Search results for: geometric search algorithm
1391 Attendance Management System Implementation Using Face Recognition
Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru
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Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.Keywords: attendance system, face detection, face recognition, PCA
Procedia PDF Downloads 3541390 Exploring the Interplay of Attention, Awareness, and Control: A Comprehensive Investigation
Authors: Venkateswar Pujari
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This study tries to investigate the complex interplay between control, awareness, and attention in human cognitive processes. The fundamental elements of cognitive functioning that play a significant role in influencing perception, decision-making, and behavior are attention, awareness, and control. Understanding how they interact can help us better understand how our minds work and may even increase our understanding of cognitive science and its therapeutic applications. The study uses an empirical methodology to examine the relationships between attention, awareness, and control by integrating different experimental paradigms and neuropsychological tests. To ensure the generalizability of findings, a wide sample of participants is chosen, including people with various cognitive profiles and ages. The study is structured into four primary parts, each of which focuses on one component of how attention, awareness, and control interact: 1. Evaluation of Attentional Capacity and Selectivity: In this stage, participants complete established attention tests, including the Stroop task and visual search tasks. 2. Evaluation of Awareness Degrees: In the second stage, participants' degrees of conscious and unconscious awareness are assessed using perceptual awareness tasks such as masked priming and binocular rivalry tasks. 3. Investigation of Cognitive Control Mechanisms: In the third phase, reaction inhibition, cognitive flexibility, and working memory capacity are investigated using exercises like the Wisconsin Card Sorting Test and the Go/No-Go paradigm. 4. Results Integration and Analysis: Data from all phases are integrated and analyzed in the final phase. To investigate potential links and prediction correlations between attention, awareness, and control, correlational and regression analyses are carried out. The study's conclusions shed light on the intricate relationships that exist between control, awareness, and attention throughout cognitive function. The findings may have consequences for cognitive psychology, neuroscience, and clinical psychology by providing new understandings of cognitive dysfunctions linked to deficiencies in attention, awareness, and control systems.Keywords: attention, awareness, control, cognitive functioning, neuropsychological assessment
Procedia PDF Downloads 851389 Evaluation and Fault Classification for Healthcare Robot during Sit-To-Stand Performance through Center of Pressure
Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno
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Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement
Procedia PDF Downloads 1911388 Green Accounting and Firm Performance: A Bibliometric Literature Review
Authors: Francesca di Donato, Sara Trucco
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Green accounting is a growing topic of interest. Indeed, nowadays, most firms affect the environment; therefore, companies are seeking the best way to disclose environmental information. Furthermore, companies are increasingly committed to improving the environment, and the topic is gaining more importance to the public, governments, and policymakers. Green accounting is a type of accounting that considers environmental costs and their impact on the financial performance of firms. Thus, the motivation of the current research is to investigate the state-of-the-art literature on the relationship between green accounting and firm performance since the birth of the topic of green accounting and to investigate gaps in the literature that represent fruitful terrain for future research. In doing so, this study provides a bibliometric literature review of existing evidence related to the link between green accounting and firm performance since 2000. The search, based on the most relevant databases for scientific journals (which are Scopus, Emerald, Web of Science, Google Scholar, and Econlit), returned 1917 scientific articles. The articles were manually reviewed in order to identify only the relevant studies in the field by excluding articles with titles and abstracts out of scope. The final sample was composed of 107 articles. A content analysis was carried out on the final sample of articles; in doing so, a classification system has been proposed. Findings show the most relevant environmental costs and issues considered in previous studies and how green accounting may be linked to the financial and non-financial performance of a firm. The study also offers suggestions for future research in this domain. This study has several practical implications. Indeed, the topic of green accounting may be applied to different sectors and different types of companies. Therefore, this study may help managers to better understand the most relevant environmental information to disclose and how environmental issues may be managed to improve the performance of the firms. Moreover, the bibliometric literature review may be of interest to those stakeholders who are interested in the historical evolution of the topic.Keywords: bibliometric literature review, firm performance, green accounting, literature review
