Search results for: geometric complexity
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2193

Search results for: geometric complexity

993 The Effect of Nursing Teamwork Training on Nursing Teamwork Effectiveness

Authors: Manar Ahmed Elbadawy

Abstract:

Background: Empirical evidence suggested that improving nursing teamwork (NTW) may be the key to reducing medical error. The functioning nursing teams require open communication, mutual respect, and shared mental models to activate quality patient care. The complexity and the high demands for specialized nursing knowledge and skill also require nursing staff to consult with one another and work in teams regularly. The current study aimed to evaluate the effect of the nursing teamwork training program on nursing teamwork effectiveness. Design: A quasi-experimental (one group pretest-posttest) design was utilized. Three medical intensive care units at a teaching hospital affiliated to Cairo University Hospital, Egypt. Subjects: A convenient sample of 48 nursing staff worked at the selected units. The Nursing Teamwork Observational Checklist was used. Results: Total (NTW) mean scores exhibited quite elevation post-program implementation compared to preprogram and showed little decrease 3 months later ( = 2.52, SD = ± 0.27, mean % =51.98, = 2.72, SD = ± 0.20, mean %=72.45, = 2.67, SD = ± 0.11, mean %= 67.48 respectively). Conclusion: Implementation of (NTW) training program had a positive effect on increasing (NTW) effectiveness. Regular and frequent short-term teamwork training is important to be introduced as well as sustainable monitoring is required to ensure nursing attitudes, knowledge and skills’ change about teamwork effectiveness.

Keywords: effectiveness, nursing, teamwork, training

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992 Exploring the Need to Study the Efficacy of VR Training Compared to Traditional Cybersecurity Training

Authors: Shaila Rana, Wasim Alhamdani

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Effective cybersecurity training is of the utmost importance, given the plethora of attacks that continue to increase in complexity and ubiquity. VR cybersecurity training remains a starkly understudied discipline. Studies that evaluated the effectiveness of VR cybersecurity training over traditional methods are required. An engaging and interactive platform can support knowledge retention of the training material. Consequently, an effective form of cybersecurity training is required to support a culture of cybersecurity awareness. Measurements of effectiveness varied throughout the studies, with surveys and observations being the two most utilized forms of evaluating effectiveness. Further research is needed to evaluate the effectiveness of VR cybersecurity training and traditional training. Additionally, research for evaluating if VR cybersecurity training is more effective than traditional methods is vital. This paper proposes a methodology to compare the two cybersecurity training methods and their effectiveness. The proposed framework includes developing both VR and traditional cybersecurity training methods and delivering them to at least 100 users. A quiz along with a survey will be administered and statistically analyzed to determine if there is a difference in knowledge retention and user satisfaction. The aim of this paper is to bring attention to the need to study VR cybersecurity training and its effectiveness compared to traditional training methods. This paper hopes to contribute to the cybersecurity training field by providing an effective way to train users for security awareness. If VR training is deemed more effective, this could create a new direction for cybersecurity training practices.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training

Procedia PDF Downloads 192
991 Gene Expression Analysis for Corals / Zooxanthellae under High Seawater Temperature Stress

Authors: Haruka Ito, Toru Maruyama, Michihiro Ito, Chuya Shinzato, Hiroyuki Fujimura, Yoshikatsu Nakano, Shoichiro Suda, Sachiyo Aburatani, Haruko Takeyama

Abstract:

Clarifying symbiotic relationships is one of the most important theme for understanding the marine eco-system. Coral reef has been regarded as an important environmental resource. Coral holobiont composed by coral, symbiotic microalgae zooxanthellae, and bacteria have complexed relationship. Zooxanthellae mainly supply organic matter to the host corals through their photosynthetic activity. The symbiotic relationship is indispensable for corals but may easily collapses due to the rise of seawater temperature. However, the molecular mechanism how seawater temperature influences their relationships still remain unclear. In this study, the transcriptomic analysis has applied to elucidate the coral-zooxanthellae relationships under high seawater temperature stress. To observe reactions of corals and zooxanthellae against the rise of seawater temperature, meta-gene expression in coral have been analyzed. The branches from six different colonies of a stony coral, Acropora tenuis, were sampled at nine times by 2016 at two locations, Ishikawabaru and South of Sesoko Island, Okinawa, Japan. The mRNAs extracted from the branches including zooxanthellae were sequenced by illumina HiSeq. Gene Set Enrichment Analysis (GSEA) based on hyper geometric distribution was performed. The seawater temperature at 2016 summer was unusually high, which was caused by El Niño event, and the number of zooxanthellae in coral was decreased in August. GSEA derived the several specific genes expressed in A. tenuis under heat stress conditions. The upregulated genes under heat stress highly related with infection immunity. The downregulated genes significantly contained cell cycle related genes. Thu, it is considered that heat stress cause disorder in cell metabolism of A. tenuis, resulting in serious influence to coral holobiont.

