Search results for: calibration data requirements
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26430

Search results for: calibration data requirements

23010 A Vehicle Monitoring System Based on the LoRa Technique

Authors: Chao-Linag Hsieh, Zheng-Wei Ye, Chen-Kang Huang, Yeun-Chung Lee, Chih-Hong Sun, Tzai-Hung Wen, Jehn-Yih Juang, Joe-Air Jiang

Abstract:

Air pollution and climate warming become more and more intensified in many areas, especially in urban areas. Environmental parameters are critical information to air pollution and weather monitoring. Thus, it is necessary to develop a suitable air pollution and weather monitoring system for urban areas. In this study, a vehicle monitoring system (VMS) based on the IoT technique is developed. Cars are selected as the research tool because it can reach a greater number of streets to collect data. The VMS can monitor different environmental parameters, including ambient temperature and humidity, and air quality parameters, including PM2.5, NO2, CO, and O3. The VMS can provide other information, including GPS signals and the vibration information through driving a car on the street. Different sensor modules are used to measure the parameters and collect the measured data and transmit them to a cloud server through the LoRa protocol. A user interface is used to show the sensing data storing at the cloud server. To examine the performance of the system, a researcher drove a Nissan x-trail 1998 to the area close to the Da’an District office in Taipei to collect monitoring data. The collected data are instantly shown on the user interface. The four kinds of information are provided by the interface: GPS positions, weather parameters, vehicle information, and air quality information. With the VMS, users can obtain the information regarding air quality and weather conditions when they drive their car to an urban area. Also, government agencies can make decisions on traffic planning based on the information provided by the proposed VMS.

Keywords: LoRa, monitoring system, smart city, vehicle

Procedia PDF Downloads 378
23009 SisGeo: Support System for the Research of Georeferenced Comparisons Applied to Professional and Academic Devices

Authors: Bruno D. Souza, Gerson G. Cunha, Michael O. Ferreira, Roberto Rosenhaim, Robson C. Santos, Sergio O. Santos

Abstract:

Devices and applications that use satellite-based positioning are becoming more popular day-by-day. Thus, evolution and improvement in this technology are mandatory. Accordingly, satellite georeferenced systems need to accomplish the same evolution rhythm. Either GPS (Global Positioning System) or its similar Russian GLONASS (Global Navigation Satellite System) are system samples that offer us powerful tools to plot coordinates on the earth surface. The development of this research aims the study of several aspects related to use of GPS and GLONASS technologies, given its application and collected data improvement during geodetic data acquisition. So, both relevant theoretic and practical aspects are considered. In this context, at the theoretical part, the main systems' characteristics are shown, observing its similarities and differences. At the practical part, a series of experiences are performed and obtained data packages are compared in order to demonstrate equivalence or differences among them. The evaluation methodology targets both quantitative and qualitative analysis provided by GPS and GPS/GLONASS receptors. Meanwhile, a specific collected data storage system was developed to better compare and analyze them (SisGeo - Georeferenced Research Comparison Support System).

Keywords: satellites, systems, applications, experiments, receivers

Procedia PDF Downloads 237
23008 Redefining Solar Generation Estimation: A Comprehensive Analysis of Real Utility Advanced Metering Infrastructure (AMI) Data from Various Projects in New York

Authors: Haowei Lu, Anaya Aaron

Abstract:

Understanding historical solar generation and forecasting future solar generation from interconnected Distributed Energy Resources (DER) is crucial for utility planning and interconnection studies. The existing methodology, which relies on solar radiation, weather data, and common inverter models, is becoming less accurate. Rapid advancements in DER technologies have resulted in more diverse project sites, deviating from common patterns due to various factors such as DC/AC ratio, solar panel performance, tilt angle, and the presence of DC-coupled battery energy storage systems. In this paper, the authors review 10,000 DER projects within the system and analyze the Advanced Metering Infrastructure (AMI) data for various types to demonstrate the impact of different parameters. An updated methodology is proposed for redefining historical and future solar generation in distribution feeders.