Procedia PDF Downloads 581387 Bayesian Using Markov Chain Monte Carlo and Lindley's Approximation Based on Type-I Censored Data
Authors: Al Omari Moahmmed Ahmed
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These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions.Keywords: weibull distribution, bayesian method, markov chain mote carlo, survival and hazard functions
Procedia PDF Downloads 4721386 Glucose Monitoring System Using Machine Learning Algorithms
Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe
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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning
Procedia PDF Downloads 1931385 The Determinants of Enterprise Risk Management: Literature Review, and Future Research
Authors: Sylvester S. Horvey, Jones Mensah
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The growing complexities and dynamics in the business environment have led to a new approach to risk management, known as enterprise risk management (ERM). ERM is a system and an approach to managing the risks of an organization in an integrated manner to achieve the corporate goals and strategic objectives. Regardless of the diversities in the business environment, ERM has become an essential factor in managing individual and business risks because ERM is believed to enhance shareholder value and firm growth. Despite the growing number of literature on ERM, the question about what factors drives ERM remains limited. This study provides a comprehensive literature review of the main factors that contribute to ERM implementation. Google Scholar was the leading search engine used to identify empirical literature, and the review spanned between 2000 and 2020. Articles published in Scimago journal ranking and Scopus were examined. Thirteen firm characteristics and sixteen articles were considered for the empirical review. Most empirical studies agreed that firm size, institutional ownership, industry type, auditor type, industrial diversification, earnings volatility, stock price volatility, and internal auditor had a positive relationship with ERM adoption, whereas firm size, institutional ownership, auditor type, and type of industry were mostly seen be statistically significant. Other factors such as financial leverage, profitability, asset opacity, international diversification, and firm complexity revealed an inconclusive result. The growing literature on ERM is not without limitations; hence, this study suggests that further research should examine ERM determinants within a new geographical context while considering a new and robust way of measuring ERM rather than relying on a simple proxy (dummy) for ERM measurement. Other firm characteristics such as organizational culture and context, corporate scandals and losses, and governance could be considered determinants of ERM adoption.Keywords: enterprise risk management, determinants, ERM adoption, literature review
Procedia PDF Downloads 1671384 Vibration-Based Data-Driven Model for Road Health Monitoring
Authors: Guru Prakash, Revanth Dugalam
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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.Keywords: SVM, data-driven, road health monitoring, pot-hole
Procedia PDF Downloads 801383 Investigating the Effectiveness of Multilingual NLP Models for Sentiment Analysis
Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar
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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.Keywords: NLP, multilingual, sentiment analysis, texts
Procedia PDF Downloads 891382 Design of Geochemical Maps of Industrial City Using Gradient Boosting and Geographic Information System
Authors: Ruslan Safarov, Zhanat Shomanova, Yuri Nossenko, Zhandos Mussayev, Ayana Baltabek
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Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed.Keywords: Pavlodar, geochemical map, gradient boosting, CatBoost, QGIS, spatial distribution, heavy metals
Procedia PDF Downloads 721381 Impact of Treatment of Fragility Fractures Due to Osteoporosis as an Economic Burden Worldwide: A Systematic Review
Authors: Fabiha Tanzeem
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BACKGROUND: Osteoporosis is a skeletal disease that is associated with a reduction in bone mass and microstructures of the bone and deterioration of bone tissue. Fragility fracture due to osteoporosis is the most significant complication of osteoporosis. The increasing prevalence of fragility fractures presents a growing burden on the global economy. There is a rapidly evolving need to improve awareness of the costs associated with these types of fractures and to review current policies and practices for the prevention and management of the disease. This systematic review will identify and describe the direct and indirect costs associated with osteoporotic fragility fractures from a global perspective from the included studies. The review will also find out whether the costs required for the treatment of fragility fractures due to osteoporosis impose an economic burden on the