Search results for: algorithm techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9590

Search results for: algorithm techniques

4700 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

Procedia PDF Downloads 121
4699 Study of Gait Stability Evaluation Technique Based on Linear Inverted Pendulum Model

Authors: Kang Sungjae

Abstract:

This research proposes a gait stability evaluation technique based on the linear inverted pendulum model and moving support foot Zero Moment Point. With this, an improvement towards the gait analysis of the orthosis walk is validated. The application of Lagrangian mechanics approximation to the solutions of the dynamics equations for the linear inverted pendulum does not only simplify the solution, but it provides a smooth Zero Moment Point for the double feet support phase. The Zero Moment Point gait analysis techniques mentioned above validates reference trajectories for the center of mass of the gait orthosis, the timing of the steps and landing position references for the swing feet. The stability evaluation technique are tested with a 6 DOF powered gait orthosis. The results obtained are promising for implementations.

Keywords: locomotion, center of mass, gait stability, linear inverted pendulum model

Procedia PDF Downloads 503
4698 Quantifying Expressive Meaning: Composing Expressive Vectors Using Linguistic Theory, Word Embeddings, and Native Speaker Surveys

Authors: Saughmon Boujkian

Abstract:

This study delves into the intricate interplay between semantics and emotional connotation in linguistic expression, focusing on the role of expressive adjectives (EAs). Through a blend of theoretical frameworks from linguistics and computational techniques from natural language processing, native speakers' judgments are curated to capture the nuanced interpretations elicited by EAs in diverse linguistic contexts. Leveraging mathematical tools like least squares analysis, the study translates qualitative linguistic phenomena into quantitative measures, unveiling the differential impact of EAs on sentence sentiment. The derived expressive vectors offer insights into the nature of expressive meaning, underscoring the complex dynamics inherent in linguistic expression. While the study's outcomes provide valuable insights, future research endeavors could explore more sophisticated linguistic models to enhance the accuracy and granularity of expressive vector representations.

Keywords: vectors, expressive meaning, multi-dimentionality, least squares regression

Procedia PDF Downloads 8
4697 Measuring Banking Risk

Authors: Mike Tsionas

Abstract:

The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

Procedia PDF Downloads 334
4696 A Portable Cognitive Tool for Engagement Level and Activity Identification

Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

Abstract:

Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

Procedia PDF Downloads 66
4695 Electromagnetic Modeling of a MESFET Transistor Using the Moments Method Combined with Generalised Equivalent Circuit Method

Authors: Takoua Soltani, Imen Soltani, Taoufik Aguili

Abstract:

The communications' and radar systems' demands give rise to new developments in the domain of active integrated antennas (AIA) and arrays. The main advantages of AIA arrays are the simplicity of fabrication, low cost of manufacturing, and the combination between free space power and the scanner without a phase shifter. The integrated active antenna modeling is the coupling between the electromagnetic model and the transport model that will be affected in the high frequencies. Global modeling of active circuits is important for simulating EM coupling, interaction between active devices and the EM waves, and the effects of EM radiation on active and passive components. The current review focuses on the modeling of the active element which is a MESFET transistor immersed in a rectangular waveguide. The proposed EM analysis is based on the Method of Moments combined with the Generalised Equivalent Circuit method (MOM-GEC). The Method of Moments which is the most common and powerful software as numerical techniques have been used in resolving the electromagnetic problems. In the class of numerical techniques, MOM is the dominant technique in solving of Maxwell and Transport’s integral equations for an active integrated antenna. In this situation, the equivalent circuit is introduced to the development of an integral method formulation based on the transposition of field problems in a Generalised equivalent circuit that is simpler to treat. The method of Generalised Equivalent Circuit (MGEC) was suggested in order to represent integral equations circuits that describe the unknown electromagnetic boundary conditions. The equivalent circuit presents a true electric image of the studied structures for describing the discontinuity and its environment. The aim of our developed method is to investigate the antenna parameters such as the input impedance and the current density distribution and the electric field distribution. In this work, we propose a global EM modeling of the MESFET AsGa transistor using an integral method. We will begin by describing the modeling structure that allows defining an equivalent EM scheme translating the electromagnetic equations considered. Secondly, the projection of these equations on common-type test functions leads to a linear matrix equation where the unknown variable represents the amplitudes of the current density. Solving this equation resulted in providing the input impedance, the distribution of the current density and the electric field distribution. From electromagnetic calculations, we were able to present the convergence of input impedance for different test function number as a function of the guide mode numbers. This paper presents a pilot study to find the answer to map out the variation of the existing current evaluated by the MOM-GEC. The essential improvement of our method is reducing computing time and memory requirements in order to provide a sufficient global model of the MESFET transistor.

