Search results for: testing effectiveness
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6862

Search results for: testing effectiveness

2932 The Development of a Miniaturized Raman Instrument Optimized for the Detection of Biosignatures on Europa

Authors: Aria Vitkova, Hanna Sykulska-Lawrence

Abstract:

In recent years, Europa has been one of the major focus points in astrobiology due to its high potential of harbouring life in the vast ocean underneath its icy crust. However, the detection of life on Europa faces many challenges due to the harsh environmental conditions and mission constraints. Raman spectroscopy is a highly capable and versatile in-situ characterisation technique that does not require any sample preparation. It has only been used on Earth to date; however, recent advances in optical and laser technology have also allowed it to be considered for extraterrestrial exploration. So far, most efforts have been focused on the exploration of Mars, the most imminent planetary target. However, as an emerging technology with high miniaturization potential, Raman spectroscopy also represents a promising tool for the exploration of Europa. In this study, the capabilities of Raman technology in terms of life detection on Europa are explored and assessed. Spectra of biosignatures identified as high priority molecular targets for life detection on Europa were acquired at various excitation wavelengths and conditions analogous to Europa. The effects of extremely low temperatures and low concentrations in water ice were explored and evaluated in terms of the effectiveness of various configurations of Raman instruments. Based on the findings, a design of a miniaturized Raman instrument optimized for in-situ detection of life on Europa is proposed.

Keywords: astrobiology, biosignatures, Europa, life detection, Raman Spectroscopy

Procedia PDF Downloads 191
2931 Effect of External Radiative Heat Flux on Combustion Characteristics of Rigid Polyurethane Foam under Piloted-Ignition and Radiative Auto-Ignition Modes

Authors: Jia-Jia He, Lin Jiang, Jin-Hua Sun

Abstract:

Rigid polyurethane foam (RPU) has been extensively applied in building insulation system, yet with high flammability for being easily ignited by high temperature spark or radiative heat flux from other flaming materials or surrounding building facade. Using a cone calorimeter by Fire Testing Technology and thermal couple tree, this study systematically investigated the effect of radiative heat flux on the ignition time and characteristic temperature distribution during RPU combustion under different heat fluxes gradient (12, 15, 20, 25, 30, 35, 40, 45, and 50 kW/m²) with spark ignition/ignition by radiation. The ignition time decreases proportionally with increase of external heat flux, meanwhile increasing the external heat flux raises the peak heat release rate and impresses on the vertical temperature distribution greatly. The critical ignition heat flux is found to be 15 and 25 kW/m² for spark ignition and radiative ignition, respectively. Based on previous experienced ignition formula, a methodology to predict ignition times in both modes has been developed theoretically. By analyzing the heat transfer mechanism around the sample surroundings, both radiation from cone calorimeter and convection flow are considered and calculated theoretically. The experimental ignition times agree well with the theoretical ones in both radiative and convective conditions; however, the observed critical ignition heat flux is higher than the calculated one under piloted-ignition mode because the heat loss process, especially in lower heat flux radiation, is not considered in this developed methodology.

Keywords: rigid polyurethane foam, cone calorimeter, ignition time, external heat flux

Procedia PDF Downloads 187
2930 Modelling Home Appliances for Energy Management System: Comparison of Simulation Results with Measurements

Authors: Aulon Shabani, Denis Panxhi, Orion Zavalani

Abstract:

This paper presents the modelling and development of a simulator for residential electrical appliances. The simulator is developed on MATLAB providing the possibility to analyze and simulate energy consumption of frequently used home appliances in Albania. Modelling of devices considers the impact of different factors, mentioning occupant behavior and climacteric conditions. Most devices are modeled as an electric circuit, and the electric energy consumption is estimated by the solutions of the guiding differential equations. The provided models refer to devices like a dishwasher, oven, water heater, air conditioners, light bulbs, television, refrigerator water, and pump. The proposed model allows us to simulate beforehand the energetic behavior of the largest consumption home devices to estimate peak consumption and improving its reduction. Simulated home prototype results are compared to real measurement of a considered typical home. Obtained results from simulator framework compared to monitored typical household using EmonTxV3 show the effectiveness of the proposed simulation. This conclusion will help for future simulation of a large group of typical household for a better understanding of peak consumption.