global healthcare system. METHODS: Four major databases were systematically searched for direct and indirect costs of osteoporotic fragility fracture studies in the English Language. PubMed, Cochrane Library, Embase and Google Scholar were searched for suitable articles published between 1990 and July 2020. RESULTS: The original search yielded 1166 papers; from these, 27 articles were selected for this review according to the inclusion and exclusion criteria. In the 27 studies, the highest direct costs were associated with the treatment of pelvic fractures, with the majority of the expenditure due to hospitalization and surgical treatments. It is also observed that most of the articles are from developed countries. CONCLUSION: This review indicates the significance of the economic burden of osteoporosis globally, although more research needs to be done in developing countries. In the treatment of fragility fractures, direct costs were the main reported expenditure in this review. The healthcare costs incurred globally can be significantly reduced by implementing measures to effectively prevent the disease. Raising awareness in children and adults by improving the quality of the information available and standardising policies and planning of services requires further research.Keywords: systematic review, osteoporosis, cost of illness
Procedia PDF Downloads 1621380 Analysis of Cycling Accessibility on Chengdu Tianfu Greenway Based on Improved Two-Step Floating Catchment Area Method: A Case Study of Jincheng Greenway
Authors: Qin Zhu
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Under the background of accelerating the construction of Beautiful and Livable Park City in Chengdu, the Tianfu greenway system, as an important support system for the construction of parks in the whole region, its accessibility is one of the key indicators to measure the effectiveness of the greenway construction. In recent years, cycling has become an important transportation mode for residents to go to the greenways because of its low-carbon, healthy and convenient characteristics, and the study of greenway accessibility under cycling mode can provide reference suggestions for the optimization and improvement of greenways. Taking Jincheng Greenway in Chengdu City as an example, the Baidu Map Application Programming Interface (API) and questionnaire survey was used to improve the two-step floating catchment area (2SFCA) method from the three dimensions of search threshold, supply side and demand side, to calculate the cycling accessibility of the greenway and to explore the spatial matching relationship with the population density, the number of entrances and the comprehensive attractiveness. The results show that: 1) the distribution of greenway accessibility in Jincheng shows a pattern of "high in the south and low in the north, high in the west and low in the east", 2) the spatial match between greenway accessibility and population density of the residential area is imbalanced, and there is a significant positive correlation between accessibility and the number of selectable greenway access points in residential areas, as well as the overall attractiveness of greenways, with a high degree of match. On this basis, it is proposed to give priority to the mismatch area to alleviate the contradiction between supply and demand, optimize the greenway access points to improve the traffic connection, enhance the comprehensive quality of the greenway and strengthen the service capacity, to further improve the cycling accessibility of the Jincheng Greenway and improve the spatial allocation of greenway resources.Keywords: accessibility, Baidu maps API, cycling, greenway, 2SFCA
Procedia PDF Downloads 711379 Occupational Health Programs for Artisanal and Small-Scale Gold Mining: A Systematic Review for the WHO Global Plan of Action for Workers' Health
Authors: Vivian W. L. Tsang, Karen Lockhart, Samuel Spiegel, Annalee Yassi
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Background: Workers in the informal economy often incur exposure to well-documented occupational health hazards. Insufficient attention has been afforded to rigorously evaluating intervention programs to reduce the risks, especially in artisanal and small-scale gold mining (ASGM). Objectives: This systematic review, conducted as part of the World Health Organization’s Global Plan of Action for Workers’ Health, sought to assess the state of knowledge on occupational health programs and interventions for the informal artisanal and small-scale gold mining (ASGM) sector, an occupation which directly employs at least 50 million people. Methods: We used a comprehensive search strategy for four well-known databases relevant to health outcomes: PubMed, Engineering Village, OVID Medline, and Web of Science, and employed the PRISMA framework for our analysis. Findings: Ten studies met the inclusion criteria of a primary study focused on assessing the impact of interventions addressing occupational health concerns in ASGM. There were no studies evaluating or even identifying comprehensive occupational health and safety programs for this sector, although target interventions addressing specific hazards exist. Major areas of intervention –education and introduction of mercury-reducing/eliminating technology were identified, and the challenges and limitations of each intervention taken into the assessment. Even for these, however, there was a lack of standardization for measuring outcome or impact, let alone long-term health outcomes for miners and mining communities. Conclusion: There is an urgent need for research on comprehensive occupational health programs addressing the array of hazards faced by artisanal and small-scale miners.Keywords: informal economy, artisanal and small-scale gold mining, occupational health, health and safety, workplace safety
