Search results for: ontology matching
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 667

Search results for: ontology matching

307 Development of a Psychometric Testing Instrument Using Algorithms and Combinatorics to Yield Coupled Parameters and Multiple Geometric Arrays in Large Information Grids

Authors: Laith F. Gulli, Nicole M. Mallory

Abstract:

The undertaking to develop a psychometric instrument is monumental. Understanding the relationship between variables and events is important in structural and exploratory design of psychometric instruments. Considering this, we describe a method used to group, pair and combine multiple Philosophical Assumption statements that assisted in development of a 13 item psychometric screening instrument. We abbreviated our Philosophical Assumptions (PA)s and added parameters, which were then condensed and mathematically modeled in a specific process. This model produced clusters of combinatorics which was utilized in design and development for 1) information retrieval and categorization 2) item development and 3) estimation of interactions among variables and likelihood of events. The psychometric screening instrument measured Knowledge, Assessment (education) and Beliefs (KAB) of New Addictions Research (NAR), which we called KABNAR. We obtained an overall internal consistency for the seven Likert belief items as measured by Cronbach’s α of .81 in the final study of 40 Clinicians, calculated by SPSS 14.0.1 for Windows. We constructed the instrument to begin with demographic items (degree/addictions certifications) for identification of target populations that practiced within Outpatient Substance Abuse Counseling (OSAC) settings. We then devised education items, beliefs items (seven items) and a modifiable “barrier from learning” item that consisted of six “choose any” choices. We also conceptualized a close relationship between identifying various degrees and certifications held by Outpatient Substance Abuse Therapists (OSAT) (the demographics domain) and all aspects of their education related to EB-NAR (past and present education and desired future training). We placed a descriptive (PA)1tx in both demographic and education domains to trace relationships of therapist education within these two domains. The two perceptions domains B1/b1 and B2/b2 represented different but interrelated perceptions from the therapist perspective. The belief items measured therapist perceptions concerning EB-NAR and therapist perceptions using EB-NAR during the beginning of outpatient addictions counseling. The (PA)s were written in simple words and descriptively accurate and concise. We then devised a list of parameters and appropriately matched them to each PA and devised descriptive parametric (PA)s in a domain categorized information grid. Descriptive parametric (PA)s were reduced to simple mathematical symbols. This made it easy to utilize parametric (PA)s into algorithms, combinatorics and clusters to develop larger information grids. By using matching combinatorics we took paired demographic and education domains with a subscript of 1 and matched them to the column with each B domain with subscript 1. Our algorithmic matching formed larger information grids with organized clusters in columns and rows. We repeated the process using different demographic, education and belief domains and devised multiple information grids with different parametric clusters and geometric arrays. We found benefit combining clusters by different geometric arrays, which enabled us to trace parametric variables and concepts. We were able to understand potential differences between dependent and independent variables and trace relationships of maximum likelihoods.

Keywords: psychometric, parametric, domains, grids, therapists

Procedia PDF Downloads 248
306 Trajectory Tracking Control for Quadrotor Helicopter by Controlled Lagrangian Method

Authors: Ce Liu, Wei Huo

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A nonlinear trajectory tracking controller for quadrotor helicopter based on controlled Lagrangian (CL) method is proposed in this paper. A Lagrangian system with virtual angles as generated coordinates rather than Euler angles is developed. Based on the model, the matching conditions presented by nonlinear partial differential equations are simplified and explicitly solved. Smooth tracking control laws and the range of control parameters are deduced based on the controlled energy of closed-loop system. Besides, a constraint condition for reference accelerations is deduced to identify the trackable reference trajectories by the proposed controller and to ensure the stability of the closed-loop system. The proposed method in this paper does not rely on the division of the quadrotor system, and the design of the control torques does not depend on the thrust as in backstepping or hierarchical control method. Simulations for a quadrotor model demonstrate the feasibility and efficiency of the theoretical results.