Keywords: active integrated antenna, current density, input impedance, MESFET transistor, MOM-GEC method

Procedia PDF Downloads 183
4694 Efficient Fake News Detection Using Machine Learning and Deep Learning Approaches

Authors: Chaima Babi, Said Gadri

Abstract:

The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

Procedia PDF Downloads 68
4693 Power of Sales and Marketing in Electronics Engineering with E-commerce: Connecting the Circuits

Authors: Muhammad Awais Kiani, Maryam Kiani

Abstract:

In today's digital age, the field of electronics engineering is experiencing unprecedented growth and innovation. To keep pace with this rapidly evolving industry, effective sales and marketing strategies are crucial, especially when combined with the power of e-commerce. This study explores the significance of integrating sales and marketing techniques with e-commerce platforms in the context of electronics engineering. It highlights the benefits, challenges, and best practices in leveraging e-commerce for sales and marketing in this industry. By embracing e-commerce, electronics engineering companies can reach a wider customer base, enhance brand visibility, and personalize customer experiences. Furthermore, this abstract delves into the importance of utilizing digital marketing tools such as search engine optimization (SEO), social media marketing, and content creation to optimize online sales. Therefore, this research aims to provide insights and recommendations for electronics engineering professionals to effectively navigate the dynamic landscape of sales and marketing in conjunction with e-commerce.

Keywords: electronics engineering, marketing, sales, E-commerce

Procedia PDF Downloads 62
4692 A Lifetime-Enhancing Monitoring Node Distribution Using Minimum Spanning Tree in Mobile Ad Hoc Networks

Authors: Sungchul Ha, Hyunwoo Kim

Abstract:

In mobile ad hoc networks, all nodes in a network only have limited resources and calculation ability. Therefore communication topology which have long lifetime is good for all nodes in mobile ad hoc networks. There are a variety of researches on security problems in wireless ad hoc networks. The existing many researches try to make efficient security schemes to reduce network power consumption and enhance network lifetime. Because a new node can join the network at any time, the wireless ad hoc networks are exposed to various threats and can be destroyed by attacks. Resource consumption is absolutely necessary to secure networks, but more resource consumption can be a critical problem to network lifetime. This paper focuses on efficient monitoring node distribution to enhance network lifetime in wireless ad hoc networks. Since the wireless ad hoc networks cannot use centralized infrastructure and security systems of wired networks, a new special IDS scheme is necessary. The scheme should not only cover all nodes in a network but also enhance the network lifetime. In this paper, we propose an efficient IDS node distribution scheme using minimum spanning tree (MST) method. The simulation results show that the proposed algorithm has superior performance in comparison with existing algorithms.

Keywords: MANETs, IDS, power control, minimum spanning tree

Procedia PDF Downloads 351
4691 Analysis and Detection of Facial Expressions in Autism Spectrum Disorder People Using Machine Learning

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

Abstract:

Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

Procedia PDF Downloads 157
4690 Revising Our Ideas on Revisions: Non-Contact Bridging Plate Fixation of Vancouver B1 and B2 Periprosthetic Femoral Fractures

Authors: S. Ayeko, J. Milton, C. Hughes, K. Anderson, R. G. Middleton

Abstract:

Background: Periprosthetic femoral fractures (PFF) in association with hip hemiarthroplasty or total hip arthroplasty is a common and serious complication. In the Vancouver Classification system algorithm, B1 fractures should be treated with Open Reduction and Internal Fixation (ORIF) and preferentially revised in combination with ORIF if B2 or B3. This study aims to assess patient outcomes after plate osteosynthesis alone for Vancouver B1 and B2 fractures. The main outcome is the 1-year re-revision rate, and secondary outcomes are 30-day and 1-year mortality. Method: This is a retrospective single-centre case-series review from January 2016 to June 2021. Vancouver B1 and B2, non-malignancy fractures in adults over 18 years of age treated with polyaxial Non-Contact Bridging plate osteosynthesis, have been included. Outcomes were gathered from electronic notes and radiographs. Results: There were 50 B1 and 64 B2 fractures. 26 B2 fractures were managed with ORIF and revision, 39 ORIF alone. Of the revision group, one died within 30 days (3.8%), one at one year (3.8%), and two were revised within one year (7.7). Of the B2 ORIF group, three died within 30-day mortality (7.96%), eight at one year (21.1%), and 0 were revised in 1 year. Conclusion: This study has demonstrated that satisfactory outcomes can be achieved with ORIF, excluding revision in the management of B2 fractures.

