Search results for: behavioural user profiling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2717

Search results for: behavioural user profiling

2357 Interactive Winding Geometry Design of Power Transformers

Authors: Paffrath Meinhard, Zhou Yayun, Guo Yiqing, Ertl Harald

Abstract:

Winding geometry design is an important part of power transformer electrical design. Conventionally, the winding geometry is designed manually, which is a time-consuming job because it involves many iteration steps in order to meet all cost, manufacturing and electrical requirements. Here a method is presented which automatically generates the winding geometry for given user parameters and allows the user to interactively set and change parameters. To achieve this goal, the winding problem is transferred to a mixed integer nonlinear optimization problem. The relevant geometrical design parameters are defined as optimization variables. The cost and other requirements are modeled as constraints. For the solution, a stochastic ant colony optimization algorithm is applied. It is well-known, that an optimizer can get stuck in a local minimum. For the winding problem, we present efficient strategies to come out of local minima, furthermore a reduced variable search range helps to accelerate the solution process. Numerical examples show that the optimization result is delivered within seconds such that the user can interactively change the variable search area and constraints to improve the design.

Keywords: ant colony optimization, mixed integer nonlinear programming, power transformer, winding design

Procedia PDF Downloads 373
2356 Human Computer Interaction Using Computer Vision and Speech Processing

Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

Abstract:

Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

Procedia PDF Downloads 354
2355 CFD Simulation for Development of Cooling System in a Cooking Oven

Authors: V. Jagadish, Mathiyalagan V.

Abstract:

Prediction of Door Touch temperature of a Cooking Oven using CFD Simulation. Self-Clean cycle is carried out in Cooking ovens to convert food spilling into ashes which makes cleaning easy. During this cycle cavity of oven is exposed to high temperature around 460 C. At this operating point the user may prone to touch the Door surfaces, Side Shield, Control Panel. To prevent heat experienced by user, cooling system is built in oven. The most effective cooling system is developed with existing design constraints through CFD Simulations. Cross Flow fan is used for Cooling system due to its cost effectiveness and it can give more air flow with low pressure drop.

Keywords: CFD, MRF, RBM, RANS, new product development, simulation, thermal analysis

Procedia PDF Downloads 147
2354 Dietary Intakes and Associated Demographic, Behavioural and Other Health-Related Factors in Mexican College Students

Authors: Laura E. Hall, Joel Monárrez-Espino, Luz María Tejada Tayabas

Abstract:

College students are at risk of weight gain and poor dietary habits, and health behaviours established during this period have been shown to track into midlife. They may therefore be an important target group for health promotion strategies, yet there is a lack of literature regarding dietary intakes and associated factors in this group, particularly in middle-income countries such as Mexico. The aim of this exploratory research was to describe and compare reported dietary intakes among nursing and nutrition college students at two public universities in Mexico, and to explore the relationship between demographic, behavioural and other health-related factors and the risk of low diet quality. Mexican college students (n=444) majoring in nutrition or nursing at two urban universities completed questionnaires regarding dietary and health-related behaviours and risks. Dietary intake was assessed via 24-hour recall. Weight, height and abdominal circumference were measured. Descriptive statistics were reported and nutrient intakes were compared between colleges and study tracks using Student’s t tests, odds ratios and Pearson chi square tests. Two dietary quality scores were constructed to explore the relationship between demographic, behavioural and other health-related factors and the diet quality scores using binary logistic regression. Analysis was performed using SPSS statistics, with differences considered statistically significant at p<0.05. The response rate to the survey was 91%. When macronutrients were considered as a percentage of total energy, the majority of students had protein intakes within recommended ranges, however one quarter of students had carbohydrate and fat intakes exceeding recommended levels. Three quarters had fibre intakes that were below recommendations. More than half of the students reported intakes of magnesium, zinc, vitamin A, folate and vitamin E that were below estimated average requirements. Students studying nutrition reported macronutrient and micronutrient intakes that were more compliant with recommendations compared to nursing students, and students studying in central-north Mexico were more compliant than those studying in southeast Mexico. Breakfast skipping (Adjusted Odds Ratio (OR) = 5.3; 95% Confidence Interval (CI) = 1.2-22.7), risk of anxiety (OR = 2.3; CI = 1.3-4.4), and university location (OR = 1.6; CI = 1.03-2.6) were associated with a greater risk of having a low macronutrient score. Caloric intakes <1800kcal (OR = 5.8; CI = 3.5-9.7), breakfast skipping (OR = 3.7; CI = 1.4-10.3), vigorous exercise ≤1h/week (OR = 2.6; CI = 1.3-5.2), soda consumption >250mls/day (OR = 2.0; CI = 1.2-3.3), unhealthy diet perception (OR = 1.9; CI = 1.2-3.0), and university location (OR = 1.8; CI = 1.1-2.8) were significantly associated with greater odds of having a low micronutrient score. College students studying nursing and nutrition did not report ideal diets, and these students should not be overlooked in public health interventions. Differences in dietary intakes between universities and study tracks were evident, with more favourable profiles evident in nutrition compared to nursing, and North-central compared to Southeast students. Further, demographic, behavioural and other health-related factors were associated with diet quality scores, warranting further research.