Keywords: photovoltaic system, solar energy, fluctuations, energy storage, uncertainty

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23007 Thermal Interruption Performance of High Voltage Gas Circuit Breaker Operating with CO₂ Mixtures

Authors: Yacine Babou, Nitesh Ranjan, Branimir Radisavljevic , Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti, Paulo Cristini

Abstract:

In the frame of replacement of Sulfur hexafluoride (SF6) gas as insulating and switching medium, diverse alternative gases, offering acceptable Global Warming Potential and fulfilling requirements in terms of heat dissipation, insulation and arc quenching performances are currently investigated for High Voltage Circuit Breaker applications. Among the potential gases, CO₂ seems a promising candidate for replacing SF6, because on one hand it is environmentally friendly, harmless, non-toxic, non-corrosive, non-flammable and on the other hand previous studies have demonstrated its fair interruption capabilities. The present study aims at investigating the performance of CO₂ for the thermal interruption in high voltage self-blast circuit breakers. In particular, the correlation between thermal interruption performance and arc voltage is considered and the effect of the arc-network interaction on the performance is rigorously analyzed. For the considered designs, the thermal interruption was evaluated by varying the slope at current zero (i.e., di/dt) for which the breaker could interrupt. Besides, the characteristics of the post-arc current are examined in detail for various rated voltages and currents. The outcome of these experimental investigations will be reported and analyzed.

Keywords: current zero measurement, high voltage circuit breaker, thermal arc discharge, thermal interruption

Procedia PDF Downloads 169
23006 Assembly Solution for Modular Buildings: Development of a Plug-In Self-Locking Device Designed for Light-Framed Structures

Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

Abstract:

The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

Procedia PDF Downloads 150
23005 Analysis of Digital Transformation in Banking: The Hungarian Case

Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

Abstract:

The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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23004 Applying Spanning Tree Graph Theory for Automatic Database Normalization

Authors: Chetneti Srisa-an

Abstract:

In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: relational database, functional dependency, automatic normalization, primary key, spanning tree

Procedia PDF Downloads 338
23003 A Multi-Objective Optimization Tool for Dual-Mode Operating Active Magnetic Regenerator Model

Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

Abstract:

This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

Procedia PDF Downloads 98
23002 Dynamic Response of Magnetorheological Fluid Tapered Laminated Beams Reinforced with Nano-Particles

Authors: Saman Momeni, Abolghassem Zabihollah, Mehdi Behzad

Abstract:

Non-uniform laminated composite structures are being used in many engineering applications where the structures are subjected to unpredicted vibration. To mitigate the vibration response of these structures, recently, magnetorheological fluid (MR), is added to non-uniform (tapered) thickness laminated composite structures to achieve a new generation of the smart composite as MR tapered beam. However, due to the nature of MR fluid, especially the low stiffness, MR tapered beam exhibit lower stiffness and in turn, lower natural frequencies. To achieve the basic design requirements of the structure without MR fluid, one may need to apply a predefined magnetic energy to the structures, requiring a constant source of energy. In the present work, a passive initial stiffness control of MR tapered beam has been studied. The effects of adding nanoparticles on the dynamic response of MR tapered beam has been investigated. It is observed that adding nanoparticles up to 3% may significantly modify the natural frequencies of the structures and achieve dynamic behavior of the structures before addition of MR fluid. Two Models of tapered structures have been taken into consideration. It is observed that adding only 3% of nanoparticles backs the structures to its initial dynamic behavior.

Keywords: non uniform laminated structures, MR fluid, nanoparticles, vibration, stiffness

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23001 Growing Architecture, Technical Product Harvesting of Near Net Shape Building Components

Authors: Franziska Moser, Martin Trautz, Anna-Lena Beger, Manuel Löwer, Jörg Feldhusen, Jürgen Prell, Alexandra Wormit, Björn Usadel, Christoph Kämpfer, Thomas-Benjamin Seiler, Henner Hollert

Abstract:

The demand for bio-based materials and components in architecture has increased in recent years due to society’s heightened environmental awareness. Nowadays, most components are being developed via a substitution approach, which aims at replacing conventional components with natural alternatives who are then being processed, shaped and manufactured to fit the desired application. This contribution introduces a novel approach to the development of bio-based products that decreases resource consumption and increases recyclability. In this approach, natural organisms like plants or trees are not being used in a processed form, but grow into a near net shape before then being harvested and utilized as building components. By minimizing the conventional production steps, the amount of resources used in manufacturing decreases whereas the recyclability increases. This paper presents the approach of technical product harvesting, explains the theoretical basis as well as the matching process of product requirements and biological properties, and shows first results of the growth manipulation studies.