Keywords: arthroplasty, bridging plate, periprosthetic fracture, revision surgery

Procedia PDF Downloads 91
4689 Interactive Learning Practices for Class Room Teaching

Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni

Abstract:

This paper presents details of teaching and learning pedagogical techniques attempted for the undergraduate engineering program to improve the concentration span of students in a classroom. The details of activities such as valid statement, quiz competition, classroom paper, group work and product marketing to make the students remain active for the entire class duration and to improve presentation skills are presented. These activities shown tremendous improvement in student’s performance in academics, also in asking questions, concept understanding and interaction with the course instructor. With these pedagogical activities we are able to achieve Program outcome elements and ABET Program outcomes such as d, i, g and h which are difficult to achieve through the conventional teaching methods.

Keywords: activities, pedagogy, interactive learning, valid statement, quiz competition, classroom papers, group work, product marketing

Procedia PDF Downloads 633
4688 A Multi-Objective Optimization Tool for Dual-Mode Operating Active Magnetic Regenerator Model

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

Abstract:

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

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

Procedia PDF Downloads 98
4687 Combining Chiller and Variable Frequency Drives

Authors: Nasir Khalid, S. Thirumalaichelvam

Abstract:

In most buildings, according to US Department of Energy Data Book, the electrical consumption attributable to centralized heating and ventilation of air- condition (HVAC) component can be as high as 40-60% of the total electricity consumption for an entire building. To provide efficient energy management for the market today, researchers are finding new ways to develop a system that can save electrical consumption of buildings even more. In this concept paper, a system known as Intelligent Chiller Energy Efficiency (iCEE) System is being developed that is capable of saving up to 25% from the chiller’s existing electrical energy consumption. In variable frequency drives (VFDs), research has found significant savings up to 30% of electrical energy consumption. Together with the VFDs at specific Air Handling Unit (AHU) of HVAC component, this system will save even more electrical energy consumption. The iCEE System is compatible with any make, model or age of centrifugal, rotary or reciprocating chiller air-conditioning systems which are electrically driven. The iCEE system uses engineering principles of efficiency analysis, enthalpy analysis, heat transfer, mathematical prediction, modified genetic algorithm, psychometrics analysis, and optimization formulation to achieve true and tangible energy savings for consumers.

Keywords: variable frequency drives, adjustable speed drives, ac drives, chiller energy system

Procedia PDF Downloads 544
4686 Experiment of Geophysical Exploration in Egypt

Authors: Ramadan Fayez Zowaid Hussein

Abstract:

Exploration geophysics is an applied branch of geophysics, and it is very important to use such a method in Egypt and not just Egypt but in Africa and the Middle East. This research aims to work deeply on the importance of this method, and this paper focuses more on the benefits of the exploration of geophysics and how to apply it to scientific methods. It helps to discover earthquakes and assist in seismology. It also helps to map the surface structure of a region and also magnetic techniques, including aeromagnetic surveys to map magnetic anomalies. This is known that having a great experience in this field as it was very interesting reading a lot and searching about this matter and this technology, and all was found made this fantastic: as the method is existing and we do not use it. It costs a lot, but one believes that this method is very important; for example, in discovering earthquakes, check the surface of the ground easily; it makes us see the surface of the ground clearly so we can find the elements of the earth easily. In conclusion, geophysical exploration use is very important, and it must be highlighted and considered to be discussed in the Middle East, not just in the Middle East but also in Africa.