Keywords: coral, symbiosis, thermal stress response, transcriptome analysis

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990 Application of Italian Guidelines for Existing Bridge Management

Authors: Giovanni Menichini, Salvatore Giacomo Morano, Gloria Terenzi, Luca Salvatori, Maurizio Orlando

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The “Guidelines for Risk Classification, Safety Assessment, and Structural Health Monitoring of Existing Bridges” were recently approved by the Italian Government to define technical standards for managing the national network of existing bridges. These guidelines provide a framework for risk mitigation and safety assessment of bridges, which are essential elements of the built environment and form the basis for the operation of transport systems. Within the guideline framework, a workflow based on three main points was proposed: (1) risk-based, i.e., based on typical parameters of hazard, vulnerability, and exposure; (2) multi-level, i.e., including six assessment levels of increasing complexity; and (3) multirisk, i.e., assessing structural/foundational, seismic, hydrological, and landslide risks. The paper focuses on applying the Italian Guidelines to specific case studies, aiming to identify the parameters that predominantly influence the determination of the “class of attention”. The significance of each parameter is determined via sensitivity analysis. Additionally, recommendations for enhancing the process of assigning the class of attention are proposed.

Keywords: bridge safety assessment, Italian guidelines implementation, risk classification, structural health monitoring

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989 Characterization of a Newfound Manganese Tungstate Mineral of Hübnerite in Turquoise Gemstone from Miduk Mine, Kerman, Iran

Authors: Zahra Soleimani Rad, Fariborz Masoudi, Shirin Tondkar

Abstract:

Turquoise is one of the most well-known gemstones in Iran. The mineralogy, crystallography, and gemology of Shahr-e-Babak turquoise in Kerman were investigated and the results are presented in this research. The Miduk porphyry copper deposit is positioned in the Shahr-Babak area in Kerman province, Iran. This deposit is located 85 km NW of the Sar-Cheshmeh porphyry copper deposit. Preliminary mineral exploration was carried out from 1967 to 1970. So far, more than fifty diamond drill holes, each reaching a maximum depth of 1013 meters, have provided evidence supporting the presence of significant and promising porphyry copper mineralization at the Miduk deposit. The mineral deposit harbors a quantity of 170 million metric tons of ore, characterized by a mean composition of 0.86% copper (Cu), 0.007% molybdenum (Mo), 82 parts-per-billion gold (Au), and 1.8 parts-per-million silver (Ag). The Supergene enrichment layer, which constitutes the predominant source of copper ore, exhibits an approximate thickness of 50 meters. Petrography shows that the texture is homogeneous. In terms of a gemstone, greasy luster and blue color are seen, and samples are similar to what is commonly known as turquoise. The geometric minerals were detected in XRD analysis by analyzing the data using the x-pert software. From the mineralogical point of view; the turquoise gemstones of Miduk of Kerman consist of turquoise, quartz, mica, and hübnerite. In this article, to our best knowledge, we are stating the hübnerite mineral identified and seen in the Persian turquoise. Based on the obtained spectra, the main mineral of the Miduk samples from the six members of the turquoise family is the turquoise type with identical peaks that can be used as a reference for identification of the Miduk turquoise. This mineral is structurally composed of phosphate units, units of Al, Cu, water, and hydroxyl units, and does not include a Fe unit. In terms of gemology, the quality of a gemstone depends on the quantity of the turquoise phase and the amount of Cu in it according to SEM and XRD analysis.