Keywords: quadrotor, trajectory tracking control, controlled lagrangians, underactuated system

Procedia PDF Downloads 96
305 Distributed Perceptually Important Point Identification for Time Series Data Mining

Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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304 Similarity of the Disposition of the Electrostatic Potential of Tetrazole and Carboxylic Group to Investigate Their Bioisosteric Relationship

Authors: Alya A. Arabi

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Bioisosteres are functional groups that can be interchangeably used without affecting the potency of the drug. Bioisosteres have similar pharmacological properties. Bioisosterism is useful for modifying the physicochemical properties of a drug while obeying the Lipinski’s rules. Bioisosteres are key in optimizing the pharmacokinetic and pharmacodynamics properties of a drug. Tetrazole and carboxylate anions are non-classic bioisosteres. Density functional theory was used to obtain the wavefunction of the molecules and the optimized geometries. The quantum theory of atoms in molecules (QTAIM) was used to uncover the similarity of the average electron density in tetrazole and carboxylate anions. This similarity between the bioisosteres capped by a methyl group was valid despite the fact that the groups have different volumes, charges, energies, or electron populations. The biochemical correspondence of tetrazole and carboxylic acid was also determined to be a result of the similarity of the topography of the electrostatic potential (ESP). The ESP demonstrates the pharmacological and biochemical resemblance for a matching “key-and-lock” interaction.

Keywords: bioisosteres, carboxylic acid, density functional theory, electrostatic potential, tetrazole

Procedia PDF Downloads 403
303 A Deep Learning Based Approach for Dynamically Selecting Pre-processing Technique for Images

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 120
302 Numerical Simulation of the Production of Ceramic Pigments Using Microwave Radiation: An Energy Efficiency Study Towards the Decarbonization of the Pigment Sector

Authors: Pedro A. V. Ramos, Duarte M. S. Albuquerque, José C. F. Pereira

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Global warming mitigation is one of the main challenges of this century, having the net balance of greenhouse gas (GHG) emissions to be null or negative in 2050. Industry electrification is one of the main paths to achieving carbon neutrality within the goals of the Paris Agreement. Microwave heating is becoming a popular industrial heating mechanism due to the absence of direct GHG emissions, but also the rapid, volumetric, and efficient heating. In the present study, a mathematical model is used to simulate the production using microwave heating of two ceramic pigments, at high temperatures (above 1200 Celsius degrees). The two pigments studied were the yellow (Pr, Zr)SiO₂ and the brown (Ti, Sb, Cr)O₂. The chemical conversion of reactants into products was included in the model by using the kinetic triplet obtained with the model-fitting method and experimental data present in the Literature. The coupling between the electromagnetic, thermal, and chemical interfaces was also included. The simulations were computed in COMSOL Multiphysics. The geometry includes a moving plunger to allow for the cavity impedance matching and thus maximize the electromagnetic efficiency. To accomplish this goal, a MATLAB controller was developed to automatically search the position of the moving plunger that guarantees the maximum efficiency. The power is automatically and permanently adjusted during the transient simulation to impose stationary regime and total conversion, the two requisites of every converged solution. Both 2D and 3D geometries were used and a parametric study regarding the axial bed velocity and the heat transfer coefficient at the boundaries was performed. Moreover, a Verification and Validation study was carried out by comparing the conversion profiles obtained numerically with the experimental data available in the Literature; the numerical uncertainty was also estimated to attest to the result's reliability. The results show that the model-fitting method employed in this work is a suitable tool to predict the chemical conversion of reactants into the pigment, showing excellent agreement between the numerical results and the experimental data. Moreover, it was demonstrated that higher velocities lead to higher thermal efficiencies and thus lower energy consumption during the process. This work concludes that the electromagnetic heating of materials having high loss tangent and low thermal conductivity, like ceramic materials, maybe a challenge due to the presence of hot spots, which may jeopardize the product quality or even the experimental apparatus. The MATLAB controller increased the electromagnetic efficiency by 25% and global efficiency of 54% was obtained for the titanate brown pigment. This work shows that electromagnetic heating will be a key technology in the decarbonization of the ceramic sector as reductions up to 98% in the specific GHG emissions were obtained when compared to the conventional process. Furthermore, numerical simulations appear as a suitable technique to be used in the design and optimization of microwave applicators, showing high agreement with experimental data.

