Search results for: enhanced geothermal systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11762

Search results for: enhanced geothermal systems

3752 Solar-Powered Adsorption Cooling System: A Case Study on the Climatic Conditions of Al Minya

Authors: El-Sadek H. Nour El-deen, K. Harby

Abstract:

Energy saving and environment friendly applications are turning out to be one of the most important topics nowadays. In this work, a simulation analysis using TRNSYS software has been carried out to study the benefit of employing a solar adsorption cooling system under the climatic conditions of Al-Minya city, Egypt. A theoretical model was carried out on a two bed adsorption cooling system employing granular activated carbon-HFC-404A as working pair. Temporal and averaged history of solar collector, adsorbent beds, evaporator and condenser has been shown. System performance in terms of daily average cooling capacity and average coefficient of performance around the year has been investigated. The results showed that maximum yearly average coefficient of performance (COP) and cooling capacity are about 0.26 and 8 kW respectively. The maximum value of the both average cooling capacity and COP cyclic is directly proportional to the maximum solar radiation. The system performance was found to be increased with the average ambient temperature. Finally, the proposed solar powered adsorption cooling systems can be used effectively under Al-Minya climatic conditions.

Keywords: adsorption, cooling, Egypt, environment, solar energy

Procedia PDF Downloads 156
3751 Internet of Assets: A Blockchain-Inspired Academic Program

Authors: Benjamin Arazi

Abstract:

Blockchain is the technology behind cryptocurrencies like Bitcoin. It revolutionizes the meaning of trust in the sense of offering total reliability without relying on any central entity that controls or supervises the system. The Wall Street Journal states: “Blockchain Marks the Next Step in the Internet’s Evolution”. Blockchain was listed as #1 in Linkedin – The Learning Blog “most in-demand hard skills needed in 2020”. As stated there: “Blockchain’s novel way to store, validate, authorize, and move data across the internet has evolved to securely store and send any digital asset”. GSMA, a leading Telco organization of mobile communications operators, declared that “Blockchain has the potential to be for value what the Internet has been for information”. Motivated by these seminal observations, this paper presents the foundations of a Blockchain-based “Internet of Assets” academic program that joins under one roof leading application areas that are characterized by the transfer of assets over communication lines. Two such areas, which are pillars of our economy, are Fintech – Financial Technology and mobile communications services. The next application in line is Healthcare. These challenges are met based on available extensive professional literature. Blockchain-based assets communication is based on extending the principle of Bitcoin, starting with the basic question: If digital money that travels across the universe can ‘prove its own validity’, can this principle be applied to digital content. A groundbreaking positive answer here led to the concept of “smart contract” and consequently to DLT - Distributed Ledger Technology, where the word ‘distributed’ relates to the non-existence of reliable central entities or trusted third parties. The terms Blockchain and DLT are frequently used interchangeably in various application areas. The World Bank Group compiled comprehensive reports, analyzing the contribution of DLT/Blockchain to Fintech. The European Central Bank and Bank of Japan are engaged in Project Stella, “Balancing confidentiality and auditability in a distributed ledger environment”. 130 DLT/Blockchain focused Fintech startups are now operating in Switzerland. Blockchain impact on mobile communications services is treated in detail by leading organizations. The TM Forum is a global industry association in the telecom industry, with over 850 member companies, mainly mobile operators, that generate US$2 trillion in revenue and serve five billion customers across 180 countries. From their perspective: “Blockchain is considered one of the digital economy’s most disruptive technologies”. Samples of Blockchain contributions to Fintech (taken from a World Bank document): Decentralization and disintermediation; Greater transparency and easier auditability; Automation & programmability; Immutability & verifiability; Gains in speed and efficiency; Cost reductions; Enhanced cyber security resilience. Samples of Blockchain contributions to the Telco industry. Establishing identity verification; Record of transactions for easy cost settlement; Automatic triggering of roaming contract which enables near-instantaneous charging and reduction in roaming fraud; Decentralized roaming agreements; Settling accounts per costs incurred in accordance with agreement tariffs. This clearly demonstrates an academic education structure where fundamental technologies are studied in classes together with these two application areas. Advanced courses, treating specific implementations then follow separately. All are under the roof of “Internet of Assets”.