Keywords: electrical appliances, energy management, modelling, peak estimation, simulation, smart home

Procedia PDF Downloads 145
2929 Testing the Possibility of Healthy Individuals to Mimic Fatigability in Multiple Sclerotic Patients

Authors: Emmanuel Abban Sagoe

Abstract:

A proper functioning of the Central Nervous System ensures that we are able to accomplish just about everything we do as human beings such as walking, breathing, running, etc. Myelinated neurons throughout the body which transmit signals at high speeds facilitate these actions. In the case of MS, the body’s immune system attacks the myelin sheath surrounding the neurons and overtime destroys the myelin sheaths. Depending upon where the destruction occurs in the brain symptoms can vary from person to person. Fatigue is, however, the biggest problem encountered by an MS sufferer. It is very often described as the bedrock upon which other symptoms of MS such challenges in balance and coordination, dizziness, slurred speech, etc. may occur. Classifying and distinguishing between perceptions based fatigue and performance based fatigability is key to identifying appropriate treatment options for patients. Objective methods for assessing motor fatigability is also key to providing clinicians and physiotherapist with critical information on the progression of the symptom. This study tested if the Fatigue Index Kliniken Schmieder assessment tool can detect fatigability as seen in MS patients when healthy subjects with no known history of neurological pathology mimic abnormal gaits. Thirty three healthy adults between ages 18-58years volunteered as subjects for the study. The subjects, strapped with RehaWatch sensors on both feet, completed 6 gait protocols of normal and mimicked fatigable gaits for 60 seconds per each gait and at 1.38889m/s treadmill speed following clear instructions given.

Keywords: attractor attributes, fatigue index Kliniken Schmieder, gait variability, movement pattern

Procedia PDF Downloads 105
2928 Prevalence of Cytomegalovirus DNA in the Patients’ Serum with HIV using Real-Time PCR

Authors: Mohammadreza Aghasadeghi, Mojtaba Hamidi-Fard, Seyed Amir Sadeghi, Ashkan Noorbakhsh

Abstract:

Introduction: HIV is known as one of the most important pathogens and mortality in all human societies, but unfortunately, no definitive cure has been found for it. Due to its weakened immune system, this virus causes a variety of primary and secondary opportunistic infections. Cytomegalovirus (CMV) is one of the most relevant opportunistic viruses seen in HIV-positive people that cause various infections in HIV-positive people. This virus causes various infections in HIV-positive people, such as retinal infection (CMVR), gastrointestinal infections, diarrhea, severe weight loss, and cerebrospinal fluid problems. These various infections make it important to evaluate the prevalence of CMV in HIV-positive people to diagnose it quickly and in a timely manner. This infection in HIV-positive people reduces life expectancy and causes serious harm to patients. However, a simple test in HIV-positive people can prevent the virus from progressing. Material and Methods: In this study, we collected 200 blood samples (including 147 men and 53 women) from HIV-positive individuals and examined the frequency of CMV-DNA in these cases by real-time PCR method. In the next step, the data was analyzed by SPSS software, and then we obtained the relationship between age, sex, and the frequency of CMV in HIV-positive individuals. Results: The total frequency of CMV DNA was about 59%, which is a relatively high prevalence due to the age range of the subjects. The frequency in men was 61.2% and 52.8% in women. This frequency was also higher in males than females. We also observed more frequency in two age groups of 16 to 30 years and 31 to 45 years. Discussion: Due to the high prevalence of CMV in HIV-positive individuals and causing serious problems in this group of people, this study was shown that both the patients and the community should pay more attention to this issue. Ministry of Health, as a stakeholder organization, can make CMV DNA testing mandatory as soon as a person is HIV positive.