Keywords: automatic impedance matching, ceramic pigments, efficiency maximization, high-temperature microwave heating, input power control, numerical simulation

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301 Modeling and Energy Analysis of Limestone Decomposition with Microwave Heating

Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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300 Saudi Arabia Border Security Informatics: Challenges of a Harsh Environment

Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

Procedia PDF Downloads 457
299 Industrial Relations as Communication: The Strange Case of the FCA-UAW Agreement

Authors: Francesco Nespoli

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After having posed a theoretical framework combining framing theory and new rhetoric, the paper analyze the shift in communication both adopted by UAW and FCA during the negotiations in fall 2015. The paper argues that mistakes and adjustments played a determinant role respectively in the rejection of the first tentative agreement and in the ratification of the contract. The purpose of the paper is to set a new theoretical framework for the analysis of communication in industrial relations, by describing a narrative construction of reality from the perspective of the new rhetoric. The paper thus analyze all public text, speeches, tweets and Facebook posts by the union reading them as part of the narrative set by the organization condensed by the slogan 'it’s our time'. That narrative tried to gain consensus from the members matching the expectations due to the industry recovery after more than five years of workers' sacrifices. In doing so, the analysis points out a shift in the communication strategy of the union after the first rejection of a tentative agreement in 15 years. The findings suggest that, from the communication point of view, consultation in industrial relations can be conceived as a particular kind of political communication where identification with the audience through deliberate narrative may not be effective if it is not preceded by a listening campaign.

Keywords: communication, consultation, automotive, FCA

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298 Hybrid Deep Learning and FAST-BRISK 3D Object Detection Technique for Bin-Picking Application

Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

Procedia PDF Downloads 50
297 The Impact of Social Protection Intervention on Alleviating Social Vulnerability (Evidence from Ethiopian Rural Households)

Authors: Tewelde Gebresslase Haile, S. P. Singh

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To bridge the existing knowledge gap on public intervention implementations, this study estimates the impact of social protection intervention (SPI) on alleviating social vulnerability. Following a multi-stage sampling, primary information was gathered through a self-administered questionnaire, FGD, and interviews from the target households located at four systematically selected districts of Tigrai, Ethiopia. Factor analysis and Propensity Score Matching are applied to construct Social Vulnerability Index (SVI) and measuring the counterfactual impact of selected intervention. As a multidimensional challenge, social vulnerability is found as an important concept used to guide policy evaluation. Accessibility of basic services of Social Affairs, Agriculture, Health and Education sectors, and Food Security Program are commonly used as SPIs. Finally, this study discovers that the households who had access to SPI have scored 9.65% lower SVI than in the absence of the intervention. Finally, this study suggests the provision of integrated, proactive, productive, and evidence-based SPIs to alleviate social vulnerability.

Keywords: social protection, livelihood assets, social vulnerability, public policy SVI

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296 Verification and Application of Finite Element Model Developed for Flood Routing in Rivers

Authors: A. L. Qureshi, A. A. Mahessar, A. Baloch

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Flood wave propagation in river channel flow can be enunciated by nonlinear equations of motion for unsteady flow. However, it is difficult to find analytical solution of these complex non-linear equations. Hence, verification of the numerical model should be carried out against field data and numerical predictions. This paper presents the verification of developed finite element model applying for unsteady flow in the open channels. The results of a proposed model indicate a good matching with both Preissmann scheme and HEC-RAS model for a river reach of 29 km at both sites (15 km from upstream and at downstream end) for discharge hydrographs. It also has an agreeable comparison with the Preissemann scheme for the flow depth (stage) hydrographs. The proposed model has also been applying to forecast daily discharges at 400 km downstream from Sukkur barrage, which demonstrates accurate model predictions with observed daily discharges. Hence, this model may be utilized for predicting and issuing flood warnings about flood hazardous in advance.