Keywords: turquoise, hübnerite, XRD analysis, Miduk, Kerman, Iran

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988 The Dressing Field Method of Gauge Symmetries Reduction: Presentation and Examples

Authors: Jeremy Attard, Jordan François, Serge Lazzarini, Thierry Masson

Abstract:

Gauge theories are the natural background for describing geometrically fundamental interactions using principal and associated fiber bundles as dynamical entities. The central notion of these theories is their local gauge symmetry implemented by the local action of a Lie group H. There exist several methods used to reduce the symmetry of a gauge theory, like gauge fixing, bundle reduction theorem or spontaneous symmetry breaking mechanism (SSBM). This paper is a presentation of another method of gauge symmetry reduction, distinct from those three. Given a symmetry group H acting on a fiber bundle and its naturally associated fields (Ehresmann (or Cartan) connection, curvature, matter fields, etc.) there sometimes exists a way to erase (in whole or in part) the H-action by just reconfiguring these fields, i.e. by making a mere change of field variables in order to get new (‘composite‘) fields on which H (in whole or in part) does not act anymore. Two examples: the re-interpretation of the BEHGHK (Higgs) mechanism, on the one hand, and the top-down construction of Tractor and Penrose's Twistor spaces and connections in the framework of conformal Cartan geometry, one the other, will be discussed. They have, of course, nothing to do with each other but the dressing field method can be applied on both to get a new insight. In the first example, it turns out, indeed, that generation of masses in the Standard Model can be separated from the symmetry breaking, the latter being a mere change of field variables, i.e. a dressing. This offers an interpretation in opposition with the one usually found in textbooks. In the second case, the dressing field method applied to the conformal Cartan geometry offer a way of understanding the deep geometric nature of the so-called Tractors and Twistors. The dressing field method, distinct from a gauge transformation (even if it can have apparently the same form), is a systematic way of finding and erasing artificial symmetries of a theory, by a mere change of field variables which redistributes the degrees of freedom of the theories.

Keywords: BEHGHK (Higgs) mechanism, conformal gravity, gauge theory, spontaneous symmetry breaking, symmetry reduction, twistors and tractors

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987 Failure Analysis and Verification Using an Integrated Method for Automotive Electric/Electronic Systems

Authors: Lei Chen, Jian Jiao, Tingdi Zhao

Abstract:

Failures of automotive electric/electronic systems, which are universally considered to be safety-critical and software-intensive, may cause catastrophic accidents. Analysis and verification of failures in these kinds of systems is a big challenge with increasing system complexity. Model-checking is often employed to allow formal verification by ensuring that the system model conforms to specified safety properties. The system-level effects of failures are established, and the effects on system behavior are observed through the formal verification. A hazard analysis technique, called Systems-Theoretic Process Analysis, is capable of identifying design flaws which may cause potential failure hazardous, including software and system design errors and unsafe interactions among multiple system components. This paper provides a concept on how to use model-checking integrated with Systems-Theoretic Process Analysis to perform failure analysis and verification of automotive electric/electronic systems. As a result, safety requirements are optimized, and failure propagation paths are found. Finally, an automotive electric/electronic system case study is used to verify the effectiveness and practicability of the method.

Keywords: failure analysis and verification, model checking, system-theoretic process analysis, automotive electric/electronic system

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986 Attribute Based Comparison and Selection of Modular Self-Reconfigurable Robot Using Multiple Attribute Decision Making Approach

Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

Abstract:

From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability

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985 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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984 Synthetic Cannabinoids: Extraction, Identification and Purification

Authors: Niki K. Burns, James R. Pearson, Paul G. Stevenson, Xavier A. Conlan

Abstract:

In Australian state Victoria, synthetic cannabinoids have recently been made illegal under an amendment to the drugs, poisons and controlled substances act 1981. Identification of synthetic cannabinoids in popular brands of ‘incense’ and ‘potpourri’ has been a difficult and challenging task due to the sample complexity and changes observed in the chemical composition of the cannabinoids of interest. This study has developed analytical methodology for the targeted extraction and determination of synthetic cannabinoids available pre-ban. A simple solvent extraction and solid phase extraction methodology was developed that selectively extracted the cannabinoid of interest. High performance liquid chromatography coupled with UV‐visible and chemiluminescence detection (acidic potassium permanganate and tris (2,2‐bipyridine) ruthenium(III)) were used to interrogate the synthetic cannabinoid products. Mass spectrometry and nuclear magnetic resonance spectroscopy were used for structural elucidation of the synthetic cannabinoids. The tris(2,2‐bipyridine)ruthenium(III) detection was found to offer better sensitivity than the permanganate based reagents. In twelve different brands of herbal incense, cannabinoids were extracted and identified including UR‐144, XLR 11, AM2201, 5‐F‐AKB48 and A796‐260.