Keywords: design with nature, eco manufacturing, sustainable construction materials, technical product harvesting

Procedia PDF Downloads 487
23000 Producing Outdoor Design Conditions based on the Dependency between Meteorological Elements: Copula Approach

Authors: Zhichao Jiao, Craig Farnham, Jihui Yuan, Kazuo Emura

Abstract:

It is common to use the outdoor design weather data to select the air-conditioning capacity in the building design stage. The outdoor design weather data are usually comprised of multiple meteorological elements for a 24-hour period separately, but the dependency between the elements is not well considered, which may cause an overestimation of selecting air-conditioning capacity. Considering the dependency between the air temperature and global solar radiation, we used the copula approach to model the joint distributions of those two weather elements and suggest a new method of selecting more credible outdoor design conditions based on the specific simultaneous occurrence probability of air temperature and global solar radiation. In this paper, the 10-year period hourly weather data from 2001 to 2010 in Osaka, Japan, was used to analyze the dependency structure and joint distribution, the result shows that the Joe-Frank copula fit for almost all hourly data. According to calculating the simultaneous occurrence probability and the common exceeding probability of air temperature and global solar radiation, the results have shown that the maximum difference in design air temperature and global solar radiation of the day is about 2 degrees Celsius and 30W/m2, respectively.

Keywords: energy conservation, design weather database, HVAC, copula approach

Procedia PDF Downloads 243
22999 A Potential Spin-orbit Torque Device Using the Tri-layer Structure

Authors: Chih-Wei Cheng, Wei-Jen Chan, Yu-Han Huang, Yi-Tsung Lin, Yen-Wei Huang, Min-Cheng Chen, Shou-Zen Chang, G. Chern, Yuan-Chieh Tseng

Abstract:

How to develop spin-orbit-torque (SOT) devices with the virtues of field-free, perpendicular magnetic anisotropy (PMA), and low switching current is one of the many challenges in spintronics today. We propose a CoFeB/Ta/CoFeB tri-layer antiferromagnetic SOT device that could meet the above requirements. The device’s PMA was developed by adopting CoFeB–MgO interface. The key to the success of this structure is to ensure that (i)changes of the inter-layer coupling(IEC) and CoFeB anisotropy can occur simultaneously; (ii) one of the CoFeB needs to have a slightly tilted moment in the beginning. When sufficient current is given, the SHEreverses the already-tiltedCoFeB, and the other CoFeB can be reversed simultaneously by the IEC with the field-free nature. Adjusting the thickness of Ta can modify the coupling state to reduce the switching current while the field-free nature was preserved. Micromagnetic simulation suggests that the Néel orange peel effect (NOPE) is non-negligible due to interface roughness and coupling effect in the presence of perpendicular anisotropy. Fortunately, the Néel field induced by the NOPE appears to favor the field-free reversal.

Keywords: CoFeB, spin-orbit torque, antiferromagnetic, MRAM, trilayer

Procedia PDF Downloads 97
22998 Environmental Impact Assessment in Mining Regions with Remote Sensing

Authors: Carla Palencia-Aguilar

Abstract:

Calculations of Net Carbon Balance can be obtained by means of Net Biome Productivity (NBP), Net Ecosystem Productivity (NEP), and Net Primary Production (NPP). The latter is an important component of the biosphere carbon cycle and is easily obtained data from MODIS MOD17A3HGF; however, the results are only available yearly. To overcome data availability, bands 33 to 36 from MODIS MYD021KM (obtained on a daily basis) were analyzed and compared with NPP data from the years 2000 to 2021 in 7 sites where surface mining takes place in the Colombian territory. Coal, Gold, Iron, and Limestone were the minerals of interest. Scales and Units as well as thermal anomalies, were considered for net carbon balance per location. The NPP time series from the satellite images were filtered by using two Matlab filters: First order and Discrete Transfer. After filtering the NPP time series, comparing the graph results from the satellite’s image value, and running a linear regression, the results showed R2 from 0,72 to 0,85. To establish comparable units among NPP and bands 33 to 36, the Greenhouse Gas Equivalencies Calculator by EPA was used. The comparison was established in two ways: one by the sum of all the data per point per year and the other by the average of 46 weeks and finding the percentage that the value represented with respect to NPP. The former underestimated the total CO2 emissions. The results also showed that coal and gold mining in the last 22 years had less CO2 emissions than limestone, with an average per year of 143 kton CO2 eq for gold, 152 kton CO2 eq for coal, and 287 kton CO2 eq for iron. Limestone emissions varied from 206 to 441 kton CO2 eq. The maximum emission values from unfiltered data correspond to 165 kton CO2 eq. for gold, 188 kton CO2 eq. for coal, and 310 kton CO2 eq. for iron and limestone, varying from 231 to 490 kton CO2 eq. If the most pollutant limestone site improves its production technology, limestone could count with a maximum of 318 kton CO2 eq emissions per year, a value very similar respect to iron. The importance of gathering data is to establish benchmarks in order to attain 2050’s zero emissions goal.

Keywords: carbon dioxide, NPP, MODIS, MINING

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22997 Electrospinning Preparation of Superhydrophobic Polydimethylsiloxane/Polystyrene Nanofibrous Membranes for Carbon Dioxide Capture

Authors: Chia-Yu Chang, Yi-Feng Lin

Abstract:

CO2 capture has attracted significant research attention due to global warming. Among the various CO2 capture methods, membrane technology has proven to be highly efficient in capturing CO2 due to the ease at which this technology can be scaled up, its low energy consumptions, small area requirements and overall environmental friendliness for use by industrial plants. Capturing CO2 is to use a membrane contactor with a combination of water-repellent porous membranes and chemical absorption processes. In a CO2 membrane contactor system, CO2 passes through a hydrophobic porous membrane in the gas phase to contact the amine absorbent in the liquid phase. Consequently, additional CO2 gas is absorbed by amine absorbents. This study examines highly porous Polydimethylsiloxane (PDMS)/Polystyrene (PS) Nanofibrous Membranes and successfully coated onto a macroporous Al2O3 membrane. The performance of these materials in a membrane contactor system for CO2 absorption is also investigated. Compared with pristine PS nanofibrous membranes, the PDMS/PS nanofibrous membranes exhibit greater solvent resistance and mechanical strength, making them more suitable for use in CO2 capture by the membrane contactor. The resulting hydrophobic membrane contactor also demonstrates the potential for large-scale CO2 absorption during post-combustion processes in power plants.

Keywords: CO2 capture, polystyrene, polydimethylsiloxane, superhydrophobic

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22996 Control of Pipeline Gas Quality to Extend Gas Turbine Life

Authors: Peter J. H. Carnell, Panayiotis Theophanous

Abstract:

Natural gas due to its cleaner combustion characteristics is expected to be the most widely used fuel in the move towards less polluting and renewable energy sources. Thus, the developed world is supplied by a complex network of gas pipelines and natural gas is becoming a major source of fuel. Natural gas delivered directly from the well will differ in composition from gas derived from LNG or produced by anaerobic digestion processes. Each will also have specific contaminants and properties although gas from all sources is likely to enter the distribution system and be blended to provide the desired characteristics such as Higher Heating Value and Wobbe No. The absence of a standard gas composition poses problems when the gas is used as a chemical feedstock, in specialised furnaces or on gas turbines. The chemical industry has suffered in the past as a result of variable gas composition. Transition metal catalysts used in ammonia, methanol and hydrogen plants were easily poisoned by sulphur, chlorides and mercury reducing both activity and catalyst expected lives from years to months. These plants now concentrate on purification and conditioning of the natural gas feed using fixed bed technologies, allowing them to run for several years and having transformed their operations. Similar technologies can be applied to the power industry reducing maintenance requirements and extending the operating life of gas turbines.