Keywords: college student, diet quality, nutrient intake, young adult

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2353 Consumer Behaviour Model for Apparel E-Tailers Using Structural Equation Modelling

Authors: Halima Akhtar, Abhijeet Chandra

Abstract:

The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

Procedia PDF Downloads 172
2352 Development of a Hamster Knowledge System Based on Android Application

Authors: Satien Janpla, Thanawan Boonpuck, Pattarapan Roonrakwit

Abstract:

In this paper, we present a hamster knowledge system based on android application. The objective of this system is to advice user to upkeep and feed hamsters based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on knowledge based of hamster experts. The results were divided by the research purposes into 2 parts: developing the mobile application for advice users and testing and evaluating the system. Black box technique was used to evaluate application performances and questionnaires were applied to measure user satisfaction with system usability by specialists and users.

Keywords: hamster knowledge, Android application, black box, questionnaires

Procedia PDF Downloads 327
2351 Profiling of Apoptotic Protein Expressions after Trabectedin Treatment in Human Prostate Cancer Cell Line PC-3 by Protein Array Technology

Authors: Harika Atmaca, Emir Bozkurt, Latife Merve Oktay, Selim Uzunoglu, Ruchan Uslu, Burçak Karaca

Abstract:

Microarrays have been developed for highly parallel enzyme-linked immunosorbent assay (ELISA) applications. The most common protein arrays are produced by using multiple monoclonal antibodies, since they are robust molecules which can be easily handled and immobilized by standard procedures without loss of activity. Protein expression profiling with protein array technology allows simultaneous analysis of the protein expression pattern of a large number of proteins. Trabectedin, a tetrahydroisoquinoline alkaloid derived from a Caribbean tunicate, Ecteinascidia turbinata, has been shown to have antitumor effects. Here, we used a novel proteomic approach to explore the mechanism of action of trabectedin in prostate cancer cell line PC-3 by apoptosis antibody microarray. XTT cell proliferation kit and Cell Death Detection Elisa Plus Kit (Roche) was used for measuring cytotoxicity and apoptosis. Human Apoptosis Protein Array (R&D Systems) which consists of 35 apoptosis related proteins was used to assess the omic protein expression pattern. Trabectedin induced cytotoxicity and apoptosis in prostate cancer cells in a time and concentration-dependent manner. The expression levels of the death receptor pathway molecules, TRAIL-R1/DR4, TRAIL R2/DR5, TNF R1/TNFRSF1A, FADD were significantly increased by 4.0-, 21.0-, 4.20- and 11.5-fold by trabectedin treatment in PC-3 cells. Moreover, mitochondrial pathway related pro-apoptotic proteins Bax, Bad, Cytochrome c, and Cleaved Caspase-3 expressions were induced by 2.68-, 2.07-, 2.8-, and 4.5-fold and the expression levels of anti-apoptotic proteins Bcl-2 and Bcl-XL were reduced by 3.5- and 5.2-fold in PC-3 cells. Proteomic (antibody microarray) analysis suggests that the mechanism of action of trabectedin may be exerted via the induction of both intrinsic and extrinsic apoptotic pathways. The antibody microarray platform can be utilised to explore the molecular mechanism of action of novel anticancer agents.