Keywords: geophysics, magnetic, gravitational, hydrocarbon exploration

Procedia PDF Downloads 63
4685 Testing the Change in Correlation Structure across Markets: High-Dimensional Data

Authors: Malay Bhattacharyya, Saparya Suresh

Abstract:

The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

Procedia PDF Downloads 110
4684 Optimizing Human Diet Problem Using Linear Programming Approach: A Case Study

Authors: P. Priyanka, S. Shruthi, N. Guruprasad

Abstract:

Health is a common theme in most cultures. In fact all communities have their concepts of health, as part of their culture. Health continues to be a neglected entity. Planning of Human diet should be done very careful by selecting the food items or groups of food items also the composition involved. Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Linear programming techniques have been extensively used for human diet formulation for quiet good number of years. Through the process, we mainly apply “The Simplex Method” which is a very useful statistical tool based on the theorem of Elementary Row Operation from Linear Algebra and also incorporate some other necessary rules set by the Simplex Method to help solve the problem. The study done by us is an attempt to develop a programming model for optimal planning and best use of nutrient ingredients.

Keywords: diet formulation, linear programming, nutrient ingredients, optimization, simplex method

Procedia PDF Downloads 544
4683 Performance Evaluation of Routing Protocols for Video Conference over MPLS VPN Network

Authors: Abdullah Al Mamun, Tarek R. Sheltami

Abstract:

Video conferencing is a highly demanding facility now a days in order to its real time characteristics, but faster communication is the prior requirement of this technology. Multi Protocol Label Switching (MPLS) IP Virtual Private Network (VPN) address this problem and it is able to make a communication faster than others techniques. However, this paper studies the performance comparison of video traffic between two routing protocols namely the Enhanced Interior Gateway Protocol(EIGRP) and Open Shortest Path First (OSPF). The combination of traditional routing and MPLS improve the forwarding mechanism, scalability and overall network performance. We will use GNS3 and OPNET Modeler 14.5 to simulate many different scenarios and metrics such as delay, jitter and mean opinion score (MOS) value are measured. The simulation result will show that OSPF and BGP-MPLS VPN offers best performance for video conferencing application.

Keywords: OSPF, BGP, EIGRP, MPLS, Video conference, Provider router, edge router, layer3 VPN

Procedia PDF Downloads 323
4682 Adopting Flocks of Birds Approach to Predator for Anomalies Detection on Industrial Control Systems

Authors: M. Okeke, A. Blyth

Abstract:

Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

Procedia PDF Downloads 286
4681 Effect of Rainflow Cycle Number on Fatigue Lifetime of an Arm of Vehicle Suspension System

Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

Abstract:

Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

Procedia PDF Downloads 243
4680 Precision Assessment of the Orthometric Heights Determination in the Northern Part of Libya

Authors: Jamal A. Gledan, Akrm H. Algnin

Abstract:

The Global Positioning System (GPS) satellite-based technology has been utilized extensively in the last few years in a wide range of Geomatics and Geographic Information Systems (GIS) applications. One of the main challenges dealing with GPS-based heights consists of converting them into Mean Sea Level (MSL) heights which is used in surveys and mapping. In this research work, differences in heights of 50 points, in northern part of Libya were carried out using both ordinary levelling (in which Geoid is the reference datum) and GPS techniques (in which Ellipsoid is the reference datum). In addition, this study has utilized the EGM2008 model to obtain the undulation values between the ellipsoidal and orthometric heights. From these values with ellipsoidal heights which can be obtained from GPS observations to compute the orthomteric heights. This research presented a suitable alternative, from an economical point of view, to substitute the expensive traditional levelling technique particularly for topographic mapping.

Keywords: geoid undulation, GPS, ordinary and geodetic levelling, orthometric height

Procedia PDF Downloads 423
4679 A Turn-on Fluorescent Sensor for Pb(II)

Authors: Ece Kök Yetimoğlu, Soner Çubuk, Neşe Taşci, M. Vezir Kahraman

Abstract:

Lead(II) is one of the most toxic environmental pollutants in the world, due to its high toxicity and non-biodegradability. Lead exposure causes severe risks to human health such as central brain damages, convulsions, kidney damages, and even death. To determine lead(II) in environmental or biological samples, scientists use atomic absorption spectrometry (AAS), inductively coupled plasma mass spectrometry (ICPMS), fluorescence spectrometry and electrochemical techniques. Among these systems the fluorescence spectrometry and fluorescent chemical sensors have attracted considerable attention because of their good selectivity and high sensitivity. The fluorescent polymers usually contain covalently bonded fluorophores. In this study imidazole based UV cured polymeric film was prepared and designed to act as a fluorescence chemo sensor for lead (II) analysis. The optimum conditions such as influence of pH value and time on the fluorescence intensity of the sensor have also been investigated. The sensor was highly sensitive with a detection limit as low as 1.87 × 10−8 mol L-1 and it was successful in the determination of Pb(II) in water samples.

