Search results for: cleaning machine

Authors: Dmitry Fedoseyev

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The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

Procedia PDF Downloads 61

Authors: Isabel Schestak, Jan Spriet, David Styles, Prysor Williams

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Breweries and distilleries are well-known for their high water usage. The water consumption in a UK brewery to produce one litre of beer reportedly ranges from 3-9 L and in a distillery from 7-45 L to produce a litre of spirit. This includes product water such as mashing water, but also water for wort and distillate cooling and for cleaning of tanks, casks, and kegs. When cooling towers are used, cooling water can be the dominating water consumption in a brewery or distillery. Interlinked to the high water use is a substantial heating requirement for mashing, wort boiling, or distillation, typically met by fossil fuel combustion such as gasoil. Many water and waste water streams are leaving the processes hot, such as the returning cooling water or the pot ales. Therefore, several options exist to optimise water and energy efficiency of spirit production through heat recovery. Although these options are known in the sector, they are often not applied in practice due to planning efforts or financial obstacles. In this study, different possibilities and design options for heat recovery systems are explored in four breweries/distilleries in the UK and assessed from an economic but also environmental point of view. The eco-efficiency methodology, according to ISO 14045, is applied to combine both assessment criteria to determine the optimum solution for heat recovery application in practice. The economic evaluation is based on the total value added (TVA) while the Life Cycle Assessment (LCA) methodology is applied to account for the environmental impacts through the installations required for heat recovery. The four case study businesses differ in a) production scale with mashing volumes ranging from 2500 to 40,000 L, in b) terms of heating and cooling technology used, and in c) the extent to which heat recovery is/is not applied. This enables the evaluation of different cases for heat recovery based on empirical data. The analysis provides guidelines for practitioners in the brewing and distilling sector in and outside the UK for the realisation of heat recovery measures. Financial and environmental payback times are showcased for heat recovery systems in the four distilleries which are operating at different production scales. The results are expected to encourage the application of heat recovery where environmentally and economically beneficial and ultimately contribute to a reduction of the water and energy footprint in brewing and distilling businesses.

Keywords: brewery, distillery, eco-efficiency, heat recovery from process and waste water, life cycle assessment

Procedia PDF Downloads 117

Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

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Thermal and Hydrodynamic are basic aspects in any hydraulic system and therefore, they must be assessed with regard to this aspect before constructing the system. This assessment needs a good expertise in this aspect to obtain an efficient hydraulic system. Therefore, this study aims to build an expert system called Hydraulic System Calculations (HSC) to ensure a smooth operation for the hydraulic system. The expert system (HSC) had been designed and coded in an user-friendly interactive program called Microsoft Visual Basic 2010. The suggested code provides the designer with a number of choices to resolve the problem of hydraulic oil overheating which may arise during the continuous operation of the hydraulic unit. As a result, the HSC can minimize the human errors, effort, time and cost of hydraulic machine design.

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

Procedia PDF Downloads 443

Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

Procedia PDF Downloads 445

Authors: Petros Gkotsis, Anastasios Zouboulis, Manasis Mitrakas, Dimitrios Zamboulis, E. Peleka