Keywords: trabectedin, prostate cancer, omic protein expression profile, apoptosis

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2350 Implementing a Database from a Requirement Specification

Authors: M. Omer, D. Wilson

Abstract:

Creating a database scheme is essentially a manual process. From a requirement specification, the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time-consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that the first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore, this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: information extraction, natural language processing, relation extraction

Procedia PDF Downloads 251
2349 Spectral Analysis Applied to Variables of Oil Wells Profiling

Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

Abstract:

Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

Procedia PDF Downloads 523
2348 Design and Implementation of a Software Platform Based on Artificial Intelligence for Product Recommendation

Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

Abstract:

Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

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2347 Exploring the Activity Fabric of an Intelligent Environment with Hierarchical Hidden Markov Theory

Authors: Chiung-Hui Chen

Abstract:

The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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2346 Improving Research by the Integration of a Collaborative Dimension in an Information Retrieval (IR) System

Authors: Amel Hannech, Mehdi Adda, Hamid Mcheick

Abstract:

In computer science, the purpose of finding useful information is still one of the most active and important research topics. The most popular application of information retrieval (IR) are Search Engines, they meet users' specific needs and aim to locate the effective information in the web. However, these search engines have some limitations related to the relevancy of the results and the ease to explore those results. In this context, we proposed in previous works a Multi-Space Search Engine model that is based on a multidimensional interpretation universe. In the present paper, we integrate an additional dimension that allows to offer users new research experiences. The added component is based on creating user profiles and calculating the similarity between them that then allow the use of collaborative filtering in retrieving search results. To evaluate the effectiveness of the proposed model, a prototype is developed. The experiments showed that the additional dimension has improved the relevancy of results by predicting the interesting items of users based on their experiences and the experiences of other similar users. The offered personalization service allows users to approve the pertinent items, which allows to enrich their profiles and further improve research.

Keywords: information retrieval, v-facets, user behavior analysis, user profiles, topical ontology, association rules, data personalization

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2345 The Impact of the Fitness Center Ownership Structure on the Service Quality Perception in the Fitness in Serbia

Authors: Dragan Zivotic, Mirjana Ilic, Aleksandra Perovic, Predrag Gavrilovic

Abstract:

As with the provision of other services, the service quality perception is one of the key factors that the modern manager must pay attention to. Countries in which the state regulation is in transition also have specific features in providing fitness services. Identification of the dimensions in which the most significant different service quality perception between different types of fitness centers, enables managers to profile the offer according to the wishes and expectations of users. The aim of the paper was the comparison of the quality of services perception in the field of fitness in Serbia between three categories of fitness centers: the privately owned centers, the publicly owned centers, and the Public-private partnership centers. For this research 350 respondents of both genders (174 men and 176 women) were interviewed, aged between 18 and 68 years, being beneficiaries of fitness services for at least 1 year. Administered questionnaire with 100 items provided information about the 15 basic areas in which they expressed the service quality perception in the gym. The core sample was composed of 212 service users in private fitness centers, 69 service users in public fitness centers and 69 service users in the public-private partnership. Sub-samples were equal in representation of women and men, as well as by age and length of use of fitness services. The obtained results were subject of univariate analysis with the Kruskal-Wallis non-parametric analysis of variance. Significant differences between the analyzed sub-samples were not found solely in the areas of rapid response and quality outcomes. In the multivariate model, the results were processed by backward stepwise discriminant analysis that extracted 3 areas that maximize the differences between sub-samples: material and technical basis, secondary facilities and coaches. By applying the classification function 93.87% of private centers services users, 62.32% of public centers services users and 85.51% of the public-private partnership centers users of services were correctly classified (total 86.00%). These results allow optimizing the allocation of the necessary resources in profiling offers of a fitness center in order to optimally adjust it to the user’s needs and expectations.

Keywords: fitness, quality perception, management, public ownership, private ownership, public-private partnership, discriminative analysis

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2344 Development of Modular Shortest Path Navigation System

Authors: Nalinee Sophatsathit

Abstract:

This paper presents a variation of navigation systems which tallies every node along the shortest path from start to destination nodes. The underlying technique rests on the well-established Dijkstra Algorithm. The ultimate goal is to serve as a user navigation guide that furnishes stop over cost of every node along this shortest path, whereby users can decide whether or not to visit any specific nodes. The output is an implementable module that can be further refined to run on the Internet and smartphone technology. This will benefit large organizations having physical installations spreaded over wide area such as hospitals, universities, etc. The savings on service personnel, let alone lost time and unproductive work, are attributive to innovative navigation system management.