Keywords: finite element method, Preissmann scheme, HEC-RAS, flood forecasting, Indus river

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295 Knowledge Based Behaviour Modelling and Execution in Service Robotics

Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

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294 Intellectual Property Rights on Plant Materials in Colombia: Legal Harmonization for Food Sovereignty

Authors: Medina Muñoz Lina Rocio

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The purpose of this paper is to examine the debates related to the harmonization of intellectual property rights on plant material, the corporate governance of the seed market in Colombia and the political economy of seeds defended by indigenous communities. In recent years, the commodification of seeds through genetic engineering and political intellectual property, codified as a result of the implementation of the Free Trade Agreement with the United States, has come into conflict with the traditional production of seeds carried out by small farmers and indigenous populations. Agricultural and food practices. In order to understand the ontological dimension of conflicts over seeds, it is necessary to analyze the conceptions that indigenous communities have about good, which they consider a common element of their social organization and define them as sentient beings. Therefore, through a multiple approach, in which the intellectual property policy, the ecological aspects of seed production and the political ontology of indigenous communities are interwoven, I intend to present the discussions held by the actors involved and present the strategies of small producers to protect their interests. It demonstrates that communities have begun to organize social movements to protect such interests and have questioned the philosophy of GM corporate agriculture as a pro-life movement. Finally, it is argued that the conservation of 'traditional' seeds of the communities is an effective strategy to support their struggles for territory, identity, food sovereignty and self-determination.

Keywords: intellectual property rights, intellectual property, traditional knowledge, food safety

Procedia PDF Downloads 43
293 The Development of Supported Employment in Malaysia

Authors: Chu Shi Wei

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Supported employment in Malaysia is in the early stages of development. The development of supported employment in Malaysia is an important step towards the inclusion of individuals with disabilities who have previously lacked the necessary support for employment in the open labour market as they were confined to sheltered workshops. There is a paradigm shift from sheltered to supported employment as the sheltered workshop is based on the medical model of disability, which focuses on the disability of the individual and segregated training institutions. The paradigm shift revolves around the social model of disability, which emphasizes the abilities of the individual and the removal of the barriers in the environment by the provision of support. This study explores the development of supported employment by utilizing a mixed methods approach which consists of collecting quantitative data through a survey and interviewing participants to collect qualitative data. Job coaches from six employment sectors participated in the survey and interview. The findings of the study indicate that the role of job coaches is integral to the development of supported employment. The role of job coaches includes job matching, on-the-job training, and developing natural supports to foster greater diversity and inclusion in the workplace.

Keywords: supported employment, disabilities, diversity, development

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292 Pathological Gambling and Impulsivity: Comparison of the Eight Laboratory Measures of Inhibition Capacities

Authors: Semion Kertzman, Pinhas Dannon

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Impulsive behaviour and the underlying brain processes are hypothesized to be central in the development and maintenance of pathological gambling. Inhibition ability can be differentially impaired in pathological gamblers (PGs). Aims: This study aimed to compare the ability of eight widely used inhibition measures to discriminate between PGs and healthy controls (HCs). Methods: PGs (N=51) and demographically matched HCs (N=51) performed cognitive inhibition (the Stroop), motor inhibition (the Go/NoGo) and reflective inhibition (the Matching Familiar Figures (MFFT)) tasks. Results: An augmented total interference response time in the Stroop task (η² =0.054), a large number of commission errors (η² =0.053) in the Go/NoGo task, and the total number of errors in the MFFT (η² =0.05) can discriminate PGs from HCs. Other measures are unable to differentiate between PGs and HCs. No significant correlations were observed between inhibition measures. Conclusion: Inhibition measures varied in the ability to discriminate PGs from HCs. Most inhibition measures were not relevant to gambling behaviour. PGs do not express rash, impulsive behaviour, such as quickly choosing an answer without thinking. In contrast, in PGs, inhibition impairment was related to slow-inaccurate performance.

Keywords: pathological gambling, impulsivity, neurocognition, addiction

Procedia PDF Downloads 276
291 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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290 Hotel Sales Promotion Effectiveness: An Experimental Study about Promotional Fit Presence vs. Absence on Behavioral Intentions

Authors: Esra Topcuoglu, Seyhmus Baloglu

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This research investigates the effects of online hotel sales promotion fit (SP fit) on traveler purchase intention (PI) and word-of-mouth (WOM). It examines these relationships based on the need for cognition (NFC), intention to travel (TI), promotional attractiveness (PA), and demographics within resource matching theory (RMT). One factor (SP: Fit presence for monetary and nonmonetary vs. Fit absence for monetary and nonmonetary) design was employed to test the effects of SP fit on traveler behaviors. Data collection was conducted from 300 subjects through Qualtrics. One-way MANOVA was performed to test the main effects of SP fit, and PROCESS simple moderation test for the interaction effects. Results revealed promotional fit increased the effectiveness of monetary and nonmonetary sales promotions. “F&B discount card at the hotel” was the most preferred deal. Fit absence for monetary sales promotion (MSP) and fit presence for nonmonetary sales promotion (NMSP) yielded significant results. The participants were involved in their intention to travel and perceptions of promotional attractiveness to value the promotions.