Keywords: electrospray mass spectrometry, high performance liquid chromatography, solid phase extraction, synthetic cannabinoids

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983 Persian Garden Design and Climate Case Studies: Shahzadeh-Mahan and Shah Garden

Authors: Raheleh Saifiabolhassan

Abstract:

Gardens symbolize human effort to bring Eden to earth and are defined as the purest pleasures and the greatest inspiration for men. According to Persian mythology, a garden called "Paris" is a magical, perfumed place populated by beautiful and angelic creatures. "Pardis" comes from the word "paridaiza," which means "walled garden." Gardening has always been a worldwide attraction due to the abundance of green space, and desert gardens are no exception. Because most historical garden designs use a similar pattern, such as Chahar-Bagh, climate effects have not been considered. The purpose of studying these general designs was to determine whether location and weather conditions are affecting them. So, two gardens were chosen for comparison: a desert (Shahzadeh-Mahan) and a humid garden (Shah) and compared their geometry, irrigation system, entrances, and pavilions. The findings of the study revealed that there are several notable differences among their architectural principles. For example, the desert garden design is introverted with transparent surfaces and a single focal point, while the moderate garden is extraverted with high complexity and multiple perspectives. In conclusion, the study recognizes the richness and significance of the Persian garden concept, which can be applied in many different contexts.

Keywords: Pardis, Chahar-bagh, Persian garden, temperate, humid climate, geometry, pavilion, irrigations, culture

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982 Combined PV Cooling and Nighttime Power Generation through Smart Thermal Management of Photovoltaic–Thermoelectric Hybrid Systems

Authors: Abdulrahman M. Alajlan, Saichao Dang, Qiaoqiang Gan

Abstract:

Photovoltaic (PV) cells, while pivotal for solar energy harnessing, confront a challenge due to the presence of persistent residual heat. This thermal energy poses significant obstacles to the performance and longevity of PV cells. Mitigating this thermal issue is imperative, particularly in tropical regions where solar abundance coexists with elevated ambient temperatures. In response, a sustainable and economically viable solution has been devised, incorporating water-passive cooling within a Photovoltaic-Thermoelectric (PV-TEG) hybrid system to address PV cell overheating. The implemented system has significantly reduced the operating temperatures of PV cells, achieving a notable reduction of up to 15 °C below the temperature observed in standalone PV systems. In addition, a thermoelectric generator (TEG) integrated into the system significantly enhances power generation, particularly during nighttime operation. The developed hybrid system demonstrates its capability to generate power at a density of 0.5 Wm⁻² during nighttime, which is sufficient to concurrently power multiple light-emitting diodes, demonstrating practical applications for nighttime power generation. Key findings from this research include a consistent temperature reduction exceeding 10 °C for PV cells, translating to a 5% average enhancement in PV output power compared to standalone PV systems. Experimental demonstrations underscore nighttime power generation of 0.5 Wm⁻², with the potential to achieve 0.8 Wm⁻² through simple geometric optimizations. The optimal cooling of PV cells is determined by the volume of water in the heat storage unit, exhibiting an inverse relationship with the optimal performance for nighttime power generation. Furthermore, the TEG output effectively powers a lighting system with up to 5 LEDs during the night. This research not only proposes a practical solution for maximizing solar radiation utilization but also charts a course for future advancements in energy harvesting technologies.