Procedia PDF Downloads 1431378 The Co-Simulation Interface SystemC/Matlab Applied in JPEG and SDR Application
Authors: Walid Hassairi, Moncef Bousselmi, Mohamed Abid
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Functional verification is a major part of today’s system design task. Several approaches are available for verification on a high abstraction level, where designs are often modeled using MATLAB/Simulink. However, different approaches are a barrier to a unified verification flow. In this paper, we propose a co-simulation interface between SystemC and MATLAB and Simulink to enable functional verification of multi-abstraction levels designs. The resulting verification flow is tested on JPEG compression algorithm. The required synchronization of both simulation environments, as well as data type conversion is solved using the proposed co-simulation flow. We divided into two encoder jpeg parts. First implemented in SystemC which is the DCT is representing the HW part. Second, consisted of quantization and entropy encoding which is implemented in Matlab is the SW part. For communication and synchronization between these two parts we use S-Function and engine in Simulink matlab. With this research premise, this study introduces a new implementation of a Hardware SystemC of DCT. We compare the result of our simulation compared to SW / SW. We observe a reduction in simulation time you have 88.15% in JPEG and the design efficiency of the supply design is 90% in SDR.Keywords: hardware/software, co-design, co-simulation, systemc, matlab, s-function, communication, synchronization
Procedia PDF Downloads 3911377 IoT Continuous Monitoring Biochemical Oxygen Demand Wastewater Effluent Quality: Machine Learning Algorithms
Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli
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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning
Procedia PDF Downloads 691376 Impact of PV Distributed Generation on Loop Distribution Network at Saudi Electricity Company Substation in Riyadh City
Authors: Mohammed Alruwaili
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Nowadays, renewable energy resources are playing an important role in replacing traditional energy resources such as fossil fuels by integrating solar energy with conventional energy. Concerns about the environment led to an intensive search for a renewable energy source. The Rapid growth of distributed energy resources will have prompted increasing interest in the integrated distributing network in the Kingdom of Saudi Arabia next few years, especially after the adoption of new laws and regulations in this regard. Photovoltaic energy is one of the promising renewable energy sources that has grown rapidly worldwide in the past few years and can be used to produce electrical energy through the photovoltaic process. The main objective of the research is to study the impact of PV in distribution networks based on real data and details. In this research, site survey and computer simulation will be dealt with using the well-known computer program software ETAB to simulate the input of electrical distribution lines with other variable inputs such as the levels of solar radiation and the field study that represent the prevailing conditions and conditions in Diriah, Riyadh region, Saudi Arabia. In addition, the impact of adding distributed generation units (DGs) to the distribution network, including solar photovoltaic (PV), will be studied and assessed for the impact of adding different power capacities. The result has been achieved with less power loss in the loop distribution network from the current condition by more than 69% increase in network power loss. However, the studied network contains 78 buses. It is hoped from this research that the efficiency, performance, quality and reliability by having an enhancement in power loss and voltage profile of the distribution networks in Riyadh City. Simulation results prove that the applied method can illustrate the positive impact of PV in loop distribution generation.Keywords: renewable energy, smart grid, efficiency, distribution network
Procedia PDF Downloads 1341375 New Approach for Minimizing Wavelength Fragmentation in Wavelength-Routed WDM Networks
Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun
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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic
Procedia PDF Downloads 5171374 Analysis of Three-Dimensional Longitudinal Rolls Induced by Double Diffusive Poiseuille-Rayleigh-Benard Flows in Rectangular Channels
Authors: O. Rahli, N. Mimouni, R. Bennacer, K. Bouhadef