Keywords: need for cognition, promotional attractiveness, sales promotion fit, travel intention

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289 Green Building for Positive Energy Districts in European Cities

Authors: Paola Clerici Maestosi

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Positive Energy District (PED) is a rather recent concept whose aim is to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe's most complex challenges. PED integrates energy efficiency, renewable energy production, and energy flexibility in an integrated, multi-sectoral approach at the city level. The core idea behind Positive Energy Districts (PEDs) is to establish an urban area that can generate more energy than it consumes. Additionally, it should be flexible enough to adapt to changes in the energy market. This is crucial because a PED's goal is not just to achieve an annual surplus of net energy but also to help reduce the impact on the interconnected centralized energy networks. It achieves this by providing options to increase on-site load matching and self-consumption, employing technologies for short- and long-term energy storage, and offering energy flexibility through smart control. Thus, it seems that PEDs can encompass all types of buildings in the city environment. Given this which is the added value of having green buildings being constitutive part of PEDS? The paper will present a systematic literature review identifying the role of green building in Positive Energy District to provide answer to following questions: (RQ1) the state of the art of PEDs implementation; (RQ2) penetration of green building in Positive Energy District selected case studies. Methodological approach is based on a broad holistic study of bibliographic sources according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) further data will be analysed, mapped and text mining through VOSviewer. Main contribution of research is a cognitive framework on Positive Energy District in Europe and a selection of case studies where green building supported the transition to PED. The inclusion of green buildings within Positive Energy Districts (PEDs) adds significant value for several reasons. Firstly, green buildings are designed and constructed with a focus on environmental sustainability, incorporating energy-efficient technologies, materials, and design principles. As integral components of PEDs, these structures contribute directly to the district's overall ability to generate more energy than it consumes. Secondly, green buildings typically incorporate renewable energy sources, such as solar panels or wind turbines, further boosting the district's capacity for energy generation. This aligns with the PED objective of achieving a surplus of net energy. Moreover, green buildings often feature advanced systems for on-site energy management, load-matching, and self-consumption. This enhances the PED's capability to respond to variations in the energy market, making the district more agile and flexible in optimizing energy use. Additionally, the environmental considerations embedded in green buildings align with the broader sustainability goals of PEDs. By reducing the ecological footprint of individual structures, PEDs with green buildings contribute to minimizing the overall impact on centralized energy networks and promote a more sustainable urban environment. In summary, the incorporation of green buildings within PEDs not only aligns with the district's energy objectives but also enhances environmental sustainability, energy efficiency, and the overall resilience of the urban environment.

Keywords: positive energy district, renewables energy production, energy flexibility, energy efficiency

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288 Seismic Assessment of Old Existing RC Buildings with Masonry Infill in Madinah as Per ASCE

Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

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An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

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287 In Online and Laboratory We Trust: Comparing Trust Game Behavior in Three Environments

Authors: Kaisa M. Herne, Hanna E. Björkstedt

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Comparisons of online and laboratory environments are important for assessing whether the environment influences behavioral results. Trust game behavior was examined in three environments: 1) The standard laboratory setting with physically present participants (laboratory), 2) An online environment with an online meeting before playing the trust game (online plus a meeting); and 3) An online environment without a meeting (online without a meeting). In laboratory, participants were present in a classroom and played the trust game anonymously via computers. Online plus a meeting mimicked the laboratory in that participants could see each other in an online meeting before sessions started, whereas online without a meeting was a standard online experiment in which participants did not see each other at any stages of the experiment. Participants were recruited through pools of student subjects at two universities. The trust game was identical in all conditions; it was played with the same software, anonymously, and with stranger matching. There were no statistically significant differences between the treatment conditions regarding trust or trustworthiness. Results suggest that conducting trust game experiments online will yield similar results to experiments implemented in a laboratory.