Keywords: photovoltaic-thermoelectric systems, nighttime power generation, PV thermal management, PV cooling

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981 A Comparative Case Study on Teaching Romanian Language to Foreign Students: Swedes in Lund versus Arabs in Alba Iulia

Authors: Lucian Vasile Bagiu, Paraschiva Bagiu

Abstract:

The study is a contrastive essay on language acquisition and learning and follows the outcomes of teaching Romanian language to foreign students both at Lund University, Sweden (from 2014 to 2017) and at '1 Decembrie 1918' University in Alba Iulia, Romania (2017-2018). Having employed the same teaching methodology (on campus, same curricula) for the same level of study (beginners’ level: A1-A2), the essay focuses on the written exam at the end of the semester. The study argues on grammar exercises concerned with: the indefinite and the definite article; the conjugation of verbs in the present indicative; the possessive; verbs in the past tense; the subjunctive; the degrees of comparison for adjectives. Identifying similar errors when solving identical grammar exercises by different groups of foreign students is an opportunity to emphasize the major challenges any foreigner has to face and overcome when trying to acquire Romanian language. The conclusion draws attention to the complexity of the morphology of Romanian language in several key elements which may be insurmountable for a foreign speaker no matter if the language acquisition takes place in a foreign country or a Romanian university.

Keywords: Arab students, morphological errors, Romanian language, Swedish students, written exam

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980 Low Light Image Enhancement with Multi-Stage Interconnected Autoencoders Integration in Pix to Pix GAN

Authors: Muhammad Atif, Cang Yan

Abstract:

The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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979 A Single Feature Probability-Object Based Image Analysis for Assessing Urban Landcover Change: A Case Study of Muscat Governorate in Oman

Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

Abstract:

The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

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978 Performants: Making the Organization of Concerts Easier

Authors: Ioannis Andrianakis, Panagiotis Panagiotopoulos, Kyriakos Chatzidimitriou, Dimitrios Tampakis, Manolis Falelakis

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Live music, whether performed in organized venues, restaurants, hotels or any other spots, creates value chains that support and develop local economies and tourism development. In this paper, we describe PerformAnts, a platform that increases the mobility of musicians and their accessibility to remotely located venues by rationalizing the cost of live acts. By analyzing the event history and taking into account their potential availability, the platform provides bespoke recommendations to both bands and venues while also facilitating the organization of tours and helping rationalize transportation expenses by realizing an innovative mechanism called “chain booking”. Moreover, the platform provides an environment where complicated tasks such as technical and financial negotiations, concert promotion or copyrights are easily manipulated by users using best practices. The proposed solution provides important benefits to the whole spectrum of small/medium size concert organizers, as the complexity and the cost of the production are rationalized. The environment is also very beneficial for local talent, musicians that are very mobile, venues located away from large urban areas or in touristic destinations, and managers who will be in a position to coordinate a larger number of musicians without extra effort.

Keywords: machine learning, music industry, creative industries, web applications

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977 Evaluation of UI for 3D Visualization-Based Building Information Applications

Authors: Monisha Pattanaik

Abstract:

In scenarios where users have to work with large amounts of hierarchical data structures combined with visualizations (For example, Construction 3d Models, Manufacturing equipment's models, Gantt charts, Building Plans), the data structures have a high density in terms of consisting multiple parent nodes up to 50 levels and their siblings to descendants, therefore convey an immediate feeling of complexity. With customers moving to consumer-grade enterprise software, it is crucial to make sophisticated features made available to touch devices or smaller screen sizes. This paper evaluates the UI component that allows users to scroll through all deep density levels using a slider overlay on top of the hierarchy table, performing several actions to focus on one set of objects at any point in time. This overlay component also solves the problem of excessive horizontal scrolling of the entire table on a fixed pane for a hierarchical table. This component can be customized to navigate through parents, only siblings, or a specific component of the hierarchy only. The evaluation of the UI component was done by End Users of application and Human-Computer Interaction (HCI) experts to test the UI component's usability with statistical results and recommendations to handle complex hierarchical data visualizations.