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The most serious drawback in wastewater treatment using membrane bioreactors (MBRs) is membrane fouling which gradually leads to membrane permeability decrease and efficiency deterioration. This work is part of a research project that aims to develop an integrated methodology for membrane fouling control, using specific chemicals which will enhance the coagulation and flocculation of compounds responsible for fouling, hence reducing biofilm formation on the membrane surface and limiting the fouling rate acting as a pre-treatment step. For this purpose, a pilot-scale plant with fully automatic operation achieved by means of programmable logic controller (PLC) has been constructed and tested. The experimental set-up consists of four units: wastewater feed unit, bioreactor, membrane (side-stream) filtration unit and permeate collection unit. Synthetic wastewater was fed as the substrate for the activated sludge. The dissolved oxygen (DO) concentration of the aerobic tank was maintained in the range of 2-3 mg/L during the entire operation by using an aerator below the membrane module. The membranes were operated at a flux of 18 LMH while membrane relaxation steps of 1 min were performed every 10 min. Both commercial and composite coagulants are added in different concentrations in the pilot-scale plant and their effect on the overall performance of the ΜΒR system is presented. Membrane fouling was assessed in terms of TMP, membrane permeability, sludge filterability tests, total resistance and the unified modified fouling index (UMFI). Preliminary tests showed that particular attention should be paid to the addition of the coagulant solution, indicating that pipe flocculation effectively increases hydraulic retention time and leads to voluminous sludge flocs. The most serious drawback in wastewater treatment using MBRs is membrane fouling, which gradually leads to membrane permeability decrease and efficiency deterioration. This results in increased treatment cost, due to high energy consumption and the need for frequent membrane cleaning and replacement. Due to the widespread application of MBR technology over the past few years, it becomes clear that the development of a methodology to mitigate membrane fouling is of paramount importance. The present work aims to develop an integrated technique for membrane fouling control in MBR systems and, thus, contribute to sustainable wastewater treatment.

Keywords: coagulation, membrane bioreactor, membrane fouling, pilot plant

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Tusar Kanti Dash, Ganapati Panda

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The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models.

Keywords: non-Intrusive speech evaluation, S-transform, light GBM, speech quality, and intelligibility

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: G. Hemath Kumar, H. Mohit, K. Karthick

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One of the most important issues in the composite technology is the repairing of parts of aircraft structures which is manufactured from composite materials. In such applications and also for joining various composite parts together, they are fastened together either using adhesives or mechanical fasteners. The tensile strength of these joints was carried out using Universal Testing Machine (UTM). A parametric study was also conducted to compare the performance of the hybrid joint with varying adherent thickness, adhesive thickness and overlap length. The composition of the material is combination of epoxy resin and carbon fibre under the method of reinforcement. To utilize the full potential of composite materials as structural elements, the strength and stress distribution of these joints must be understood. The study of tensile strength in the members involved under various design conditions and various joints were took place.

Keywords: carbon fiber, FRP composite, MMC, automotive

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Authors: Nabilah Ibrahim, Hafiz Mohd Zaini, Wan Fatin Liyana Mutalib

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Ultrasound equipment or machine is capable to scan in two dimensional (2D) areas. However there are some limitations occur during scanning an object. The problem will occur when scanning process that involving the asymmetric object. In this project, the ultrasound probe holder for asymmetric reflector scanning in 3D image is proposed to make easier for scanning the phantom or object that has asymmetric shape. Initially, the constructed asymmetric phantom that construct will be used in 2D scanning. Next, the asymmetric phantom will be interfaced by the movement of ultrasound probe holder using the Arduino software. After that, the performance of the ultrasound probe holder will be evaluated by using the various asymmetric reflector or phantom in constructing a 3D image

Keywords: ultrasound 3D images, axial and lateral resolution, asymmetric reflector, Arduino software

Procedia PDF Downloads 558

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

Procedia PDF Downloads 288

Authors: Ahmed Abbou, Ali Mousmi, Rachid El Akhrif

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This research paper aims to reduce the chattering phenomenon due to control by sliding mode control applied on a wind energy conversion system based on the doubly fed induction generator (DFIG). Our goal is to offset the effect of parametric uncertainties and come as close as possible to the dynamic response solicited by the control law in the ideal case and therefore force the active and reactive power generated by the DFIG to accurately follow the reference values which are provided to it. The simulation results using Matlab / Simulink demonstrate the efficiency and performance of the proposed technique while maintaining the simplicity of control by first order sliding mode.