Keywords: CMV, HIV, AIDS, real-time PCR, SPSS

Procedia PDF Downloads 200
2927 Multi Object Tracking for Predictive Collision Avoidance

Authors: Bruk Gebregziabher

Abstract:

The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

Procedia PDF Downloads 68
2926 Applicability of Fuzzy Logic for Intrusion Detection in Mobile Adhoc Networks

Authors: Ruchi Makani, B. V. R. Reddy

Abstract:

Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

Procedia PDF Downloads 163
2925 Green Synthesis of Nano Liposomes Containing Berberine Chlorideagainst Leishmania major

Authors: Ali Fattahi Bafghi, Abolghasem Siyadatpanah, Farzaneh Mirzaei, Fahimeh Pournasir, Roghayeh Norouzi, Maria De Lourdes Pereira

Abstract:

Leishmaniasis caused by Leishmania major is one of the main infectious diseases that affect populations in developing countries around the world. We assessed the effectiveness of berberine chloride nano-liposome (BcNLs) against L. major promastigotes in vitro. Nano-liposomal berberine chloride was prepared using the thin-film hydration method and characterized based on encapsulation efficiency, size, and zeta potential. Anti-Leishmania effect of different concentrations (0.05-60 µg/ml) of BcNLs as studied in L. major [MRHO/IR/75/ER] at 24, 48, and 72 h using the hemocytometer technique. Berberine chloride was successfully loaded into nano-liposomes with an encapsulation efficiency of 85.54%. The surface charge of nanoparticles is neutral, and the morphology of nano-liposomal berberine chloride is spherical without any agglomeration. Cell viability assay was performed on the HFF cell line to show the biocompatibility of liposome nanoparticles. IC50 of BcNPs at 24, 48, and 72 h against L. major were found to be 7.6, 5.96, and 3.19 µg/ml, respectively. BcNLs showed a significant anti-Leishmania effect and induced a better and more tangible effect on the survival of L. major promastigotes and could be suitable candidates for further investigation. The results showed that the BcNLs agent is effective against L. major promastigotes and may be a promising alternative to current treatments.

Keywords: Leishmania major, berberine chloride, nano-liposomes, cutaneous leishmaniasis

Procedia PDF Downloads 133
2924 Design and Radio Frequency Characterization of Radial Reentrant Narrow Gap Cavity for the Inductive Output Tube

Authors: Meenu Kaushik, Ayon K. Bandhoyadhayay, Lalit M. Joshi

Abstract:

Inductive output tubes (IOTs) are widely used as microwave power amplifiers for broadcast and scientific applications. It is capable of amplifying radio frequency (RF) power with very good efficiency. Its compactness, reliability, high efficiency, high linearity and low operating cost make this device suitable for various applications. The device consists of an integrated structure of electron gun and RF cavity, collector and focusing structure. The working principle of IOT is a combination of triode and klystron. The cathode lies in the electron gun produces a stream of electrons. A control grid is placed in close proximity to the cathode. Basically, the input part of IOT is the integrated structure of gridded electron gun which acts as an input cavity thereby providing the interaction gap where the input RF signal is applied to make it interact with the produced electron beam for supporting the amplification phenomena. The paper presents the design, fabrication and testing of a radial re-entrant cavity for implementing in the input structure of IOT at 350 MHz operating frequency. The model’s suitability has been discussed and a generalized mathematical relation has been introduced for getting the proper transverse magnetic (TM) resonating mode in the radial narrow gap RF cavities. The structural modeling has been carried out in CST and SUPERFISH codes. The cavity is fabricated with the Aluminum material and the RF characterization is done using vector network analyzer (VNA) and the results are presented for the resonant frequency peaks obtained in VNA.