Keywords: building information modeling, digital twin, navigation, UI component, user interface, usability, visualization

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976 Identifying Factors for Evaluating Livability Potential within a Metropolis: A Case of Kolkata

Authors: Arpan Paul, Joy Sen

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Livability is a holistic concept whose factors include many complex characteristics and levels of interrelationships among them. It has been considered as people’s need for public amenities and is recognized as a major element to create social welfare. The concept and principles of livability are essential for recognizing the significance of community well-being. The attributes and dimensions of livability are also important aspects to measure the overall quality of environment. Livability potential is mainly considered as the capacity to develop into the overall well-being of an urban area in future. The intent of the present study is to identify the prime factors to evaluate livability potential within a metropolis. For ground level case study, the paper has selected Kolkata Metropolitan Area (KMA) as it has wide physical, social, and economic variations within it. The initial part of the study deals with detailed literature review on livability and its significance of evaluating its potential within a metropolis. The next segment is dedicated for identifying the primary factors which would evaluate livability potential within a metropolis. In pursuit of identifying primary factors, which have a direct impact on urban livability, this study delineates the metropolitan area into various clusters, having their distinct livability potential. As a final outcome of the study, variations of livability potential of those selected clusters are highlighted to explain the complexity of the metropolitan development.

Keywords: Kolkata Metropolitan Area (KMA), livability potential, metropolis, wellbeing

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975 Information Theoretic Approach for Beamforming in Wireless Communications

Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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974 Peak Data Rate Enhancement Using Switched Micro-Macro Diversity in Cellular Multiple-Input-Multiple-Output Systems

Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

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With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple output systems, orthogonal frequency division multiplexing

Procedia PDF Downloads 289
973 CTHTC: A Convolution-Backed Transformer Architecture for Temporal Knowledge Graph Embedding with Periodicity Recognition

Authors: Xinyuan Chen, Mohd Nizam Husen, Zhongmei Zhou, Gongde Guo, Wei Gao

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Temporal Knowledge Graph Completion (TKGC) has attracted increasing attention for its enormous value; however, existing models lack capabilities to capture both local interactions and global dependencies simultaneously with evolutionary dynamics, while the latest achievements in convolutions and Transformers haven't been employed in this area. What’s more, periodic patterns in TKGs haven’t been fully explored either. To this end, a multi-stage hybrid architecture with convolution-backed Transformers is introduced in TKGC tasks for the first time combining the Hawkes process to model evolving event sequences in a continuous-time domain. In addition, the seasonal-trend decomposition is adopted to identify periodic patterns. Experiments on six public datasets are conducted to verify model effectiveness against state-of-the-art (SOTA) methods. An extensive ablation study is carried out accordingly to evaluate architecture variants as well as the contributions of independent components in addition, paving the way for further potential exploitation. Besides complexity analysis, input sensitivity and safety challenges are also thoroughly discussed for comprehensiveness with novel methods.

Keywords: temporal knowledge graph completion, convolution, transformer, Hawkes process, periodicity

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972 Working Together: The Nature of Collaborative Legal and Social Services and Their Influence on Practice

Authors: Jennifer Donovan

Abstract:

Practice collaborations between legal assistance and social support services have emerged as a growing framework worldwide for delivering services to clients with high degrees of disadvantage, vulnerability and complexity. In Australia, the past five years has seen a significant growth in these socio-legal collaborations, with programs being delivered through legal, social service and health organizations and addressing a range of issues including mental health, immigration, parental child abduction and domestic violence. This presentation is based on research currently mapping the nature of these collaborations in Australia and exploring the influence that collaborating professions are having on each other’s practice. In a similar way to problem-solving courts being seen as a systematic take up of therapeutic jurisprudence in the court setting, socio-legal collaborations have the potential to be a systematic take up of therapeutic jurisprudence in an advice setting. This presentation will explore the varied ways in which socio-legal collaboration is being implemented in these programs. It will also explore the development of interdisciplinary therapeutic jurisprudence within them, with preliminary findings suggesting that both legal and social service practice is being influenced by the collaborative setting, with legal practice showing a more therapeutic orientation and social service professions, such as social work, moving toward a legal and rights orientation.

Keywords: collaboration, socio-legal, Australia, therapeutic jurisprudence

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971 Integrating Building Information Modeling into Facilities Management Operations

Authors: Mojtaba Valinejadshoubi, Azin Shakibabarough, Ashutosh Bagchi

Abstract:

Facilities such as residential buildings, office buildings, and hospitals house large density of occupants. Therefore, a low-cost facility management program (FMP) should be used to provide a satisfactory built environment for these occupants. Facility management (FM) has been recently used in building projects as a critical task. It has been effective in reducing operation and maintenance cost of these facilities. Issues of information integration and visualization capabilities are critical for reducing the complexity and cost of FM. Building information modeling (BIM) can be used as a strong visual modeling tool and database in FM. The main objective of this study is to examine the applicability of BIM in the FM process during a building’s operational phase. For this purpose, a seven-storey office building is modeled Autodesk Revit software. Authors integrated the cloud-based environment using a visual programming tool, Dynamo, for the purpose of having a real-time cloud-based communication between the facility managers and the participants involved in the project. An appropriate and effective integrated data source and visual model such as BIM can reduce a building’s operational and maintenance costs by managing the building life cycle properly.