Keywords: blockchain, education, financial technology, mobile telecommunications services

Procedia PDF Downloads 175
3750 Machine Learning Invariants to Detect Anomalies in Secure Water Treatment

Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

Procedia PDF Downloads 175
3749 Sustainable Renovation and Restoration of the Rural — Based on the View Point of Psychology

Authors: Luo Jin China, Jin Fang

Abstract:

Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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3748 Numerical Simulation of Air Flow, Exhaust and Their Mixture in a Helicopter Exhaust Injective Cooler

Authors: Mateusz Paszko, Konrad Pietrykowski, Krzysztof Skiba

Abstract:

Due to low-altitude and relatively low flight speed, today’s combat assets like missile weapons equipped with infrared guidance systems are one of the most important threats to the helicopters performing combat missions. Especially meaningful in helicopter aviation is infrared emission by exhaust gases, regressed to the surroundings. Due to high temperature, exhaust gases are a major factor in detectability of a helicopter performing air combat operations. This study presents the results of simulating the flow of the mixture of exhaust and air in the flow duct of an injective exhaust cooler, adapted to cooperate with the PZL 10W turbine engine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted for set flight conditions of the PZL W-3 Falcon helicopter. The conclusions resulting from the conducted numerical computations should allow for optimisation of the flow duct geometry in the cooler, in order to achieve the greatest possible temperature reduction of exhaust exiting into the surroundings. It is expected that the obtained results should be useful for further works related to the development of the final version of exhaust cooler for the PZL W-3 Falcon helicopter.

Keywords: exhaust cooler, helicopter, numerical simulation, stealth

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3747 System Identification in Presence of Outliers

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

Abstract:

The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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3746 Analytical Investigation on Seismic Behavior of Infilled Reinforced Concrete Frames Strengthened with Precast Diagonal Concrete Panels

Authors: Ceyhun Aksoylu, Rifat Sezer

Abstract:

In this study, a strengthening method applicable without any evacuation process was investigated. In this analytical study, the pushover analysis results carry out by using the software of SAP2000. For this purpose, 1/3 scaled, 1-bay and 2-story R/C seven frames having usual deficiencies faults produced, one of which were not strengthened, but having brick-infill wall and the other 3 frames with infill walls strengthened with various shaped of high strength-precast diagonal concrete panels. The prepared analytical models investigated under reversed-cyclic loading that resembles the seismic effect. As a result of the analytical study, the properties of the reinforced concrete frames, such as strength, rigidity, energy dissipation capacity, etc. were determined and the strengthened models were compared with the unstrengthened one having the same properties. As a result of this study, the contributions of precast diagonal concrete applied on the infill walls of the existing frame systems against seismic effects were introduced with its advantages and disadvantages.

Keywords: RC frame, seismic effect, infill wall, strengthening, precast diagonal concrete panel, pushover analysis

Procedia PDF Downloads 344
3745 Technical Determinants of the Success of the Quality Management Systems Implementation in Automotive Industry

Authors: Agnieszka Misztal

Abstract:

The popularity of the quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with the demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel appropriate to focus attention on the selection of companies aspiring to quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car), 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). Identified determinants were divided in two types of criteria into: internal and external, as well as: hard and soft. The article presents hard - technical factors that automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: automotive industry, quality management system, automotive technology, automotive company

Procedia PDF Downloads 398
3744 Emotion Recognition with Occlusions Based on Facial Expression Reconstruction and Weber Local Descriptor

Authors: Jadisha Cornejo, Helio Pedrini

Abstract:

Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

Procedia PDF Downloads 177
3743 Optimal Sizes of Battery Energy Storage Systems for Economic Operation in Microgrid

Authors: Sirus Mohammadi, Sara Ansari, Darush dehghan, Habib Hoshyari

Abstract:

Batteries for storage of electricity from solar and wind generation farms are a key element in the success of sustainability. In recent years, due to large integration of Renewable Energy Sources (RESs) like wind turbine and photovoltaic unit into the Micro-Grid (MG), the necessity of Battery Energy Storage (BES) has increased dramatically. The BES has several benefits and advantages in the MG-based applications such as short term power supply, power quality improvement, facilitating integration of RES, ancillary service and arbitrage. This paper presents the cost-based formulation to determine the optimal size of the BES in the operation management of MG. Also, some restrictions, i.e. power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction should be considered as well. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG.

Keywords: microgrid, energy storage system, optimal sizing, net present value

Procedia PDF Downloads 492
3742 High-Frequency Cryptocurrency Portfolio Management Using Multi-Agent System Based on Federated Reinforcement Learning

Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

Abstract:

Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

Procedia PDF Downloads 114
3741 Influence of the Flow Rate Ratio in a Jet Pump on the Size of Air Bubbles

Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

Abstract:

In waste water treatment processes, aeration introduces air into a liquid. In these systems, air is introduced by different devices submerged in the waste water. Smaller bubbles result in more bubble surface area per unit of volume and higher oxygen transfer efficiency. Jet pumps are devices that use air bubbles and are widely used in waste water treatment processes. The principle of jet pumps is their ability to transfer energy of one fluid, called primary or motive, into a secondary fluid or gas. These pumps have no moving parts and are able to work in remote areas under extreme conditions. The objective of this work is to study experimentally the characteristics of the jet pump and the size of air bubbles in the laboratory water tank. The effect of flow rate ratio on pump performance is investigated in order to have a better understanding about pump behavior under various conditions, in order to determine the efficiency of receiving air bubbles different sizes. The experiments show that we should take care when increasing the flow rate ratio while seeking to decrease bubble size in the outlet flow. This study will help improve and extend the use of the jet pump in many practical applications.

Keywords: jet pump, air bubbles size, retention time, waste water

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3740 Escaping the Trauma: A Psychological Study of Jonathan Safran Foer’s Extremely Loud & Incredibly Close

Authors: Mahima Thakur

Abstract:

Trauma rehabilitation requires both repairing physical injury and reconstructing broken narrative systems. The trauma's aftereffects entwine the broken patterns, allowing a cohesive narrative to emerge. In this article, the book Extremely Loud and Incredibly Close by Jonathan Safran Foer is discussed from a psychoanalytic perspective. The paper discusses the 9/11 attacks and their effects on those who suffered and lost family members during the catastrophe. The primary character of the novel, Oskar, along with his grandfather and grandmother, each have unique trauma escape stories that will be examined in light of Cathy Caruth and Geoffery H. Hartman‘s study. The text's numerous horrifying repetitions function as a narration strategy that not only captures the awareness of trauma but also gives the reader the psychological feature to overcome its deadening effects. This article explores the role that communication may have in assisting individuals in overcoming trauma. In addition to more research on traumatic memories, Dominick LaCapra's trauma theory's notions of "working through" and "acting out" highlight the need of communication in overcoming trauma and attempting to live outside of it.