Keywords: fluorescence, lead(II), photopolymerization, polymeric sensor

Procedia PDF Downloads 658
4678 Parameters Influencing the Output Precision of a Lens-Lens Beam Generator Solar Concentrator

Authors: M. Tawfik, X. Tonnellier, C. Sansom

Abstract:

The Lens-Lens Beam Generator (LLBG) is a Fresnel-based optical concentrating technique which provides flexibility in selecting the solar receiver location compared to conventional techniques through generating a powerful concentrated collimated solar beam. In order to achieve that, two successive lenses are used and followed by a flat mirror. Hence the generated beam emerging from the LLBG has a high power flux which impinges on the target receiver, it is important to determine the precision of the system output. In this present work, mathematical investigation of different parameters affecting the precision of the output beam is carried out. These parameters include: Deflection in sun-facing lens and its holding arm, delay in updating the solar tracking system, and the flat mirror surface flatness. Moreover, relationships that describe the power lost due to the effect of each parameter are derived in this study.

Keywords: Fresnel lens, LLBG, solar concentrator, solar tracking

Procedia PDF Downloads 201
4677 Assessment of Sleeping Patterns of Saudis with Type 2 Diabetes Mellitus in Ramadan and Non-Ramadan Periods Using a Wearable Device and a Questionnaire

Authors: Abdullah S. Alghamdi, Khaled Alghamdi, Richard O. Jenkins, Parvez I. Haris

Abstract:

Background: Quantity and quality of sleep have been reported to be significant risk factors for obesity and development of metabolic disorders such as type 2 diabetes mellitus (T2DM). The relationship between diabetes and sleep quantity was reported to be U-shaped, which means increased or decreased sleeping hours can increase the risk of diabetes. The plasma glucagon levels were found to continuously decrease during night-time sleep in healthy individuals, independently of blood glucose and insulin levels. The disturbance of the circadian rhythm is also important and has been linked with an increased the chance of diabetes incidence. There is a lack of research on sleep patterns on Saudis with T2DM and how this is affected by Ramadan fasting. Aim: To assess the sleeping patterns of Saudis with T2DM (before, during, and after Ramadan), using two different techniques and relate this to their HbA1c levels. Method: This study recruited 82 Saudi with T2DM, who chose to fast during Ramadan, from the Endocrine and Diabetic Centre of Al Iman General Hospital, Riyadh, Saudi Arabia. Ethical approvals for the study were obtained from De Montfort University and Saudi Ministry of Health. Their sleeping patterns were assessed by a self-administered questionnaire (before, during, and after Ramadan). The assessment included the daily total sleeping hours (DTSH), and total night-time sleeping hours (TNTSH) of the participants. In addition, sleeping patterns of 36 patients, randomly selected from the 82 participants, were further tracked during and after Ramadan by using Fitbit Flex 2™ accelerometer. Blood samples were collected in each period for measuring HbA1c. Results: Questionnaire analysis revealed that the sleeping patterns significantly changed between the periods, with shorter hours during Ramadan (P < 0.001 for DTSH, and P < 0.001 for TNTSH). These findings were confirmed by the Fitbit data, which also indicated significant shorter sleeping hours for the DTSH, and the TNTSH during Ramadan (P < 0.001 and P < 0.001, respectively). Although there were no significant correlations between the questionnaire and Fitbit data, the TNTSH were shorter among the participants in all periods by both techniques. The mean HbA1c significantly varied between periods, with lowest level during Ramadan. Although the statistical tests did not show significant variances in the mean HbA1c between the groups of participants regarding their hours of sleeping, the lowest mean HbA1c was observed in the group of participants who slept for 6-8 hours and had longer night-time sleeping hours. Conclusion: A short sleep duration, and absence of night-time sleep were significantly observed among the majority of the study population during Ramadan, which could suppress the full benefits of Ramadan fasting for diabetic patients. This study showed that there is a good agreement between the findings of the questionnaire and the Fitbit device for evaluating sleeping patterns in a Saudi population. A larger study is needed in the future to investigate the impact of Ramadan fasting on sleep quality and quantity and its relationship with health and disease.

