investigate the effect of lead acetate toxicity on behavioral patterns of adult female rats and learning ability of offspring. Rats were allotted into 4 groups, group one received 1g/l lead acetate (n=10), group two received 1.5g/l lead acetate (n=10), group three received 2g/l lead acetate in drinking water (n=10) and control group did not receive lead acetate (n=5) from 8th day of pregnancy till weaning of pups.
The obtained results revealed a dose dependent increase in the feeding time, drinking frequency, licking frequency, scratching frequency, licking litters, nest building and retrieving frequencies, while standing time increased significantly in rats treated with 1.5g/l lead acetate than other treated groups and control, on contrary lying time decreased gradually in a dose dependent manner. Moreover, movement activities were higher in rats treated with 1g/l lead acetate than other treated groups and control. Furthermore, time spent in closed arms was significantly lower in rats given 2g/l lead acetate than other treated groups, while, they spent significantly much time spent in open arms than other treated groups which could be attributed to occurrence of adaptation. Furthermore, number of entries in open arms was dose dependent. However, the ratio between open/closed arms revealed a significant decrease in rats treated with 2g/l lead acetate than control group.
Keywords: Lead toxicity, rats, learning ability, behavior.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26937524 Clustering Mixed Data Using Non-normal Regression Tree for Process Monitoring
Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek
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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17877523 Dialogue Meetings as an Arena for Collaboration and Reflection among Researchers and Practitioners
Authors: Kerstin Grunden, Ann Svensson, Berit Forsman, Christina Karlsson, Ayman Obeid
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The research question of the article is to explore whether the dialogue meetings method could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in municipalities, or not. A testbed was planned to be implemented in a retirement home in a Swedish municipality, and the practitioners worked with a pre-study of that testbed. In the article, the dialogue between the researchers and the practitioners in the dialogue meetings is described and analyzed. The potential of dialogue meetings as an arena for learning and reflection among researchers and practitioners is discussed. The research methodology approach is participatory action research with mixed methods (dialogue meetings, focus groups, participant observations). The main findings from the dialogue meetings were that the researchers learned more about the use of traditional research methods, and the practitioners learned more about how they could improve their use of the methods to facilitate change processes in their organization. These findings have the potential both for the researchers and the practitioners to result in more relevant use of research methods in change processes in organizations. It is concluded that dialogue meetings could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in a health care organization.Keywords: Dialogue meetings, implementation, reflection, test bed, welfare technology, participatory action research.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4757522 Harnessing the Power of AI: Transforming DevSecOps for Enhanced Cloud Security
Authors: Ashly Joseph, Jithu Paulose
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The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.
Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1727521 Speech Data Compression using Vector Quantization
Authors: H. B. Kekre, Tanuja K. Sarode
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Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24087520 Ontology and CDSS Based Intelligent Health Data Management in Health Care Server
Authors: Eun-Jung Ko, Hyung-Jik Lee, Jeun-Woo Lee
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In ubiqutious healthcare environment, user's health data are transfered to the remote healthcare server by the user's wearable system or mobile phone. These collected user's health data should be managed and analyzed in the healthcare server, so that care giver or user can monitor user's physiological state. In this paper, we designed and developed the intelligent Healthcare Server to manage the user's health data using CDSS and ontology. Our system can analyze user's health data semantically using CDSS and ontology, and report the result of user's physiological raw data to the user and care giver.
Keywords: u-healthcare, CDSS, healthcare server, health data, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22407519 A Genetic Algorithm for Clustering on Image Data
Authors: Qin Ding, Jim Gasvoda
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Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.
Keywords: Clustering, data mining, genetic algorithm, image data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20607518 A Holistic Framework for Unifying Data Security and Management in Modern Enterprises
Authors: Ashly Joseph
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Modern businesses struggle significantly to secure and manage their data properly as the volume and complexity of their data both expand exponentially. Through the use of a multi-layered defense strategy, a centralized management platform, and cutting-edge technologies like AI, this research paper presents a comprehensive framework to integrate data security and management. The constraints of current data protection and management strategies, technological advancements, and the evolving threat landscape are all examined in this article. It suggests best practices for putting into practice integrated data security and governance models, placing an emphasis on ongoing adaptation. The advantages mentioned include a strengthened security posture, simpler procedures, lower costs, and reduced complexity. Additionally, issues including skill shortages, antiquated systems, and cultural obstacles are examined. Security executives and Chief Information Security Officers are given practical advice on how to evaluate, plan, and put into place strong data-centric security and management capabilities. The goal of the paper is to provide a thorough study of the data security and management landscape and to arm contemporary businesses with the knowledge they need to be proactive in protecting their data assets.