Keywords: inductive output tubes, IOT, radial cavity, coaxial cavity, particle accelerators

Procedia PDF Downloads 106
2923 A Machine Learning Approach for Anomaly Detection in Environmental IoT-Driven Wastewater Purification Systems

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

Procedia PDF Downloads 138
2922 The Impact of Quality Management System Establishment over the Performance of Public Administration Services in Kosovo

Authors: Ilir Rexhepi, Naim Ismajli

Abstract:

Quality and quality management are key factors of success nowadays. Public sector and quality management in this sector contains many challenges and difficulties, most notably in a new country like Kosovo. This study analyses the process of implementation of quality management system in public administration institutions in this country. The main objective is to show how to set up a quality management system and how does the quality management system setup affect the overall public administration services in Kosovo. This study shows how the efficiency and effectiveness of public institution services/performance is rapidly improving through the establishment and functionalization of Quality Management System. The specific impact of established QMC within the organization has resulted with the identification of mission related processes within the entire system including input identification, the person in charge and the way of conversion to the output of each activity though the interference with other service processes within the system. By giving detailed analyses of all steps of implementation of the Quality Management System, its effect and consequences towards the overall public institution service performance, we try to go one step further, by showing it as a very good example or tool of other public institutions for improving their service performance. Interviews with employees, middle and high level managers including the quality manager and general secretaries are also part of analyses in this paper.

Keywords: quality, quality management system, efficiency, public administration institutions

Procedia PDF Downloads 261
2921 Effect of B2O3 Addition on Sol-gel Synthesized 45S5 Bioglass

Authors: P. Dey, S. K. Pal

Abstract:

Ceramics or glass ceramics with the property of bone bonding at the nearby tissues and producing possible bone in growth are known to be bioactive. The most extensively used glass in this context is 45S5 which is a silica based bioglass mostly explored in the field of tissue engineering as scaffolds for bone repair. Nowadays, the borate based bioglass are being utilized in orthopedic area largely due to its superior bioactivity with the formation of bone bonding. An attempt has been made, in the present study, to observe the effect of B2O3 addition in 45S5 glass and perceive its consequences on the thermal, mechanical and biological properties. The B2O3 was added in 1, 2.5, and 5 wt% with simultaneous reduction in the silica content of the 45S5 composition. The borate based bioglass has been synthesized by the means of sol-gel route. The synthesized powders were then thermally analyzed by DSC-TG. The as synthesized powders were then calcined at 600ºC for 2hrs. The calcined powders were then pressed into pellets followed by sintering at 850ºC with a holding time of 2hrs. The phase analysis and the microstructural analysis of the as synthesized and calcined powder glass samples and the sintered glass samples were being carried out using XRD and FESEM respectively. The formation of hydroxyapatite layer was performed by immersing the sintered samples in the simulated body fluid (SBF) and mechanical property has been tested for the sintered samples by universal testing machine (UTM). The sintered samples showed the presence of sodium calcium silicate phase while the formation of hydroxyapaptite takes place for SBF immersed samples. The formation of hydroxyapatite is more pronounced in case of borated based glass samples instead of 45S5.

Keywords: 45S5 bioglass, bioactive, borate, hydroxyapatite, sol-gel synthesis

Procedia PDF Downloads 244
2920 Processing of Input Material as a Way to Improve the Efficiency of the Glass Production Process

Authors: Joanna Rybicka-Łada, Magda Kosmal, Anna Kuśnierz

Abstract:

One of the main problems of the glass industry is the still high consumption of energy needed to produce glass mass, as well as the increase in prices, fuels, and raw materials. Therefore, comprehensive actions are taken to improve the entire production process. The key element of these activities, starting from filling the set to receiving the finished product, is the melting process, whose task is, among others, dissolving the components of the set, removing bubbles from the resulting melt, and obtaining a chemically homogeneous glass melt. This solution avoids dust formation during filling and is available on the market. This process consumes over 90% of the total energy needed in the production process. The processes occurring in the set during its conversion have a significant impact on the further stages and speed of the melting process and, thus, on its overall effectiveness. The speed of the reactions occurring and their course depend on the chemical nature of the raw materials, the degree of their fragmentation, thermal treatment as well as the form of the introduced set. An opportunity to minimize segregation and accelerate the conversion of glass sets may be the development of new technologies for preparing and dosing sets. The previously preferred traditional method of melting the set, based on mixing all glass raw materials together in loose form, can be replaced with a set in a thickened form. The aim of the project was to develop a glass set in a selectively or completely densified form and to examine the influence of set processing on the melting process and the properties of the glass.