Keywords: navigation systems, shortest path, smartphone technology, user navigation guide

Procedia PDF Downloads 324
2343 Designing Next Generation Platforms for Recombinant Protein Production by Genome Engineering of Escherichia coli

Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

Abstract:

We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

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2342 pscmsForecasting: A Python Web Service for Time Series Forecasting

Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

Abstract:

pscmsForecasting is an open-source web service that implements a variety of time series forecasting algorithms and exposes them to the user via the ubiquitous HTTP protocol. It allows developers to enhance their applications by adding time series forecasting functionalities through an intuitive and easy-to-use interface. This paper provides some background on time series forecasting and gives details about the implemented algorithms, aiming to enhance the end user’s understanding of the underlying methods before incorporating them into their applications. A detailed description of the web service’s interface and its various parameterizations is also provided. Being an open-source project, pcsmsForecasting can also be easily modified and tailored to the specific needs of each application.

Keywords: time series, forecasting, web service, open source

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2341 An Insite to the Probabilistic Assessment of Reserves in Conventional Reservoirs

Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar

Abstract:

The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.

Keywords: simulation, probability, confidence interval, sensitivity analysis

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2340 ECG Based Reliable User Identification Using Deep Learning

Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

Abstract:

Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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2339 Arduino-Based Laser Communication

Authors: Simon Bambey, Edward Lim, Kai Corley-Jory, Pooya Taheri

Abstract:

The main goal of this paper is to propose a simple and low-cost microcontroller-based laser communication link. To demonstrate that laser communication is a viable and efficient means for transmitting data, a transceiver capable of transfer rates of approximately 0.7 kB/s is prototyped. The hardware used for the transceiver consists of Commercial Off-The-Shelf (COTS) lasers, photodiodes, and the Arduino Mega 2560 which is an open-source and easy-to-use microcontroller-based platform intended for making interactive projects. A graphic user interface utilizing the Meteor framework is developed to facilitate the communication between the user and transceiver. The developed transceiver prototype is capable of receiving and transmitting data at significant ranges with no loss of information. Furthermore, stable and secure communication is achieved through several mechanisms developed to manage simultaneous sending and receiving, in addition to detecting physical interruptions during transmission. The design setup is scalable and with further development can be transformed into a fiber-optic transmission system. Due to its nature, laser communication is very secure and can provide a safe and private communication link. Overall, this paper demonstrates how laser communication can be an economical, durable, and effective means of information transfer.

Keywords: Arduino microcontrollers, laser applications, user interfaces, wireless communication

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2338 Developing a Recommendation Library System based on Android Application

Authors: Kunyanuth Kularbphettong, Kunnika Tenprakhon, Pattarapan Roonrakwit

Abstract:

In this paper, we present a recommendation library application on Android system. The objective of this system is to support and advice user to use library resources based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on under association rules, Apriori algorithm. In this project, it was divided the result by the research purposes into 2 parts: developing the Mobile application for online library service and testing and evaluating the system. Questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory both specialists and users.

Keywords: online library, Apriori algorithm, Android application, black box

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2337 Context-Aware Point-Of-Interests Recommender Systems Using Integrated Sentiment and Network Analysis

Authors: Ho Yeon Park, Kyoung-Jae Kim

Abstract:

Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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2336 GUI Design of Mathematical Model of Cardiovascular-Respiratory System

Authors: Ntaganda J.M., Maniraguha J.D., Mukeshimana S., Harelimana D, Bizimungu T., Ruataganda E.

Abstract:

This paper presents the design of Graphic User Interface (GUI) in Matlab as interaction tool between human and machine. The designed GUI can be used by medical doctors and other experts particularly the physiologists. Matlab packages and estimated parameters of the mathematical model of cardiovascular-respiratory system developed in Rwandan context are used in GUI. The ordinary differential equations (ODE’s) govern a mathematical model in designing GUI in Matlab and a window that sets model estimated parameters and the measured parameters by any user. For healthy subject, these measured parameters include heart rate, systolic blood and diastolic blood pressure, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide in arterial blood, concentration of bound and dissolved oxygen in the mixed venous blood entering the lungs, and concentration of bound and dissolved carbon dioxide in the mixed venous blood entering the lungs. The results of numerical test give a consistent appearance as empirically known results.

Keywords: Graphic User Interface, mathematical model, cardiovascur-respiratory system, walking physical activity, blood pressure, oxygen

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2335 Next-Viz: A Literature Review and Web-Based Visualization Tool Proposal

Authors: Railly Hugo, Igor Aguilar-Alonso

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Software visualization is a powerful tool for understanding complex software systems. However, current visualization tools often lack features or are difficult to use, limiting their effectiveness. In this paper, we present next-viz, a proposed web-based visualization tool that addresses these challenges. We provide a literature review of existing software visualization techniques and tools and describe the architecture of next-viz in detail. Our proposed tool incorporates state-of-the-art visualization techniques and is designed to be user-friendly and intuitive. We believe next-viz has the potential to advance the field of software visualization significantly.