Keywords: trauma theory, Cathy Caruth, memories, escapes, communication

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3739 The Role of NAD+ and Nicotinamide (Vitamin B3) in Glaucoma: A Literature Review

Authors: James Pietris

Abstract:

Glaucoma is a collection of irreversible optic neuropathies which, if left untreated, lead to severe visual field loss. These diseases are a leading cause of blindness across the globe and are estimated to affect approximately 80 million people, particularly women and people of Asian descent.1This represents a major burden on healthcare systems worldwide. Recently, there has been increasing interest in the potential of nicotinamide (vitamin B3) as a novel option in the management of glaucoma. This review aims to analyse the currently available literature to determine whether there is evidence of an association between nicotinamide adenine dinucleotide (NAD+) and glaucomatous optic neuropathy and whether nicotinamide has the potential to prevent or reverse these effects. The literature showed a strong connection between reduced NAD+ levels and retinal ganglion cell dysfunction through multiple different studies. There is also evidence of the positive effect of nicotinamide supplementation on retinal ganglion cell function in models of mouse glaucoma and in a study involving humans. Based on the literature findings, a recommendation has been made that more research into the efficacy, appropriate dosing, and potential side effects of nicotinamide supplementation is needed before it can be definitively determined whether it is appropriate for widespread prophylactic and therapeutic use against glaucoma in humans.

Keywords: glaucoma, nicotinamide, vitamin B3, optic neuropathy

Procedia PDF Downloads 104
3738 3D Elasticity Analysis of Laminated Composite Plate Using State Space Method

Authors: Prathmesh Vikas Patil, Yashaswini Lomte Patil

Abstract:

Laminated composite materials have considerable attention in various engineering applications due to their exceptional strength-to-weight ratio and mechanical properties. The analysis of laminated composite plates in three-dimensional (3D) elasticity is a complex problem, as it requires accounting for the orthotropic anisotropic nature of the material and the interactions between multiple layers. Conventional approaches, such as the classical plate theory, provide simplified solutions but are limited in performing exact analysis of the plate. To address such a challenge, the state space method emerges as a powerful numerical technique for modeling the behavior of laminated composites in 3D. The state-space method involves transforming the governing equations of elasticity into a state-space representation, enabling the analysis of complex structural systems in a systematic manner. Here, an effort is made to perform a 3D elasticity analysis of plates with cross-ply and angle-ply laminates using the state space approach. The state space approach is used in this study as it is a mixed formulation technique that gives the displacements and stresses simultaneously with the same level of accuracy.

Keywords: cross ply laminates, angle ply laminates, state space method, three-dimensional elasticity analysis

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3737 A Hybrid Model of Goal, Integer and Constraint Programming for Single Machine Scheduling Problem with Sequence Dependent Setup Times: A Case Study in Aerospace Industry

Authors: Didem Can

Abstract:

Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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3736 Simulation as a Problem-Solving Spotter for System Reliability

Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

Abstract:

An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

Procedia PDF Downloads 358
3735 Hierarchical Scheme for Detection of Rotating Mimo Visible Light Communication Systems Using Mobile Phone Camera

Authors: Shih-Hao Chen, Chi-Wai Chow

Abstract:

Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) visible light communication (VLC) system. The MIMO VLC system using the popular mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from n x n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding the received RGB LED array signals is detecting the direction of received array signals. If the LED transmitter (Tx) is rotated, the signal may not be received correctly and cause an error in the received signal. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n x n RGB LED array as the MIMO Tx. A novel two dimension Hadamard coding scheme is proposed and demonstrated. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

Keywords: Visible Light Communication (VLC), Multiple-input and multiple-output (MIMO), Red-Green-Blue (RGB), Hadamard coding scheme

Procedia PDF Downloads 415
3734 Intrabody Communication Using Different Ground Configurations in Digital Door Lock

Authors: Daewook Kim, Gilwon Yoon

Abstract:

Intrabody communication (IBC) is a new way of transferring data using human body as a medium. Minute current can travel though human body without any harm. IBC can remove electrical wires for human area network. IBC can be also a secure communication network system unlike wireless networks which can be accessed by anyone with bad intentions. One of the IBC systems is based on frequency shift keying modulation where individual data are transmitted to the external devices for the purpose of secure access such as digital door lock. It was found that the quality of IBC data transmission was heavily dependent on ground configurations of electronic circuits. Reliable IBC transmissions were not possible when both of the transmitter and receiver used batteries as circuit power source. Transmission was reliable when power supplies were used as power source for both transmitting and receiving sites because the common ground was established through the grounds of instruments such as power supply and oscilloscope. This was due to transmission dipole size and the ground effects of floor and AC power line. If one site used battery as power source and the other site used the AC power as circuit power source, transmission was possible.