Keywords: correction of the equivalent command, DFIG, induction machine, sliding mode controller

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Authors: Ahmed A.D. Sarhan, Chong Feng Duan, Mum Wai Yip, M. Sayuti

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Rapid Prototyping (RP) technologies enable physical parts to be produced from various materials without depending on the conventional tooling. Fused Deposition Modeling (FDM) is one of the famous RP processes used at present. Tensile strength and compressive strength resistance will be identified for different sample structures and different layer orientations of ABS rapid prototype solid models. The samples will be fabricated by a FDM rapid prototyping machine in different layer orientations with variations in internal geometrical structure. The 0° orientation where layers were deposited along the length of the samples displayed superior strength and impact resistance over all the other orientations. The anisotropic properties were probably caused by weak interlayer bonding and interlayer porosity.

Keywords: building orientation, compression strength, rapid prototyping, tensile strength

Procedia PDF Downloads 694

Authors: Eric Shannon, Mark J. McGuire, John P. Parmigiani

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A hazard associated with the use of timber harvesters is chain shot. Harvester saw chain is subjected to large dynamic mechanical stresses which can cause it to fracture. The resulting open loop of saw chain can fracture a second time and create a projectile consisting of several saw-chain links referred to as a chain shot. Its high kinetic energy enables it to penetrate operator enclosures and be a significant hazard. Accurate data on projectile composition, mass, and speed are needed for the design of both operator enclosures resistant to projectile penetration and for saw chain resistant to fracture. The work presented here contributes to providing this data through the use of a test machine designed and built at Oregon State University. The machine’s enclosure is a standard shipping container. To safely contain any anticipated chain shot, the container was lined with both 9.5 mm AR500 steel plates and 50 mm high-density polyethylene (HDPE). During normal operation, projectiles are captured virtually undamaged in the HDPE enabling subsequent analysis. Standard harvester components are used for bar mounting and chain tensioning. Standard guide bars and saw chains are used. An electric motor with flywheel drives the system. Testing procedures follow ISO Standard 11837. Chain speed at break was approximately 45.5 m/s. Data was collected using both a 75 cm solid bar (Oregon 752HSFB149) and 90 cm solid bar (Oregon 902HSFB149). Saw chains used were 89 Drive Link .404”-18HX loops made from factory spools. Standard 16-tooth sprockets were used. Projectile speed was measured using both a high-speed camera and a chronograph. Both rotational and translational kinetic energy are calculated. For this study 50 chain shot events were executed. Results showed that projectiles consisted of a variety combinations of drive links, tie straps, and cutter links. Most common (occurring in 60% of the events) was a drive-link / tie-strap / drive-link combination having a mass of approximately 10.33 g. Projectile mass varied from a minimum of 2.99 g corresponding to a drive link only to a maximum of 18.91 g corresponding to a drive-link / tie-strap / drive-link / cutter-link / drive-link combination. Projectile translational speed was measured to be approximately 270 m/s and rotational speed of approximately 14000 r/s. The calculated translational and rotational kinetic energy magnitudes each average over 600 J. This study provides useful information for both timber harvester manufacturers and saw chain manufacturers to design products that reduce the hazards associated with timber harvesting.

Keywords: chain shot, timber harvesters, safety, testing

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 137

Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Jose D. Herrera, Mario A. Rios

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This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

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Authors: Choupani Andisheh, Temucin Elif Sevval, Bediz Bekir