Keywords: glass, melting process, glass set, raw materials

Procedia PDF Downloads 45
2919 PointNetLK-OBB: A Point Cloud Registration Algorithm with High Accuracy

Authors: Wenhao Lan, Ning Li, Qiang Tong

Abstract:

To improve the registration accuracy of a source point cloud and template point cloud when the initial relative deflection angle is too large, a PointNetLK algorithm combined with an oriented bounding box (PointNetLK-OBB) is proposed. In this algorithm, the OBB of a 3D point cloud is used to represent the macro feature of source and template point clouds. Under the guidance of the iterative closest point algorithm, the OBB of the source and template point clouds is aligned, and a mirror symmetry effect is produced between them. According to the fitting degree of the source and template point clouds, the mirror symmetry plane is detected, and the optimal rotation and translation of the source point cloud is obtained to complete the 3D point cloud registration task. To verify the effectiveness of the proposed algorithm, a comparative experiment was performed using the publicly available ModelNet40 dataset. The experimental results demonstrate that, compared with PointNetLK, PointNetLK-OBB improves the registration accuracy of the source and template point clouds when the initial relative deflection angle is too large, and the sensitivity of the initial relative position between the source point cloud and template point cloud is reduced. The primary contribution of this paper is the use of PointNetLK to avoid the non-convex problem of traditional point cloud registration and leveraging the regularity of the OBB to avoid the local optimization problem in the PointNetLK context.

Keywords: mirror symmetry, oriented bounding box, point cloud registration, PointNetLK-OBB

Procedia PDF Downloads 139
2918 Gender Diversity in Early Years Education: An Exploratory Study Applied to Preschool Curriculum System in Romania

Authors: Emilia-Gheorghina Negru

Abstract:

As an EU goal, gender diversity in early year’s education aims and promotes equality of chances and respect for gender peculiarities of the pupils which are involved in formal educational activities. Early year’s education, as the first step to the Curriculum, prints to teachers the need to identify the role of the gender dimension on this stage, depending on the age level of preschool children through effective, complex, innovative and analytical awareness of gender diversity teaching and management strategies. Through gender educational work we, as teachers, will examine the effectiveness of the PATHS (Promoting Alternative Thinking Strategies) curriculum the gender development of school-aged children. PATHS and a school-based preventive intervention model are necessary to be designed to improve children's ability to discuss and understand equality and gender concepts. Our teachers must create an intervention model and provide PATHS lessons during the school year. Results of the intervention will be effective for both low- and high-risk children in improving their range of math’s skills for girls and vocabulary, fluency and emotional part for boys in discussing gender experiences, their efficacy beliefs regarding the management of equality in gender area, and their developmental understanding of some aspects of gender.

Keywords: gender, gender differences, gender equality, gender role, gender stereotypes

Procedia PDF Downloads 353
2917 Field Tests and Numerical Simulation of Tunis Soft Soil Improvement Using Prefabricated Vertical Drains

Authors: Marwa Ben Khalifa, Zeineb Ben Salem, Wissem Frikha

Abstract:

This paper presents a case study of “Radès la Goulette” bridge project using the technique of prefabricated vertical drains (PVD) associated with step by step construction of preloading embankments with averaged height of about 6 m. These embankments are founded on a highly compressible layer of Tunis soft soil. The construction steps included extensive soil instrumentation such as piezometers and settlement plates for monitoring the dissipation of excess pore water pressures and settlement during the consolidation of Tunis soft soil. An axisymmetric numerical model using the 2D finite difference code FLAC was developed and calibrated using laboratory tests to predict the soil behavior and consolidation settlements. The constitutive model impact for simulating the soft soil behavior is investigated. The results of analyses show that numerical analysis provided satisfactory predictions for the field performance during the construction of Radès la Goulette embankment. The obtained results show the effectiveness of PVD in the acceleration of the consolidation time. A comparison of numerical results with theoretical analysis was presented.