Keywords: Data security, security management, cloud computing, cybersecurity, data governance, security architecture, data management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2997517 Acquiring Contour Following Behaviour in Robotics through Q-Learning and Image-based States
Authors: Carlos V. Regueiro, Jose E. Domenech, Roberto Iglesias, Jose L. Correa
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In this work a visual and reactive contour following behaviour is learned by reinforcement. With artificial vision the environment is perceived in 3D, and it is possible to avoid obstacles that are invisible to other sensors that are more common in mobile robotics. Reinforcement learning reduces the need for intervention in behaviour design, and simplifies its adjustment to the environment, the robot and the task. In order to facilitate its generalisation to other behaviours and to reduce the role of the designer, we propose a regular image-based codification of states. Even though this is much more difficult, our implementation converges and is robust. Results are presented with a Pioneer 2 AT on a Gazebo 3D simulator.Keywords: Image-based State Codification, Mobile Robotics, ReinforcementLearning, Visual Behaviour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16187516 Islamic Education System: Implementation of Curriculum Kuttab Al-Fatih Semarang
Authors: Basyir Yaman, Fades Br. Gultom
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The picture and pattern of Islamic education in the Prophet's period in Mecca and Medina is the history of the past that we need to bring back. The Basic Education Institute called Kuttab. Kuttab or Maktab comes from the word kataba which means to write. The popular Kuttab in the Prophet’s period aims to resolve the illiteracy in the Arab community. In Indonesia, this Institution has 25 branches; one of them is located in Semarang (i.e. Kuttab Al-Fatih). Kuttab Al-Fatih as a non-formal institution of Islamic education is reserved for children aged 5-12 years. The independently designed curriculum is a distinctive feature that distinguishes between Kuttab Al-Fatih curriculum and the formal institutional curriculum in Indonesia. The curriculum includes the faith and the Qur’an. Kuttab Al-Fatih has been licensed as a Community Activity Learning Center under the direct supervision and guidance of the National Education Department. Here, we focus to describe the implementation of curriculum Kuttab Al-Fatih Semarang (i.e. faith and al-Qur’an). After that, we determine the relevance between the implementation of the Kuttab Al-Fatih education system with the formal education system in Indonesia. This research uses literature review and field research qualitative methods. We obtained the data from the head of Kuttab Al-Fatih Semarang, vice curriculum, faith coordinator, al-Qur’an coordinator, as well as the guardians of learners and the learners. The result of this research is the relevance of education system in Kuttab Al-Fatih Semarang about education system in Indonesia. Kuttab Al-Fatih Semarang emphasizes character building through a curriculum designed in such a way and combines thematic learning models in modules.
Keywords: Islamic education system, implementation of curriculum, Kuttab Al-Fatih semarang, formal education system in Indonesia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13127515 Post Mining- Discovering Valid Rules from Different Sized Data Sources
Authors: R. Nedunchezhian, K. Anbumani
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A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.
Keywords: Association rules, multiple data stores, synthesizing, valid rules.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14077514 Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Disease
Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang
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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.
Keywords: Alzheimer’s disease, Speech Emotion Recognition, longitudinal biomarker, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3047513 RFID-ready Master Data Management for Reverse Logistics
Authors: Jincheol Han, Hyunsun Ju, Jonghoon Chun
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Sharing consistent and correct master data among disparate applications in a reverse-logistics chain has long been recognized as an intricate problem. Although a master data management (MDM) system can surely assume that responsibility, applications that need to co-operate with it must comply with proprietary query interfaces provided by the specific MDM system. In this paper, we present a RFID-ready MDM system which makes master data readily available for any participating applications in a reverse-logistics chain. We propose a RFID-wrapper as a part of our MDM. It acts as a gateway between any data retrieval request and query interfaces that process it. With the RFID-wrapper, any participating applications in a reverse-logistics chain can easily retrieve master data in a way that is analogous to retrieval of any other RFID-based logistics transactional data.Keywords: Reverse Logistics, Master Data Management, RFID.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19807512 Dynamic Models versus Frailty Models for Recurrent Event Data
Authors: Entisar A. Elgmati
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Recurrent event data is a special type of multivariate survival data. Dynamic and frailty models are one of the approaches that dealt with this kind of data. A comparison between these two models is studied using the empirical standard deviation of the standardized martingale residual processes as a way of assessing the fit of the two models based on the Aalen additive regression model. Here we found both approaches took heterogeneity into account and produce residual standard deviations close to each other both in the simulation study and in the real data set.Keywords: Dynamic, frailty, misspecification, recurrent events.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23557511 A BERT-Based Model for Financial Social Media Sentiment Analysis
Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe
Abstract:
The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural Language Processing (NLP) in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.
Keywords: BERT, financial markets, Twitter, sentiment analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 748