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This numerical study investigates the travelling wave’s appearance and the behavior of Poiseuille-Rayleigh-Benard (PRB) flow induced in 3D thermosolutale mixed convection (TSMC) in horizontal rectangular channels. The governing equations are discretized by using a control volume method with third order Quick scheme in approximating the advection terms. Simpler algorithm is used to handle coupling between the momentum and continuity equations. To avoid the excessively high computer time, full approximation storage (FAS) with full multigrid (FMG) method is used to solve the problem. For a broad range of dimensionless controlling parameters, the contribution of this work is to analyzing the flow regimes of the steady longitudinal thermoconvective rolls (noted R//) for both thermal and mass transfer (TSMC). The transition from the opposed volume forces to cooperating ones, considerably affects the birth and the development of the longitudinal rolls. The heat and mass transfers distribution are also examined.Keywords: heat and mass transfer, mixed convection, poiseuille-rayleigh-benard flow, rectangular duct
Procedia PDF Downloads 2931373 Machine Learning for Exoplanetary Habitability Assessment
Authors: King Kumire, Amos Kubeka
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The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.Keywords: machine-learning, habitability, exoplanets, supercomputing
Procedia PDF Downloads 831372 Machine Learning for Exoplanetary Habitability Assessment
Authors: King Kumire, Amos Kubeka
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The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far, has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.Keywords: exoplanets, habitability, machine-learning, supercomputing
Procedia PDF Downloads 1071371 A Brave New World of Privacy: Empirical Insights into the Metaverse’s Personalization Dynamics
Authors: Cheng Xu
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As the metaverse emerges as a dynamic virtual simulacrum of reality, its implications on user privacy have become a focal point of interest. While previous discussions have ventured into metaverse privacy dynamics, a glaring empirical gap persists, especially concerning the effects of personalization in the context of news recommendation services. This study stands at the forefront of addressing this void, meticulously examining how users' privacy concerns shift within the metaverse's personalization context. Through a pre-registered randomized controlled experiment, participants engaged in a personalization task across both the metaverse and traditional online platforms. Upon completion of this task, a comprehensive news recommendation service provider offers personalized news recommendations to the users. Our empirical findings reveal that the metaverse inherently amplifies privacy concerns compared to traditional settings. However, these concerns are notably mitigated when users have a say in shaping the algorithms that drive these recommendations. This pioneering research not only fills a significant knowledge gap but also offers crucial insights for metaverse developers and policymakers, emphasizing the nuanced role of user input in shaping algorithm-driven privacy perceptions.Keywords: metaverse, privacy concerns, personalization, digital interaction, algorithmic recommendations
Procedia PDF Downloads 1071370 A Particle Swarm Optimal Control Method for DC Motor by Considering Energy Consumption
Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu
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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control
Procedia PDF Downloads 1491369 The Predictability of Three Implants to Support a Fixed Prosthesis in the Edentulous Mandible
Authors: M. Hirani, M. Devine, O. Obisesan, C. Bryant
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Introduction: The use of four or more implants to support a fixed prosthesis in the edentulous mandible is well documented, with high levels of clinical outcomes recorded. Despite this, the use of three implant-supported fixed prostheses offers the potential to deliver a more cost-effective method of oral rehabilitation in the lower arch, an important consideration given that edentulism is most prevalent in low-income subpopulations. The purpose of this study aimed to evaluate the implant and prosthetic survival rate, changes in marginal bone level, and patient satisfaction associated with a three-implant-supported fixed prosthesis for rehabilitation of the edentulous mandible over a follow-up period of at least one year. Methods: A comprehensive literature search was performed to evaluate studies that met the selection criteria. The information extracted included the study design and population, participant demographics, observation period, loading protocol, and the number of implants placed together with the required outcome measures. Mean values and standard deviations (SD) were calculated using SPSS® (IBM Corporation, New York, USA), and the level of statistical significance across all comparative studies described was set at P < 0.05. Results: The eligible studies included a total of 1968 implants that were placed in 652 patients. The subjects ranged in age from 33-89 years, with a mean of 63.2 years. The mean cumulative implant and prosthetic survival rates were 95.5% and 96.2%, respectively, over a mean follow-up period of 3.25 years. The mean marginal bone loss recorded was 1.04 mm, and high patient satisfaction rates were reported across the studies. Conclusion: Current evidence suggests that a three implant-supported fixed prosthesis for the edentulous mandible is a successful treatment strategy presenting high implant and prosthetic survival rates over the short-to-medium term. Further well-designed controlled clinical trials are required to evaluate longer-term outcomes, with supplemental data correlating implant dimensions and prosthetic design.Keywords: implants, mandible, fixed, prosthesis