Keywords: tunis soft soil, radès bridge project, prefabricated vertical drains, FLAC, acceleration of consolidation

Procedia PDF Downloads 113
2916 Microbial Reduction of Terpenes from Pine Wood Material

Authors: Bernhard Widhalm, Cornelia Rieder-Gradinger, Thomas Ters, Ewald Srebotnik, Thomas Kuncinger

Abstract:

Terpenes are natural components in softwoods and rank among the most frequently emitted volatile organic compounds (VOC) in the wood-processing industry. In this study, the main focus was on α- and β-pinene as well as Δ3-carene, which are the major terpenes in softwoods. To lower the total emission level of wood composites, defined terpene degrading microorganisms were applied to basic raw materials (e.g. pine wood particles and strands) in an optimised and industry-compatible testing procedure. In preliminary laboratory tests, bacterial species suitable for the utilisation of α-pinene as single carbon source in liquid culture were selected and then subjected to wood material inoculation. The two species Pseudomonas putida and Pseudomonas fluorescens were inoculated onto wood particles and strands and incubated at room temperature. Applying specific pre-cultivation and daily ventilation of the samples enabled a reduction of incubation time from six days to one day. SPME measurements and subsequent GC-MS analysis indicated a complete absence of α- and β-pinene emissions after 24 hours from pine wood particles. When using pine wood strands rather than particles, bacterial treatment resulted in a reduction of α- and β-pinene by 50%, while Δ3-carene emissions were reduced by 30% in comparison to untreated strands. Other terpenes were also reduced in the course of the microbial treatment. The method developed here appears to be feasible for industrial application. However, growth parameters such as time and temperature as well as the technical implementation of the inoculation step will have to be adapted for the production process.

Keywords: GC-MS, pseudomonas, SPME, terpenes

Procedia PDF Downloads 332
2915 Development of Methods for Plastic Injection Mold Weight Reduction

Authors: Bita Mohajernia, R. J. Urbanic

Abstract:

Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

Procedia PDF Downloads 277
2914 The Impact of Hospital Strikes on Patient Care: Evidence from 135 Strikes in the Portuguese National Health System

Authors: Eduardo Costa

Abstract:

Hospital strikes in the Portuguese National Health Service (NHS) are becoming increasingly frequent, raising concerns in what respects patient safety. In fact, data shows that mortality rates for patients admitted during strikes are up to 30% higher than for patients admitted in other days. This paper analyses the effects of hospital strikes on patients’ outcomes. Specifically, it analyzes the impact of different strikes (physicians, nurses and other health professionals), on in-hospital mortality rates, readmission rates and length of stay. The paper uses patient-level data containing all NHS hospital admissions in mainland Portugal from 2012 to 2017, together with a comprehensive strike dataset comprising over 250 strike days (19 physicians-strike days, 150 nurses-strike days and 50 other health professionals-strike days) from 135 different strikes. The paper uses a linear probability model and controls for hospital and regional characteristics, time trends, and changes in patients’ composition and diagnoses. Preliminary results suggest a 6-7% increase in in-hospital mortality rates for patients exposed to physicians’ strikes. The effect is smaller for patients exposed to nurses’ strikes (2-5%). Patients exposed to nurses strikes during their stay have, on average, higher 30-days urgent readmission rates (4%). Length of stay also seems to increase for patients exposed to any strike. Results – conditional on further testing, namely on non-linear models - suggest that hospital operations and service levels are partially disrupted during strikes.