Keywords: building information modeling, facility management, operational phase, building life cycle

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970 Virtual Container Yard: Assessing the Perceived Impact of Legal Implications to Container Carriers

Authors: L. Edirisinghe, P. Mukherjee, H. Edirisinghe

Abstract:

Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Keywords: virtual container yard, legal, maritime law, inventory

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969 Linguistic Features for Sentence Difficulty Prediction in Aspect-Based Sentiment Analysis

Authors: Adrian-Gabriel Chifu, Sebastien Fournier

Abstract:

One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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968 Role of Matric Suction in Mechanics behind Swelling Characteristics of Expansive Soils

Authors: Saloni Pandya, Nikhil Sharma, Ajanta Sachan

Abstract:

Expansive soils in the unsaturated state are part of vadose zone and encountered in several arid and semi-arid parts of the world. Influence of high temperature, low precipitation and alternate cycles of wetting and drying are responsible for the chemical weathering of rocks, which results in the formation of expansive soils. Shrinkage-swelling (expansive) soils cover a substantial portion of area in India. Damages caused by expansive soils to various geotechnical structures are alarming. Matric suction develops in unsaturated soil due to capillarity and surface tension phenomena. Matric suction influences the geometric arrangement of soil skeleton, which induces the volume change behaviour of expansive soil. In the present study, an attempt has been made to evaluate the role of matric suction in the mechanism behind swelling characteristics of expansive soil. Four different soils have been collected from different parts of India for the current research. Soil sample S1, S2, S3 and S4 were collected from Nagpur, Bharuch, Bharuch-Dahej highway and Ahmedabad respectively. DFSI (Differential Free Swell Index) of these soils samples; S1, S2, S3, and S4; were determined to be 134%, 104%, 70% and 30% respectively. X-ray diffraction analysis of samples exhibited that percentage of Montmorillonite mineral present in the soils reduced with the decrease in DFSI. A series of constant volume swell pressure tests and in-contact filter paper tests were performed to evaluate swelling pressure and matric suction of all four soils at 30% saturation and 1.46 g/cc dry density. Results indicated that soils possessing higher DFSI exhibited higher matric suction as compared to lower DFSI expansive soils. Significant influence of matric suction on swelling pressure of expansive soils was observed with varying DFSI values. Higher matric suction of soil might govern the water uptake in the interlayer spaces of Montmorillonite mineral present in expansive soil leading to crystalline swelling.

Keywords: differential free swell index, expansive soils, matric suction, swelling pressure

Procedia PDF Downloads 144
967 Deep Learning to Improve the 5G NR Uplink Control Channel

Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

Abstract:

The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

Procedia PDF Downloads 50
966 Architectural and Sedimentological Parameterization for Reservoir Quality of Miocene Onshore Sandstone, Borneo

Authors: Numair A. Siddiqui, Usman Muhammad, Manoj J. Mathew, Ramkumar M., Benjamin Sautter, Muhammad A. K. El-Ghali, David Menier, Shiqi Zhang

Abstract:

The sedimentological parameterization of shallow-marine siliciclastic reservoirs in terms of reservoir quality and heterogeneity from outcrop study can help improve the subsurface reservoir prediction. An architectural analysis has documented variations in sandstone geometry and rock properties within shallow-marine sandstone exposed in the Miocene Sandakan Formation of Sabah, Borneo. This study demonstrates reservoir sandstone quality assessment for subsurface rock evaluation, from well-exposed successions of the Sandakan Formation, Borneo, with which applicable analogues can be identified. The analyses were based on traditional conventional field investigation of outcrops, grain-size and petrographic studies of hand specimens of different sandstone facies and gamma-ray and permeability measurements. On the bases of these evaluations, the studied sandstone was grouped into three qualitative reservoir rock classes; high (Ø=18.10 – 43.60%; k=1265.20 – 5986.25 mD), moderate (Ø=17.60 – 37%; k=21.36 – 568 mD) and low quality (Ø=3.4 – 15.7%; k=3.21 – 201.30 mD) for visualization and prediction of subsurface reservoir quality. These results provided analogy for shallow marine sandstone reservoir complexity that can be utilized in the evaluation of reservoir quality of regional and subsurface analogues.