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Due to their various advantages compared to many other drug delivery systems such as hypodermic injections and oral medications, microneedle arrays (MNAs) are a promising drug delivery system. To achieve enhanced performance of the MN, it is crucial to develop numerical models, optimization methods, and simulations. Accordingly, in this work, the optimized design of dissolvable MNAs, as well as their manufacturing, is investigated. For this purpose, a mechanical model of a single MN, having the geometry of an obelisk, is developed using commercial finite element software. The model considers the condition in which the MN is under pressure at the tip caused by the reaction force when penetrating the skin. Then, a multi-objective optimization based on non-dominated sorting genetic algorithm II (NSGA-II) is performed to obtain geometrical properties such as needle width, tip (apex) angle, and base fillet radius. The objective of the optimization study is to reach a painless and effortless penetration into the skin along with minimizing its mechanical failures caused by the maximum stress occurring throughout the structure. Based on the obtained optimal design parameters, master (male) molds are then fabricated from PMMA using a mechanical micromachining process. This fabrication method is selected mainly due to the geometry capability, production speed, production cost, and the variety of materials that can be used. Then to remove any chip residues, the master molds are cleaned using ultrasonic cleaning. These fabricated master molds can then be used repeatedly to fabricate Polydimethylsiloxane (PDMS) production (female) molds through a micro-molding approach. Finally, Polyvinylpyrrolidone (PVP) as a dissolvable polymer is cast into the production molds under vacuum to produce the dissolvable MNAs. This fabrication methodology can also be used to fabricate MNAs that include bioactive cargo. To characterize and demonstrate the performance of the fabricated needles, (i) scanning electron microscope images are taken to show the accuracy of the fabricated geometries, and (ii) in-vitro piercing tests are performed on artificial skin. It is shown that optimized MN geometries can be precisely fabricated using the presented fabrication methodology and the fabricated MNAs effectively pierce the skin without failure.

Keywords: microneedle, microneedle array fabrication, micro-manufacturing structural optimization, finite element analysis

Procedia PDF Downloads 111

Authors: Carlos Y. Soto, Camila A. Lota, G. Astrid Garzón

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Bacterial biofilms cause an ongoing problem for food safety. They are formed when microorganisms aggregate to form a community that attaches to solid surfaces. Biofilms increase the resistance of pathogens to cleaning, disinfection and antibacterial products. This resistance gives rise to problems for human health, industry, and agriculture. At present, plant extracts rich in polyphenolics are being investigated as natural alternatives to degrade bacterial biofilms. The pomace of the tropical Berry Vaccinium meridionale S. contains high amounts of phenolic compounds. Therefore, in the current study, the antimicrobial and antibiofilm effects of extracts from the pomace of Vaccinium meridionale S. were tested on three foodborne pathogens: Enterohaemorrhagic Escherichia coli O157:H7 (ATCC®700728TM), Staphylococcus aureus subsp. aureus (ATCC® 6538TM), and Salmonella enterica serovar Enteritidis (ATCC® 13076TM). Microwave-assisted extraction was used to extract polyphenols with aqueous methanol (80% v/v) at a solid to solvent ratio of 1:10 (w/v) for 20 min. The magnetic stirring was set at 400 rpm, and the microwave power was adjusted to 400 W. The antimicrobial effect of the extract was assessed by determining the half maximal inhibitory concentration (IC50) against the three food poisoning pathogens at concentrations ranging from 50 to 2,850 μg gallic acid equivalents (GAE)/mL of the extract. Biofilm inhibition was assessed using a crystal violet assay applying the same range of concentration. Three replications of the experiments were carried out, and all analyses were run in triplicate. IC50 values were determined using the GraphPad Prism8® program. Significant differences (P<0.05) among means were identified using one-factor analysis of variance (ANOVA) and the post-hoc least significant difference (LSD) test using the Statgraphics plus program, version 2.1.There was significant difference among the mean IC50 values for the tested bacteria. The IC50 for S. aureus was 48 ± 9 μg GAE/mL, followed by 123 ± 49 μg GAE/mL for Salmonella and 376 ± 32 μg GAE/mL for E. coli. The percent inhibition of the extract on biofilm formation was significantly higher for S. aureus (85.8  0.3), followed by E. coli (74.5  1.0) and Salmonella (53.6  9.7). These findings suggest that polyphenolic extracts obtained from the pomace of V. meridionale S. might be used as natural antimicrobial and anti-biofilm natural agents, effective against S. aureus, E. coli and Salmonella enterica.