Procedia PDF Downloads 1271368 Study Skills Empowering Strategies to Enhance Second Year Diploma Accountancy Students’ Academic Performance
Authors: Mohamed Karodia
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Accountancy as a subject is one of the sciences that for many years has been perceived as a difficult subject to study and teach. Yet, it continuously attracts scholars graduating from school and entering Higher Education Institutions as a subject of choice and career. The teaching and learning of this subject have not been easy and has evolved and progressed over the past few decades however students still find it difficult to study and this has resulted in poor student achievement. In search of solutions, this study has considered the effect and efficacy that study skills have on the performance of Accountancy students and in particular students studying Second Year Diploma in Accountancy at the University of Johannesburg. These students appear to have a lack of appropriate study skills and as a result of these impacts on their performance in the courses, they are studying. This study also focuses on strategies to enhance Second Year Diploma Accountancy students’ academic performance. A literature review was conducted to investigate what scholarly literature suggests about study skills, in general, and in particular for Accountancy to be successful. In order to determine what study skills Second Year Accountancy students are applying when they learn and why they are failing the Accountancy examinations and formal class tests, the study adopted the quantitative research method. A questionnaire addressing various aspects of study skills, studying accountancy and studying, in general, was provided to 800 students studying Second Year Diploma in Accountancy at the University of Johannesburg’s Soweto Campus. The quantitative data collected were analyzed using descriptive statistics in the form of proportions, frequencies, means, and standard deviations, t-tests to compare differences between two groups as well as correlations between variables. Based on the findings of this study, it is recommended that students are provided with courses in time management, procrastination, reading, note taking and writing, test preparation techniques as well as study attitude. Lecturers spend more time teaching students how to study in general as well as accountancy specifically preferably at the first-year level before proceeding to the second year. It is also recommended that the University implements a study skills course to assist the students with studying.Keywords: accountancy, skills, strategies, study
Procedia PDF Downloads 1271367 Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study
Authors: Si Mon Kueh, Tom J. Kazmierski
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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)
Procedia PDF Downloads 3151366 Mycophenolate Versus Methotrexate in Non-Infectious Ocular Inflammatory Disease: A Systematic Review and Meta-Analysis
Authors: Mohammad Karam, Abdulmalik Alsaif, Abdulrahman Al-Naseem, Amrit Hayre, Abdurrahman Al Jabbouri, Ahmad Aldubaikhi, Narvair Kahlar, Salem Al-Mutairi
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Purpose: To compare the outcomes of mycophenolate mofetil (MMF) versus methotrexate (MTX) in non-infectious ocular inflammatory disease (NIOID). Methods: A systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Guidelines and an electronic search was conducted to identify all comparative studies of MMF versus MTX in NIOID. Treatment results and side effects were primary outcome measures. Secondary outcome measures included visual acuity and resolution of macular oedema. Fixed and random-effects models were used for the analysis. Results: Four studies enrolling 905 patients were identified. There was no significant difference between MMF and MTX groups in overall treatment success (Odds Ratio [OR] = 0.97, P = 0.96) and failure (OR = 0.86, P = 0.85) of NIOID. Although treatment success of uveitis showed no significant difference for anterior and intermediate uveitis cases (OR = 2.33, P = 0.14), MTX showed a significantly improved effect in cases involving posterior uveitis and panuveitis (OR = 0.41, P = 0.003). However, the median dose required for treatment success was lower for MTX whereas MMF was associated with a faster median time to treatment success. Further to this, MMF showed a reduced rate of side effects when compared to MTX, but MTX failed to reach statistical significance, most notably for liver enzyme elevation (OR = 0.65, P = 0.16), fatigue (OR = 0.84, P = 0.49) and headache (OR = 0.81, P = 0.37). For secondary outcomes, no significant difference was noted in visual acuity and resolution of macular edema. Conclusions: MMF is comparable to MTX in the treatment of NIOID as there was no significant difference in the outcome of treatment success and side effect profiles.Keywords: Mycophenolate mofetil, methotrexate, non-infectious ocular inflammation, uveitis, scleritis