Keywords: software visualization, literature review, tool proposal, next-viz, web-based, architecture, visualization techniques, user-friendly, intuitive

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2334 ​​An Overview and Analysis of ChatGPT 3.5/4.0​

Authors: Sarah Mohammed, Huda Allagany, Ayah Barakat, Muna Elyas

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This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings.

Keywords: artificial intelligence, chat GPT, analysis, education

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2333 The Evolution of Amazon Alexa: From Voice Assistant to Smart Home Hub

Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

Abstract:

This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

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2332 Biosignal Recognition for Personal Identification

Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

Abstract:

A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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2331 A Multimodal Dialogue Management System for Achieving Natural Interaction with Embodied Conversational Agents

Authors: Ozge Nilay Yalcin

Abstract:

Dialogue has been proposed to be the natural basis for the human-computer interaction, which is behaviorally rich and includes different modalities such as gestures, posture changes, gaze, para-linguistic parameters and linguistic context. However, equipping the system with these capabilities might have consequences on the usability of the system. One issue is to be able to find a good balance between rich behavior and fluent behavior, as planning and generating these behaviors is computationally expensive. In this work, we propose a multi-modal dialogue management system that automates the conversational flow from text-based dialogue examples and uses synchronized verbal and non-verbal conversational cues to achieve a fluent interaction. Our system is integrated with Smartbody behavior realizer to provide real-time interaction with embodied agent. The nonverbal behaviors are used according to turn-taking behavior, emotions, and personality of the user and linguistic analysis of the dialogue. The verbal behaviors are responsive to the emotional value of the utterance and the feedback from the user. Our system is aimed for online planning of these affective multi-modal components, in order to achieve enhanced user experience with richer and more natural interaction.

Keywords: affect, embodied conversational agents, human-agent interaction, multimodal interaction, natural interfaces

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2330 Parallel Computing: Offloading Matrix Multiplication to GPU

Authors: Bharath R., Tharun Sai N., Bhuvan G.

Abstract:

This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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2329 Internet of Things Edge Device Power Modelling and Optimization Simulator

Authors: Cian O'Shea, Ross O'Halloran, Peter Haigh

Abstract:

Wireless Sensor Networks (WSN) are Internet of Things (IoT) edge devices. They are becoming widely adopted in many industries, including health care, building energy management, and conditional monitoring. As the scale of WSN deployments increases, the cost and complexity of battery replacement and disposal become more significant and in time may become a barrier to adoption. Harvesting ambient energies provide a pathway to reducing dependence on batteries and in the future may lead to autonomously powered sensors. This work describes a simulation tool that enables the user to predict the battery life of a wireless sensor that utilizes energy harvesting to supplement the battery power. To create this simulator, all aspects of a typical WSN edge device were modelled including, sensors, transceiver, and microcontroller as well as the energy source components (batteries, solar cells, thermoelectric generators (TEG), supercapacitors and DC/DC converters). The tool allows the user to plug and play different pre characterized devices as well as add user-defined devices. The goal of this simulation tool is to predict the lifetime of a device and scope for extension using ambient energy sources.

Keywords: Wireless Sensor Network, IoT, edge device, simulation, solar cells, TEG, supercapacitor, energy harvesting

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2328 Formal Specification of Web Services Applications for Digital Reference Services of Library Information System

Authors: Magaji Zainab Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

Abstract:

This paper discusses the formal specification of web services applications for digital reference services (WSDRS). Digital reference service involves a user requesting for help from a reference librarian and a reference librarian responding to the request of a user all by electronic means. In most cases users do not get satisfied while using digital reference service due to delay of response of the librarians. Another may be due to no response or due to librarian giving an irrelevant solution to the problem submitted by the user. WDSRS is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ need in the reference section of libraries. But informal model is in natural language which is inconsistent and ambiguous that may cause difficulties to the developers of the system. In order to solve this problem we decided to convert the informal specifications into formal specifications. This is supposed to reduce the overall development time and cost. Formal specification can be used to provide an unambiguous and precise supplement to natural language descriptions. It can be rigorously validated and verified leading to the early detection of specification errors. We use Z language to develop the formal model and verify it with Z/EVES theorem prover tool.

Keywords: formal, specifications, web services, digital reference services

Procedia PDF Downloads 370