Keywords: antibiofilm, antimicrobial, E. coli, S. aureus, salmonella, IC50, pomace, V. meridionale

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Grace Fangmin Tan, Elaine Yiling Tay, Elizabeth Huiwen Tham, Andrea Wei Ching Yeo

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Background: While accidental poisonings in children may seem unavoidable, knowledge of circumstances surrounding such incidents and identification of risk factors is important in the development of secondary prevention strategies. Some risk factors include age of the child, lack of adequate supervision and improper storage of substances. The aim of this study is to assess risk factors and circumstances influencing outcomes in these children. Methodology: A retrospective medical record review of all accidental poisoning cases presenting to the Children’s Emergency at National University Hospital (NUH), Singapore between January 2014 and December 2015 was conducted. Information on demographics, poisoning circumstances and clinical outcomes were collected. Results: Ninety-nine of a total of 186 poisoning cases were accidental ingestions, with a mean age of 4.7 (range 0.4 to 18.3 years). The gender distribution is rather equal with 52(52.5%) females and 47(47.5%) males. Seventy-nine (79.8%) were self-administered by the child and in 20 cases (20.2%), the substance was administered erroneously by caregivers 12/20 (60.0%) of whom were given the wrong drug dose while 8/20 (40.0%) were given the wrong substance. Self-administration was associated with presentation to the ED within 12 hours (p=0.027, OR 6.65, 95% CI 1.24-35.72). Notably, 94.9% of the cases involved substances kept within reach of the child. Sixty-nine (82.1%) had the substance kept in the original container, 3(3.6%) in food containers, 8(9.5%) in other containers and 4(4.8%) without a container. Of the 50 cases with information on labelling, 40/50(80.0%) were accurately labelled, 2/50 (4.0%) wrongly labelled, and 8/50 (16.0%) were unlabelled. Implicated substances included personal care products (11.1%), household cleaning products (3.0%), and different classes of drugs such as paracetamol (22.2%), antihistamines (17.2%) and sympathomimetics (8.1%). Children < 3 years of age were 4.8 times more likely to be poisoned by household substances than children >3 years of age (p=0.009, 95% CI 1.48-15.77). Prehospital interventions were more likely to have been done in poisoning with household substances (p=0.005, OR 6.12 95% CI 1.73-21.68). Fifty-nine (59.6%) were asymptomatic, 34 (34.3%) had a Poisoning Severity Score (PSS) grade of 1 (minor) and 6 (6.1%) grade 2 (moderate). Older children were 9.3 times more likely to be symptomatic (p<0.001, 95% CI 3.15-27.25). Thirty (32%) required admission. Conclusion: A significant proportion of accidental poisoning cases were due to medication administration errors by caregivers, which should be preventable. Risk factors for accidental poisoning included lack of adequate caregiver supervision, improper labelling and young age of the child. There is an urgent need to improve caregiver counselling during medication dispensing as well as to educate caregivers on basic child safety measures in the home to prevent future accidental poisonings.

Keywords: accidental, caregiver, paediatrics, poisoning

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Authors: Jaskirat Singh, Roshan Lal Virdi, Khushdeep Goyal

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The purpose of this paper is to perform a microstructural analysis of Friction Stir Welded joints of aluminum alloys 6063 and 5083, also to check the properties of the weld zone by SEM analysis. FSW experiments were carried on CNC Vertical milling machine. The tools used for welding were the round cylindrical pin shape and square pin shape. It is found that Microstructure shows the uniformly distributed material with minimum heat affected zone and dense welded zone without any defect. Microstructures indicate that the weld material is defect free. The SEM shows the diffusion of material with base metal with proper bonding without any defect.