Keywords: gas composition, gas conditioning, gas turbines, power generation, purification

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22995 The Role of Mass Sport Guidance in the Health Service Industry of China

Authors: Qiu Jian-Rong, Li Qing-Hui, Zhan Dong, Zhang Lei

Abstract:

Facing the problem of the demand of economic restructuring and risk of social economy stagnation due to the ageing of population, the Health Service Industry will play a very important role in the structure of industry in the future. During the process, the orient of Chinese sports medicine as well as the joint with preventive medicine, and the integration with data bank and cloud computing will be involved.

Keywords: China, the health service industry, mass sport, data bank

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22994 A Numerical Investigation of Lamb Wave Damage Diagnosis for Composite Delamination Using Instantaneous Phase

Authors: Haode Huo, Jingjing He, Rui Kang, Xuefei Guan

Abstract:

This paper presents a study of Lamb wave damage diagnosis of composite delamination using instantaneous phase data. Numerical experiments are performed using the finite element method. Different sizes of delamination damages are modeled using finite element package ABAQUS. Lamb wave excitation and responses data are obtained using a pitch-catch configuration. Empirical mode decomposition is employed to extract the intrinsic mode functions (IMF). Hilbert–Huang Transform is applied to each of the resulting IMFs to obtain the instantaneous phase information. The baseline data for healthy plates are also generated using the same procedure. The size of delamination is correlated with the instantaneous phase change for damage diagnosis. It is observed that the unwrapped instantaneous phase of shows a consistent behavior with the increasing delamination size.

Keywords: delamination, lamb wave, finite element method, EMD, instantaneous phase

Procedia PDF Downloads 309
22993 Relationship between Wave Velocities and Geo-Pressures in Shallow Libyan Carbonate Reservoir

Authors: Tarek Sabri Duzan

Abstract:

Knowledge of the magnitude of Geo-pressures (Pore, Fracture & Over-burden pressures) is vital especially during drilling, completions, stimulations, Enhance Oil Recovery. Many times problems, like lost circulation could have been avoided if techniques for calculating Geo-pressures had been employed in the well planning, mud weight plan, and casing design. In this paper, we focused on the relationships between Geo-pressures and wave velocities (P-Wave (Vp) and S-wave (Vs)) in shallow Libyan carbonate reservoir in the western part of the Sirte Basin (Dahra F-Area). The data used in this report was collected from four new wells recently drilled. Those wells were scattered throughout the interested reservoir as shown in figure-1. The data used in this work are bulk density, Formation Mult -Tester (FMT) results and Acoustic wave velocities. Furthermore, Eaton Method is the most common equation used in the world, therefore this equation has been used to calculate Fracture pressure for all wells using dynamic Poisson ratio calculated by using acoustic wave velocities, FMT results for pore pressure, Overburden pressure estimated by using bulk density. Upon data analysis, it has been found that there is a linear relationship between Geo-pressures (Pore, Fracture & Over-Burden pressures) and wave velocities ratio (Vp/Vs). However, the relationship was not clear in the high-pressure area, as shown in figure-10. Therefore, it is recommended to use the output relationship utilizing the new seismic data for shallow carbonate reservoir to predict the Geo-pressures for future oil operations. More data can be collected from the high-pressure zone to investigate more about this area.

Keywords: bulk density, formation mult-tester (FMT) results, acoustic wave, carbonate shalow reservoir, d/jfield velocities

Procedia PDF Downloads 274
22992 Manufacturing Facility Location Selection: A Numercal Taxonomy Approach

Authors: Seifoddini Hamid, Mardikoraeem Mahsa, Ghorayshi Roya

Abstract:

Manufacturing facility location selection is an important strategic decision for many industrial corporations. In this paper, a new approach to the manufacturing location selection problem is proposed. In this approach, cluster analysis is employed to identify suitable manufacturing locations based on economic, social, environmental, and political factors. These factors are quantified using the existing real world data.