Keywords: laboratory vs. online experiment, trust behavior, trust game, trustworthiness behavior

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286 DGA Data Interpretation Using Extension Theory for Power Transformer Diagnostics

Authors: O. P. Rahi, Manoj Kumar

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Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

Procedia PDF Downloads 379
285 Economic Impacts of Sanctuary and Immigration and Customs Enforcement Policies Inclusive and Exclusive Institutions

Authors: Alexander David Natanson

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This paper focuses on the effect of Sanctuary and Immigration and Customs Enforcement (ICE) policies on local economies. "Sanctuary cities" refers to municipal jurisdictions that limit their cooperation with the federal government's efforts to enforce immigration. Using county-level data from the American Community Survey and ICE data on economic indicators from 2006 to 2018, this study isolates the effects of local immigration policies on U.S. counties. The investigation is accomplished by simultaneously studying the policies' effects in counties where immigrants' families are persecuted via collaboration with Immigration and Customs Enforcement (ICE), in contrast to counties that provide protections. The analysis includes a difference-in-difference & two-way fixed effect model. Results are robust to nearest-neighbor matching, after the random assignment of treatment, after running estimations using different cutoffs for immigration policies, and with a regression discontinuity model comparing bordering counties with opposite policies. Results are also robust after restricting the data to a single-year policy adoption, using the Sun and Abraham estimator, and with event-study estimation to deal with the staggered treatment issue. In addition, the study reverses the estimation to understand what drives the decision to choose policies to detect the presence of reverse causality biases in the estimated policy impact on economic factors. The evidence demonstrates that providing protections to undocumented immigrants increases economic activity. The estimates show gains in per capita income ranging from 3.1 to 7.2, median wages between 1.7 to 2.6, and GDP between 2.4 to 4.1 percent. Regarding labor, sanctuary counties saw increases in total employment between 2.3 to 4 percent, and the unemployment rate declined from 12 to 17 percent. The data further shows that ICE policies have no statistically significant effects on income, median wages, or GDP but adverse effects on total employment, with declines from 1 to 2 percent, mostly in rural counties, and an increase in unemployment of around 7 percent in urban counties. In addition, results show a decline in the foreign-born population in ICE counties but no changes in sanctuary counties. The study also finds similar results for sanctuary counties when separating the data between urban, rural, educational attainment, gender, ethnic groups, economic quintiles, and the number of business establishments. The takeaway from this study is that institutional inclusion creates the dynamic nature of an economy, as inclusion allows for economic expansion due to the extension of fundamental freedoms to newcomers. Inclusive policies show positive effects on economic outcomes with no evident increase in population. To make sense of these results, the hypothesis and theoretical model propose that inclusive immigration policies play an essential role in conditioning the effect of immigration by decreasing uncertainties and constraints for immigrants' interaction in their communities, decreasing the cost from fear of deportation or the constant fear of criminalization and optimize their human capital.

Keywords: inclusive and exclusive institutions, post matching, fixed effect, time trend, regression discontinuity, difference-in-difference, randomization inference and sun, Abraham estimator

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284 Confluence of Relations: An Auto-Ethnographic Account of Field Recording in the Anthropocene Age

Authors: Freya Zinovieff

Abstract:

In the age of the Anthropocene, all ecosystems, no matter how remote, is influenced by the relations between humans and technology. These influences are evidenced by current extinction rates, changes in species diversity, and species adaptation to pollution. Field recording is a tool through which we are able to document the extent to which life forms associated with the place are entangled with human-technology relationships. This paper documents the convergence of interaction between technologies, species, and landscape via an auto-ethnographic account of a field recording taken from a cell phone tower in Bali, Indonesia. In the recording, we hear a confluence of relations where critter and technology meet. The electrical hum of the tower merges with frogs and the amaranthine throb of crickets, in such a way that it is hard to tell where technology begins and the voice of creatures ends. The outcomes of this venture resulted in a framework for evaluating the sensorial relations within field recording. The framework calls for the soundscape to be understood as a multilayered ontology through which there is a convergence of multispecies relationships, or entanglements, across time and geographic location. These entanglements are not necessarily obvious. Sometimes quiet, sometimes elusive, sometimes only audible through the mediated conduit of digital technology. The paper argues that to be aware of these entanglements is to open ourselves to a type of beauty that is firmly rooted in the present paradigm of extinction and loss. By virtue of this understanding, we are bestowed with an opportunity to embrace the grave reality of the current sixth mass extinction and move forwards with what activist Joanna Macy calls the compassionate action.