Keywords: friction stir welding, aluminum alloy, microstructure, SEM analysis

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

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Authors: Daniel Bülz, Franziska Lüttich, Sreetama Banerjee, Georgeta Salvan, Dietrich R. T. Zahn

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For the development of electronics, organic semiconductors are of great interest due to their adjustable optical and electrical properties. Especially for spintronic applications they are interesting because of their weak spin scattering, which leads to longer spin life times compared to inorganic semiconductors. It was shown that some organic materials change their resistance if an external magnetic field is applied. Pentacene is one of the materials which exhibit the so called photoinduced magnetoresistance which results in a modulation of photocurrent when varying the external magnetic field. Also the soluble derivate of pentacene, the 6,13-bis (triisopropylsilylethynyl)-pentacene (TIPS-pentacene) exhibits the same negative magnetoresistance. Aiming for simpler fabrication processes, in this work, we compare TIPS-pentacene organic field effect transistors (OFETs) made from solution with those fabricated by thermal evaporation. Because of the different processing, the TIPS-pentacene thin films exhibit different morphologies in terms of crystal size and homogeneity of the substrate coverage. On the other hand, the interface treatment is known to have a high influence on the threshold voltage, eliminating trap states of silicon oxide at the gate electrode and thereby changing the electrical switching response of the transistors. Therefore, we investigate the influence of interface treatment using octadecyltrichlorosilane (OTS) or using a simple cleaning procedure with acetone, ethanol, and deionized water. The transistors consist of a prestructured OFET substrates including gate, source, and drain electrodes, on top of which TIPS-pentacene dissolved in a mixture of tetralin and toluene is deposited by drop-, spray-, and spin-coating. Thereafter we keep the sample for one hour at a temperature of 60 °C. For the transistor fabrication by thermal evaporation the prestructured OFET substrates are also kept at a temperature of 60 °C during deposition with a rate of 0.3 nm/min and at a pressure below 10-6 mbar. The OFETs are characterized by means of optical microscopy in order to determine the overall quality of the sample, i.e. crystal size and coverage of the channel region. The output and transfer characteristics are measured in the dark and under illumination provided by a white light LED in the spectral range from 450 nm to 650 nm with a power density of (8±2) mW/cm2.

Keywords: organic field effect transistors, solution processed, surface treatment, TIPS-pentacene

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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Authors: Poornima Gupta, Sadaf Siraj

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The study examined the organizational causes of organizational stress in women executives and entrepreneurs in India. This was done so that mediation strategies could be developed to combat the organizational stress experienced by them, in order to retain the female employees as well as attract quality talent. The data for this research was collected through the self- administered survey, from the women executives across various industries working at different levels in management. The research design of the study was descriptive and cross-sectional. It was carried out through a self-administered questionnaire filled in by the women executives and entrepreneurs in the NCR region. Multistage sampling involving stratified random sampling was employed. A total of 1000 questionnaires were distributed out of which 450 were returned and after cleaning the data 404 were fit to be considered for analyses. The overall findings of the study suggested that there were various job-related factors that induce stress. Fourteen factors were identified which were a major cause of stress among the working women by applying Factor analysis. The study also assessed the demographic factors which influence the stress in women executives across various industries. The findings show that the women, no doubt, were stressed by organizational factors. The mean stress score was 153 (out of a possible score of 196) indicating high stress. There appeared to be an inverse relationship between the marital status, age, education, work experience, and stress. Married women were less stressed compared to single women employees. Similarly, female employees 29 years or younger experienced more stress at work. Women having education up to 12th standard or less were more stressed compared to graduates and post graduates. Women who had spent more than two years in the same organization perceived more stress compared to their counterparts. Family size and income, interestingly, had no significant impact on stress. The study also established that the level of stress experienced by women across industries differs considerably. Banking sector emerged as the industry where the women experienced the most stress followed by Entrepreneurs, Medical, BPO, Advertising, Government, Academics, and Manufacturing, in that order. The results contribute to the better understanding of the personal and economic factors surrounding job stress and working women. It concludes that the organizations need to be sensitive to the women’s needs. Organizations are traditionally designed around men with the rules made by the men for the men. Involvement of women in top positions, decision making, would make them feel more useful and less stressed. The invisible glass ceiling causes more stress than realized among women. Less distinction between the men and women colleagues in terms of giving responsibilities, involvement in decision making, framing policies, etc. would go a long way to reduce stress in women.

Keywords: women, stress, gender in management, women in management

Procedia PDF Downloads 255