Keywords: manufacturing facility, manufacturing sites, real world data

Procedia PDF Downloads 552
22991 Unsupervised Domain Adaptive Text Retrieval with Query Generation

Authors: Rui Yin, Haojie Wang, Xun Li

Abstract:

Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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22990 Journals' Productivity in the Literature on Malaria in Africa

Authors: Yahya Ibrahim Harande

Abstract:

The purpose of this study was to identify the journals that published articles on malaria disease in Africa and to determine the core of productive journals from the identified journals. The data for the study were culled out from African Index Medicus (AIM) database. A total of 529 articles was gathered from 115 journal titles from 1979-2011. In order to obtain the core of productive journals, Bradford`s law was applied to the collected data. Five journal titles were identified and determined as core journals. The data used for the study was analyzed and that, the subject matter used, Malaria was in conformity with the Bradford`s law. On the aspect dispersion of the literature, English was found to be the dominant language of the journals. (80.9%) followed by French (16.5%). Followed by Portuguese (1.7%) and German (0.9%). Recommendation is hereby proposed for the medical libraries to acquire these five journals that constitute the core in malaria literature for the use of their clients. It could also help in streamlining their acquision and selection exercises. More researches in the subject area using Bibliometrics approaches are hereby recommended.

Keywords: productive journals, malaria disease literature, Bradford`s law, core journals, African scholars

Procedia PDF Downloads 331
22989 Study of Natural Convection Heat Transfer of Plate-Fin Heat Sink

Authors: Han-Taw Chen, Tzu-Hsiang Lin, Chung-Hou Lai

Abstract:

This study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a rectangular closed enclosure. The inverse method with the finite difference method and the experimental temperature data is applied to determine the approximate heat transfer coefficient. Later, based on the obtained results, the zero-equation turbulence model is used to obtain the heat transfer and fluid flow characteristics between two fins. To validate the accuracy of the results obtained, the comparison of the heat transfer coefficient is made. The obtained temperature at selected measurement locations of the fin is also compared with experimental data. The effect of the height of the rectangular enclosure on the obtained results is discussed.

Keywords: inverse method, fluent, heat transfer characteristics, plate-fin heat sink

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22988 Digital Learning and Entrepreneurship Education: Changing Paradigms

Authors: Shivangi Agrawal, Hsiu-I Ting

Abstract:

Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g., online entrepreneurship education courses and programs) and other digital tools (e.g., digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.

Keywords: entrepreneurship education, digital technologies, academic entrepreneurship, COVID-19

Procedia PDF Downloads 238
22987 Phonetics and Phonological Investigation of Geminates and Gemination in Some Indic Languages

Authors: Hifzur Ansary

Abstract:

The aim and scope of the present research are to delve into the form of geminates and the process of gemination with special reference to Indic Languages. This work presents the results of a cross-linguistic investigation of word-medial geminate consonants. This study is a theoretical as well as experimental, that is, it is based not only on impressionistic data from Indic languages but also on an instrumental analysis of the data. The primary data have been collected from the native speakers. The secondary data have been collected from printed materials such as journals, grammar books and other published articles. The observations made in this study have been checked with a number of educated native speakers of Bangla and Telugu. The study focuses on geminates and gemination in Bangla (Indo-Aryan Language Family) and Telugu (Dravidian Language family) exhaustively. Thus this study also attempts to posit the valid geminates in Bangali and Telugu and provides an account of gemination in these languages. It also makes a comparison of singletons and geminated consonants. It describes the distribution of geminate phonemes and non-geminate phonemes of Bangla and Telugu. The present research would also investigate the vowel lengthening in Bangla with respect to gemination. The study also explains how gemination processes present in Indian Languages are transferred to Indian English.