Keywords: frequency shift keying, ground, intrabody, communication, door lock

Procedia PDF Downloads 415
3733 Integrating AI into Breast Cancer Diagnosis: Aligning Perspectives for Effective Clinical Practice

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

Abstract:

Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

Procedia PDF Downloads 57
3732 Global Indicators of Successful Remote Monitoring Adoption Applying Diffusion of Innovation Theory

Authors: Danika Tynes

Abstract:

Innovations in technology have implications for sustainable development in health and wellness. Remote monitoring is one innovation for which the evidence-base has grown to support its viability as a quality healthcare delivery adjunct. This research reviews global data on telehealth adoption, in particular, remote monitoring, and the conditions under which its success becomes more likely. System-level indicators were selected to represent four constructs of DoI theory (relative advantage, compatibility, complexity, and observability) and assessed against 5 types of Telehealth (Teleradiology, Teledermatology, Telepathology, Telepsychology, and Remote Monitoring) using ordinal logistic regression. Analyses include data from 84 countries, as extracted from the World Health Organization, World Bank, ICT (Information Communications Technology) Index, and HDI (Human Development Index) datasets. Analyses supported relative advantage and compatibility as the strongest influencers of remote monitoring adoption. Findings from this research may help focus on the allocation of resources, as a sustainability concern, through consideration of systems-level factors that may influence the success of remote monitoring adoption.

Keywords: remote monitoring, diffusion of innovation, telehealth, digital health

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3731 Perception-Oriented Model Driven Development for Designing Data Acquisition Process in Wireless Sensor Networks

Authors: K. Indra Gandhi

Abstract:

Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: data acquisition, model-driven development, separation of concern, wireless sensor networks

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3730 Accelerated Evaluation of Structural Reliability under Tsunami Loading

Authors: Sai Hung Cheung, Zhe Shao

Abstract:

It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

Procedia PDF Downloads 673
3729 Introduction of Knowledge Management in a Public Sector Organization in India

Authors: Siddharth Vashisth, Varun Mathur

Abstract:

This review provides an overview of the impact that implementation of various Knowledge Management (KM) strategies has had on the growth of a department in a Public Sector Company in India. In a regulated utility controlled by the government, the growth of an organization such as Hindustan Petroleum Corporation Limited (HPCL) had depended largely on the efficiencies of the systems and its people. However, subsequent to the de-regularization & to the entry of the private competition, the need for a ‘systematic templating’ of knowledge was recognized. This necessitated the introduction of Knowledge Management Centre (KMC). Projects & Pipelines Department (P&P) of HPCL introduced KMC that contributed significantly towards KM by adopting various strategies such as standardization, leveraging information system, competency enhancement, and improvements & innovations. These strategies gave both tangible as well as intangible benefits towards KM. Knowledge, technology & people are the three pillars that need to be catered for effective knowledge management in any organization. In HPCL, the initiative of KMC has served as an intermediary between these three major pillars as each activity of the strategy was centered on them and contributed significantly to their growth and up-gradation, ensuring overall growth of KM in the department.

Keywords: knowledge, knowledge management, public sector organization, standardization, technology, people, skill, information system, innovation, competency, impact

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3728 Collision Avoidance Maneuvers for Vessels Navigating through Traffic Separation Scheme

Authors: Aswin V. J., Sreeja S., R. Harikumar

Abstract:

Ship collision is one of the major concerns while navigating in the ocean. In congested sea routes where there are hectic offshore operations, ships are often forced to take close encounter maneuvers. Maritime rules for preventing collision at sea are defined in the International Regulations for Preventing Collision at Sea. Traffic Separation Schemes (TSS) are traffic management route systems ruled by International Maritime Organization (IMO), where the traffic lanes indicate the general direction of traffic flow. The Rule 10 of International Regulations for Preventing Collision at Sea prescribes the conduct of vessels while navigating through TSS. But no quantitative criteria regarding the procedures to detect and evaluate collision risk is specified in International Regulations for Preventing Collision at Sea. Most of the accidents that occur are due to operational errors affected by human factors such as lack of experience and loss of situational awareness. In open waters, the traffic density is less when compared to that in TSS, and hence the vessels can be operated in autopilot mode. A collision avoidance method that uses the possible obstacle trajectories in advance to predict “collision occurrence” and can generate suitable maneuvers for collision avoidance is presented in this paper. The suitable course and propulsion changes that can be used in a TSS considering International Regulations for Preventing Collision at Sea are found out for various obstacle scenarios.

Keywords: collision avoidance, maneuvers, obstacle trajectories, traffic separation scheme

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3727 An Exploratory Analysis of Brisbane's Commuter Travel Patterns Using Smart Card Data

Authors: Ming Wei

Abstract:

Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

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3726 Wastewater Treatment by Floating Macrophytes (Salvinia natans) under Algerian Semi-Arid Climate

Authors: Laabassi Ayache, Boudehane Asma

Abstract:

Macrophyte pond has developed strongly in the field of wastewater treatment for irrigation in rural areas and small communities. Their association allows, in some cases, to increase the hydraulic capacity while maintaining the highest level of quality. The present work is devoted to the treatment of domestic wastewater under climatic conditions of Algeria (semi-arid) through a system using two tanks planted with Salvinia natans. The performance study and treatment efficiency of the system overall shows that the latter provides a significant removal of nitrogen pollution: total Kjeldahl nitrogen NTK (85.2%), Ammonium NH₄⁺-N (79%), Nitrite NO₂⁻-N (40%) also, a major meaningful reduction of biochemical oxygen demand BOD₅ was observed at the output of the system (96.9 %). As BOD₅, the chemical oxygen demand (COD) removal was higher than 95% at the exit of the two tanks. A moderately low yield of phosphate-phosphorus (PO₄³-P) was achieved with values not exceeding 37%. In general, the quality of treated effluent meets the Algerian standard of discharge and which allows us to select a suitable species in constructed wetland treatment systems under semi-arid climate.

Keywords: nutrient removal, Salvinia natans, semi-arid climate, wastewater treatment

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3725 Improving Machine Learning Translation of Hausa Using Named Entity Recognition

Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

Abstract:

Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

Procedia PDF Downloads 39
3724 Human Action Retrieval System Using Features Weight Updating Based Relevance Feedback Approach

Authors: Munaf Rashid

Abstract:

For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.

Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook

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3723 Congestion Mitigation on an Urban Arterial through Infrastructure Intervention

Authors: Attiq Ur Rahman Dogar, Sohaib Ishaq

Abstract:

Pakistan had experienced rapid motorization in the last decade. Due to the soft leasing schemes of banks and increase in average household income, even the middle class can now afford cars. The public transit system is inadequate and sparse. Due to these reasons, traffic demand on urban arterials has increased manifold. Poor urban transit planning and aging transportation systems have resulted in traffic congestion. The focus of this study is to improve traffic flow on a section of N-5 passing through the Rawalpindi downtown. Present efforts aim to carry out the analysis of traffic conditions on this section and to investigate the impact of traffic signal co-ordination on travel time. In addition to signal co-ordination, we also examined the effect of different infrastructure improvements on the travel time. After the economic analysis of alternatives and discussions, the improvement plan for Rawalpindi downtown urban arterial section is proposed for implementation.

Keywords: signal coordination, infrastructure intervention, infrastructure improvement, cycle length, fuel consumption cost, travel time cost, economic analysis, travel time, Rawalpindi, Pakistan, traffic signals

Procedia PDF Downloads 312