Procedia PDF Downloads 1481365 An Inverse Heat Transfer Algorithm for Predicting the Thermal Properties of Tumors during Cryosurgery
Authors: Mohamed Hafid, Marcel Lacroix
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This study aimed at developing an inverse heat transfer approach for predicting the time-varying freezing front and the temperature distribution of tumors during cryosurgery. Using a temperature probe pressed against the layer of tumor, the inverse approach is able to predict simultaneously the metabolic heat generation and the blood perfusion rate of the tumor. Once these parameters are predicted, the temperature-field and time-varying freezing fronts are determined with the direct model. The direct model rests on one-dimensional Pennes bioheat equation. The phase change problem is handled with the enthalpy method. The Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM) is used to solve the inverse model. The effect (a) of the thermal properties of the diseased tissues; (b) of the initial guesses for the unknown thermal properties; (c) of the data capture frequency; and (d) of the noise on the recorded temperatures is examined. It is shown that the proposed inverse approach remains accurate for all the cases investigated.Keywords: cryosurgery, inverse heat transfer, Levenberg-Marquardt method, thermal properties, Pennes model, enthalpy method
Procedia PDF Downloads 1931364 Antimicrobial, Antioxidant and Cytotoxic Activities of Cleoma viscosa Linn. Crude Extracts
Authors: Suttijit Sriwatcharakul
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The bioactivity studies from the weed ethanolic crude extracts from leaf, stem, pod and root of wild spider flower; Cleoma viscosa Linn. were analyzed for the growth inhibition of 6 bacterial species; Salmonella typhimurium TISTR 5562, Pseudomonas aeruginosa ATCC 27853, Staphylococcus aureus TISTR 1466, Streptococcus epidermidis ATCC 1228, Escherichia coli DMST 4212 and Bacillus subtilis ATCC 6633 with initial concentration crude extract of 50 mg/ml. The agar well diffusion results found that the extracts inhibit only gram positive bacteria species; S. aureus, S. epidermidis and B. subtilis. The minimum inhibition concentration study with gram positive strains revealed that leaf crude extract give the best result of the lowest concentration compared with other plant parts to inhibit the growth of S. aureus, S. epidermidis and B. subtilis at 0.78, 0.39 and lower than 0.39 mg/ml, respectively. The determination of total phenolic compounds in the crude extracts exhibited the highest phenolic content was 10.41 mg GAE/g dry weight in leaf crude extract. Analyzed the efficacy of free radical scavenging by using DPPH radical scavenging assay with all crude extracts showed value of IC50 of leaf, stem, pod and root crude extracts were 8.32, 12.26, 21.62 and 35.99 mg/ml, respectively. Studied cytotoxicity of crude extracts on human breast adenocarcinoma cell line by MTT assay found that pod extract had the most cytotoxicity CC50 value, 32.41 µg/ml. Antioxidant activity and cytotoxicity of crude extracts exhibited that the more increase of extract concentration, the more activities indicated. According to the bioactivities results, the leaf crude extract of Cleoma viscosa Linn. is the most interesting plant part for further work to search the beneficial of this weed.Keywords: antimicrobial, antioxidant activity, Cleoma viscosa Linn., cytotoxicity test, total phenolic compound
Procedia PDF Downloads 2651363 Non-Invasive Imaging of Tissue Using Near Infrared Radiations
Authors: Ashwani Kumar Aggarwal
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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering
Procedia PDF Downloads 3091362 Nutritional Characteristics, Phytochemical and Antimicrobial Potential of Leaf Protein Concentrates from Huckleberry
Authors: Sodamade Abiodun, Adeboye Olubunmi Omolara
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Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that can serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of Huckleberry was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education campus, Oyo. The sample was authenticated at the forestry research institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition; mineral analysis phytochemical and antimicrobial properties of the leaf protein concentrates were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive results of the mineral analysis showed that the sample contains Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g while cadmium was not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, steroid, Terpenoid, cordial glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Huckleberry leaf protein concentrates showed that it contains bioactive compounds that are capable of eradicating some tested microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisidlae pneumonia and Proteus merabilis. The results of the analysis of leaf protein concentrates of Huckleberry showed that the sample contains high nutrient and mineral constituents and phytochemical compounds that could make the sample useful for medicinal activities.Keywords: huckleberry, mentha piperita, phytochemical, leaf protein concentrates, nutritional characteristics
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