Keywords: geminate consonant, singleton-geminate contrast, different types of assimilation, gemination derives from borrowed words

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22986 Supply Chain Risk Management: A Meta-Study of Empirical Research

Authors: Shoufeng Cao, Kim Bryceson, Damian Hine

Abstract:

The existing supply chain risk management (SCRM) research is currently chaotic and somewhat disorganized, and the topic has been addressed conceptually more often than empirically. This paper, using both qualitative and quantitative data, employs a modified Meta-study method to investigate the SCRM empirical research published in quality journals over the period of 12 years (2004-2015). The purpose is to outline the extent research trends and the employed research methodologies (i.e., research method, data collection and data analysis) across the sub-field that will guide future research. The synthesized findings indicate that empirical study on risk ripple effect along an entire supply chain, industry-specific supply chain risk management and global/export supply chain risk management has not yet given much attention than it deserves in the SCRM field. Besides, it is suggested that future empirical research should employ multiple and/or mixed methods and multi-source data collection techniques to reduce common method bias and single-source bias, thus improving research validity and reliability. In conclusion, this paper helps to stimulate more quality empirical research in the SCRM field via identifying promising research directions and providing some methodology guidelines.

Keywords: empirical research, meta-study, methodology guideline, research direction, supply chain risk management

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22985 Design of Bacterial Pathogens Identification System Based on Scattering of Laser Beam Light and Classification of Binned Plots

Authors: Mubashir Hussain, Mu Lv, Xiaohan Dong, Zhiyang Li, Bin Liu, Nongyue He

Abstract:

Detection and classification of microbes have a vast range of applications in biomedical engineering especially in detection, characterization, and quantification of bacterial contaminants. For identification of pathogens, different techniques are emerging in the field of biomedical engineering. Latest technology uses light scattering, capable of identifying different pathogens without any need for biochemical processing. Bacterial Pathogens Identification System (BPIS) which uses a laser beam, passes through the sample and light scatters off. An assembly of photodetectors surrounded by the sample at different angles to detect the scattering of light. The algorithm of the system consists of two parts: (a) Library files, and (b) Comparator. Library files contain data of known species of bacterial microbes in the form of binned plots, while comparator compares data of unknown sample with library files. Using collected data of unknown bacterial species, highest voltage values stored in the form of peaks and arranged in 3D histograms to find the frequency of occurrence. Resulting data compared with library files of known bacterial species. If sample data matching with any library file of known bacterial species, sample identified as a matched microbe. An experiment performed to identify three different bacteria particles: Enterococcus faecalis, Pseudomonas aeruginosa, and Escherichia coli. By applying algorithm using library files of given samples, results were compromising. This system is potentially applicable to several biomedical areas, especially those related to cell morphology.

Keywords: microbial identification, laser scattering, peak identification, binned plots classification

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22984 An Analysis into Global Suicide Trends and Their Relation to Current Events Through a Socio-Cultural Lens

Authors: Lyndsey Kim

Abstract:

We utilized country-level data on suicide rates from 1985 through 2015 provided by the WHO to explore global trends as well as country-specific trends. First, we find that up until 1995, there was an increase in suicide rates globally, followed by a steep decline in deaths. This observation is largely driven by the data from Europe, where suicides are prominent but steadily declining. Second, men are more likely to commit suicide than women across the world over the years. Third, the older generation is more likely to commit suicide than youth and adults. Finally, we turn to Durkheim’s theory and use it as a lens to understand trends in suicide across time and countries and attempt to identify social and economic events that might explain patterns that we observe. For example, we discovered a drastically different pattern in suicide rates in the US, with a steep increase in suicides in the early 2000s. We hypothesize this might be driven by both the 9/11 attacks and the recession of 2008.

Keywords: suicide trends, current events, data analysis, world health organization, durkheim theory

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22983 Trading off Accuracy for Speed in Powerdrill

Authors: Filip Buruiana, Alexander Hall, Reimar Hofmann, Thomas Hofmann, Silviu Ganceanu, Alexandru Tudorica

Abstract:

In-memory column-stores make interactive analysis feasible for many big data scenarios. PowerDrill is a system used internally at Google for exploration in logs data. Even though it is a highly parallelized column-store and uses in memory caching, interactive response times cannot be achieved for all datasets (note that it is common to analyze data with 50 billion records in PowerDrill). In this paper, we investigate two orthogonal approaches to optimize performance at the expense of an acceptable loss of accuracy. Both approaches can be implemented as outer wrappers around existing database engines and so they should be easily applicable to other systems. For the first optimization we show that memory is the limiting factor in executing queries at speed and therefore explore possibilities to improve memory efficiency. We adapt some of the theory behind data sketches to reduce the size of particularly expensive fields in our largest tables by a factor of 4.5 when compared to a standard compression algorithm. This saves 37% of the overall memory in PowerDrill and introduces a 0.4% relative error in the 90th percentile for results of queries with the expensive fields. We additionally evaluate the effects of using sampling on accuracy and propose a simple heuristic for annotating individual result-values as accurate (or not). Based on measurements of user behavior in our real production system, we show that these estimates are essential for interpreting intermediate results before final results are available. For a large set of queries this effectively brings down the 95th latency percentile from 30 to 4 seconds.

Keywords: big data, in-memory column-store, high-performance SQL queries, approximate SQL queries

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22982 Role of Artificial Intelligence in Nano Proteomics

Authors: Mehrnaz Mostafavi

Abstract:

Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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22981 Data Quality on Regular Childhood Immunization Programme at Degehabur District: Somali Region, Ethiopia

Authors: Eyob Seife

Abstract:

Immunization is a life-saving intervention which prevents needless suffering through sickness, disability, and death. Emphasis on data quality and use will become even stronger with the development of the immunization agenda 2030 (IA2030). Quality of data is a key factor in generating reliable health information that enables monitoring progress, financial planning, vaccine forecasting capacities, and making decisions for continuous improvement of the national immunization program. However, ensuring data of sufficient quality and promoting an information-use culture at the point of the collection remains critical and challenging, especially in hard-to-reach and pastoralist areas where Degehabur district is selected based on a hypothesis of ‘there is no difference in reported and recounted immunization data consistency. Data quality is dependent on different factors where organizational, behavioral, technical, and contextual factors are the mentioned ones. A cross-sectional quantitative study was conducted on September 2022 in the Degehabur district. The study used the world health organization (WHO) recommended data quality self-assessment (DQS) tools. Immunization tally sheets, registers, and reporting documents were reviewed at 5 health facilities (2 health centers and 3 health posts) of primary health care units for one fiscal year (12 months) to determine the accuracy ratio. The data was collected by trained DQS assessors to explore the quality of monitoring systems at health posts, health centers, and the district health office. A quality index (QI) was assessed, and the accuracy ratio formulated were: the first and third doses of pentavalent vaccines, fully immunized (FI), and the first dose of measles-containing vaccines (MCV). In this study, facility-level results showed both over-reporting and under-reporting were observed at health posts when computing the accuracy ratio of the tally sheet to health post reports found at health centers for almost all antigens verified where pentavalent 1 was 88.3%, 60.4%, and 125.6% for Health posts A, B, and C respectively. For first-dose measles-containing vaccines (MCV), similarly, the accuracy ratio was found to be 126.6%, 42.6%, and 140.9% for Health posts A, B, and C, respectively. The accuracy ratio for fully immunized children also showed 0% for health posts A and B and 100% for health post-C. A relatively better accuracy ratio was seen at health centers where the first pentavalent dose was 97.4% and 103.3% for health centers A and B, while a first dose of measles-containing vaccines (MCV) was 89.2% and 100.9% for health centers A and B, respectively. A quality index (QI) of all facilities also showed results between the maximum of 33.33% and a minimum of 0%. Most of the verified immunization data accuracy ratios were found to be relatively better at the health center level. However, the quality of the monitoring system is poor at all levels, besides poor data accuracy at all health posts. So attention should be given to improving the capacity of staff and quality of monitoring system components, namely recording, reporting, archiving, data analysis, and using information for decision at all levels, especially in pastoralist areas where such kinds of study findings need to be improved beside to improving the data quality at root and health posts level.

Keywords: accuracy ratio, Degehabur District, regular childhood immunization program, quality of monitoring system, Somali Region-Ethiopia

Procedia PDF Downloads 85