Keywords: anthropocene, human-technology relationships, multispecies ethnography, field recording

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283 Matching Farmer Competence and Farm Resources with the Transformation of Agri-Food Marketing Systems

Authors: Bhawat Chiamjinnawat

Abstract:

The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: farmer competence, farm resources, fruit industry, high-value markets, Thailand

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282 Presenting a Model for Predicting the State of Being Accident-Prone of Passages According to Neural Network and Spatial Data Analysis

Authors: Hamd Rezaeifar, Hamid Reza Sahriari

Abstract:

Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.

Keywords: accident, data mining, neural network, GIS

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281 Acrochordons and Diabetes Mellitus: A Case Control Study

Authors: Pratistha Shrestha

Abstract:

Background: Acrochordons (Skin tags) are common benign skin tumors usually occurring on the neck and major flexors of older people. These range in size from 1 mm to 1cm in diameter and are skin-colored or brownish. A possible association with diabetes mellitus has been suggested in previous studies, but the result is not conclusive. Objective: The aim of this study was to find out the association of diabetes mellitus with acrochordons. Material and Methods: One hundred and two patients were selected for the study. Among them, 51 (males–23 and females–28) with acrochordons were taken as cases, and 51 with other dermatologic diseases after matching age and sex were taken as controls. The patients were selected from OPD of the Department of Dermatology and Venereology in Universal College of Medical Sciences–Teaching Hospital (UCMS-TH). Blood glucose levels, including both fasting plasma glucose and 2-hour post-glucose load, were determined for both case and control and compared. Results: Patients with acrochordons had a significantly higher frequency of diabetes than the control group (p < 0.001). A total of 48.5% and 40% of patients with acrochordons having diabetes were obese and overweight, respectively. Conclusion: There is an increased risk of diabetes mellitus in patients with acrochordons. With regard to the importance of early diagnosis of diabetes, it is recommended a high level of suspicion for diabetes mellitus in patients with acrochordons.

Keywords: acrochordons, diabetes mellitus, obesity, skin tags

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280 Improving System Performance through User's Resource Access Patterns

Authors: K. C. Wong

Abstract:

This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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279 A Precision Medicine Approach to Sickle Cell Disease by Targeting the Adhesion Interactome

Authors: Anthara Vivek, Manisha Shukla, Mahesh Narayan, Prakash Narayan

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Sickle cell disease disproportionately affects sub-Saharan Africa and certain tribal populaces in India and has consequently drawn little intertest from Pharma. In sickle cell patients, adhesion of erythrocytes or reticulocytes to one another and the vessel wall results in painful ischemic episodes with few, if any, effective treatments for vaso-occlusive crises. Identification of disease-associated adhesion markers on erythrocytes or reticulocytes might inform the use of more effective therapies against vaso-occlusive crises. Increased expression of one or more of bcam, itga4, cd44, cd47, rap1a, vcam1, or icam4 has been reported in sickle cell subjects. Using the miRNet ontology knowledgebase, peripheral blood interactomes were generated by seeding various combinations of the afore-referenced mRNA. These interactomes yielded an array of miR targets. As examples, targeting hsa-miR-155-5p can potentially neutralize the rap1a-bcam-cd44-itga4-vcam1 erythrocyte/reticulocyte adhesion interactome whereas targeting hsa-miRs-103a-3p or 107 can potentially neutralize adhesion in cells overexpressing icam4-cd47-bcam-itga4-cd36. AM3380 (MIRacle™) is an off-the shelf hsa-miR-155-5p agomiR that can potentially neutralize the rap1a-bcam-cd44-itga4-vcam1 signaling axis. Phlebotomy coupled with transcriptomics represents a potentially feasible and effective precision medicine strategy to mitigate vaso-occlusive crises in sickle cell patients.

Keywords: adhesion, interactome, precision, medicine

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278 A Greedy Alignment Algorithm Supporting Medication Reconciliation

Authors: David Tresner-Kirsch

Abstract:

Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

Procedia PDF Downloads 261