Keywords: Diabetes, Fasting, Fitbit, HbA1c, IPAQ, Ramadan, Sleep

Procedia PDF Downloads 96
4676 Brewing in a Domestic Refrigerator Using Freeze-Dried Raw Materials

Authors: Angelika-Ioanna Gialleli, Gousi Mantha, Maria Kanellaki, Bekatorou Argyro, Athanasios Koutinas

Abstract:

In this study, a new brewing technology with dry raw materials is proposed with potential application in home brewing. Bio catalysts were prepared by immobilization of the psychrotolerant yeast strain Saccharomyces cerevisiae AXAZ-1 on tubular cellulose. Both the word and the biocatalysts were freeze-dried without any cryoprotectants and used for low temperature brewing. The combination of immobilization and freeze-drying techniques was applied successfully, giving a potential for supplying breweries with preserved and ready-to-use immobilized cells. The effect of wort sugar concentration (7°, 8.5°, 10°Be), temperature (2, 5, 7° C) and carrier concentration (5, 10, 20 g/L) on fermentation kinetics and final product quality (volatiles, colour, polyphenols, bitterness) was assessed. The same procedure was repeated with free cells for comparison of the results. The results for immobilized cells were better compared to free cells regarding fermentation kinetics and organoleptic characteristics.

Keywords: brewing, tubular cellulose, low temperature, biocatalyst

Procedia PDF Downloads 313
4675 The Application of Lean-Kaizen in Course Plan and Delivery in Malaysian Higher Education Sector

Authors: Nur Aishah Binti Awi, Zulfiqar Khan

Abstract:

Lean-kaizen has always been applied in manufacturing sector since many years ago. What about education sector? This paper discuss on how lean-kaizen can also be applied in education sector, specifically in academic area of Malaysian’s higher education sector. The purpose of this paper is to describe the application of lean kaizen in course plan and delivery. Lean-kaizen techniques have been used to identify waste in the course plan and delivery. A field study has been conducted to obtain the data. This study used both quantitative and qualitative data. The researcher had interviewed the chosen lecturers regarding to the problems of course plan and delivery that they encountered. Secondary data of students’ feedback at the end of semester also has been used to improve course plan and delivery. The result empirically shows that lean-kaizen helps to improve the course plan and delivery by reducing the wastes. Thus, this study demonstrates that lean-kaizen can also help education sector to improve their services as achieved by manufacturing sector.

Keywords: course delivery, education, Kaizen, lean

Procedia PDF Downloads 356
4674 Naïve Bayes: A Classical Approach for the Epileptic Seizures Recognition

Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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4673 Proxisch: An Optimization Approach of Large-Scale Unstable Proxy Servers Scheduling

Authors: Xiaoming Jiang, Jinqiao Shi, Qingfeng Tan, Wentao Zhang, Xuebin Wang, Muqian Chen

Abstract:

Nowadays, big companies such as Google, Microsoft, which have adequate proxy servers, have perfectly implemented their web crawlers for a certain website in parallel. But due to lack of expensive proxy servers, it is still a puzzle for researchers to crawl large amounts of information from a single website in parallel. In this case, it is a good choice for researchers to use free public proxy servers which are crawled from the Internet. In order to improve efficiency of web crawler, the following two issues should be considered primarily: (1) Tasks may fail owing to the instability of free proxy servers; (2) A proxy server will be blocked if it visits a single website frequently. In this paper, we propose Proxisch, an optimization approach of large-scale unstable proxy servers scheduling, which allow anyone with extremely low cost to run a web crawler efficiently. Proxisch is designed to work efficiently by making maximum use of reliable proxy servers. To solve second problem, it establishes a frequency control mechanism which can ensure the visiting frequency of any chosen proxy server below the website’s limit. The results show that our approach performs better than the other scheduling algorithms.

Keywords: proxy server, priority queue, optimization algorithm, distributed web crawling

Procedia PDF Downloads 200
4672 Trajectory Design and Power Allocation for Energy -Efficient UAV Communication Based on Deep Reinforcement Learning

Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

Abstract:

In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

Procedia PDF Downloads 132
4671 Early Stage Suicide Ideation Detection Using Supervised Machine Learning and Neural Network Classifier

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

Abstract:

In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 79