Keywords: architecture and sedimentology, subsurface rock evaluation, reservoir quality, borneo

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965 Comparing UV-based and O₃-Based AOPs for Removal of Emerging Contaminants from Food Processing Digestate Sludge

Authors: N. Moradi, C. M. Lopez-Vazquez, H. Garcia Hernandez, F. Rubio Rincon, D. Brdanovic, Mark van Loosdrecht

Abstract:

Advanced oxidation processes have been widely used for disinfection, removal of residual organic material, and for the removal of emerging contaminants from drinking water and wastewater. Yet, the application of these technologies to sludge treatment processes has not gained enough attention, mostly, considering the complexity of the sludge matrix. In this research, ozone and UV/H₂O₂ treatment were applied for the removal of emerging contaminants from a digestate supernatant. The removal of the following compounds was assessed:(i) salicylic acid (SA) (a surrogate of non-stradiol anti-inflammatory drugs (NSAIDs)), and (ii) sulfamethoxazole (SMX), sulfamethazine (SMN), and tetracycline (TCN) (the most frequent human and animal antibiotics). The ozone treatment was carried out in a plexiglass bubble column reactor with a capacity of 2.7 L; the system was equipped with a stirrer and a gas diffuser. The UV and UV/H₂O₂ treatments were done using a LED set-up (PearlLab beam device) dosing H₂O₂. In the ozone treatment evaluations, 95 % of the three antibiotics were removed during the first 20 min of exposure time, while an SA removal of 91 % occurred after 8 hours of exposure time. In the UV treatment evaluations, when adding the optimum dose of hydrogen peroxide (H₂O₂:COD molar ratio of 0.634), 36% of SA, 82% of TCN, and more than 90 % of both SMX and SMN were removed after 8 hours of exposure time. This study concluded that O₃ was more effective than UV/H₂O₂ in removing emerging contaminants from the digestate supernatant.

Keywords: digestate sludge, emerging contaminants, ozone, UV-AOP

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964 Effects of Nano-Coating on the Mechanical Behavior of Nanoporous Metals

Authors: Yunus Onur Yildiz, Mesut Kirca

Abstract:

In this study, mechanical properties of a nanoporous metal coated with a different metallic material are studied through a new atomistic modelling technique and molecular dynamics (MD) simulations. This new atomistic modelling technique is based on the Voronoi tessellation method for the purpose of geometric representation of the ligaments. With the proposed technique, atomistic models of nanoporous metals which have randomly oriented ligaments with non-uniform mass distribution along the ligament axis can be generated by enabling researchers to control both ligament length and diameter. Furthermore, by the utilization of this technique, atomistic models of coated nanoporous materials can be numerically obtained for further mechanical or thermal characterization. In general, this study consists of two stages. At the first stage, we use algorithms developed for generating atomic coordinates of the coated nanoporous material. In this regard, coordinates of randomly distributed points are determined in a controlled way to be employed in the establishment of the Voronoi tessellation, which results in randomly oriented and intersected line segments. Then, line segment representation of the Voronoi tessellation is transformed to atomic structure by a special process. This special process includes generation of non-uniform volumetric core region in which atoms can be generated based on a specific crystal structure. As an extension, this technique can be used for coating of nanoporous structures by creating another volumetric region encapsulating the core region in which atoms for the coating material are generated. The ultimate goal of the study at this stage is to generate atomic coordinates that can be employed in the MD simulations of randomly organized coated nanoporous structures. At the second stage of the study, mechanical behavior of the coated nanoporous models is investigated by examining deformation mechanisms through MD simulations. In this way, the effect of coating on the mechanical behavior of the selected material couple is investigated.

Keywords: atomistic modelling, molecular dynamic, nanoporous metals, voronoi tessellation

Procedia PDF Downloads 266