Keywords: health sector strikes, in-hospital mortality rate, length of stay, readmission rate

Procedia PDF Downloads 125
2913 Free Vibration of Axially Functionally Graded Simply Supported Beams Using Differential Transformation Method

Authors: A. Selmi

Abstract:

Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Keywords: differential transformation method, functionally graded material, mode shape, natural frequency

Procedia PDF Downloads 290
2912 The Use of Continuous Improvement Methods to Empower the Osh MS With Leading Key Performance Indicators

Authors: Maha Rashid Al-Azib, Almuzn Qasem Alqathradi, Amal Munir Alshahrani, Bilqis Mohammed Assiri, Ali Almuflih

Abstract:

The Occupational Safety and Health Management System in one of the largest Saudi companies has been experiencing in the last 10 years extensive direct and indirect expenses due to lack of proactive leading indicators and safety leadership effective procedures. And since there are no studies that are associated with this department of safety in the company, this research has been conducted. In this study we used a mixed method approach containing a literature review and experts input, then a qualitative questionnaire provided by Institute for Work and Health related to determining the company’s occupational safety and health management system level out from three levels (Compliance - Improvement - Continuous Learning) and the output regarding the company’s level was in Continuous Learning. After that Deming cycle was employed to create a set of proactive leading indicators and analyzed using the SMART method to make sure of its effectiveness and suitability to the company. The objective of this research is to provide a set of proactive indicators to contribute in making an efficient occupational safety and health management system that has less accidents which results in less expenses. Therefore, we provided the company with a prototype of an APP, designed and empowered with our final results to contribute in supporting decisions making processes.

Keywords: proactive leading indicators, OSH MS, safety leadership, accidents reduction

Procedia PDF Downloads 63
2911 Transformer Fault Diagnostic Predicting Model Using Support Vector Machine with Gradient Decent Optimization

Authors: R. O. Osaseri, A. R. Usiobaifo

Abstract:

The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

Procedia PDF Downloads 304
2910 Design, Analysis and Construction of a 250vac 8amps Arc Welding Machine

Authors: Anthony Okechukwu Ifediniru, Austin Ikechukwu Gbasouzor, Isidore Uche Uju

Abstract:

This article is centered on the design, analysis, construction, and test of a locally made arc welding machine that operates on 250vac with 8 amp output taps ranging from 60vac to 250vac at a fixed frequency, which is of benefit to urban areas; while considering its cost-effectiveness, strength, portability, and mobility. The welding machine uses a power supply to create an electric arc between an electrode and the metal at the welding point. A current selector coil needed for current selection is connected to the primary winding. Electric power is supplied to the primary winding of its transformer and is transferred to the secondary winding by induction. The voltage and current output of the secondary winding are connected to the output terminal, which is used to carry out welding work. The output current of the machine ranges from 110amps for low current welding to 250amps for high current welding. The machine uses a step-down transformer configuration for stepping down the voltage in order to obtain a high current level for effective welding. The welder can adjust the output current within a certain range. This allows the welder to properly set the output current for the type of welding that is being performed. The constructed arc welding machine was tested by connecting the work piece to it. Since there was no shock or spark from the transformer’s laminated core and was successfully used to join metals, it confirmed and validated the design.

Keywords: AC current, arc welding machine, DC current, transformer, welds

Procedia PDF Downloads 162
2909 Fault-Tolerant Predictive Control for Polytopic LPV Systems Subject to Sensor Faults

Authors: Sofiane Bououden, Ilyes Boulkaibet

Abstract:

In this paper, a robust fault-tolerant predictive control (FTPC) strategy is proposed for systems with linear parameter varying (LPV) models and input constraints subject to sensor faults. Generally, virtual observers are used for improving the observation precision and reduce the impacts of sensor faults and uncertainties in the system. However, this type of observer lacks certain system measurements which substantially reduce its accuracy. To deal with this issue, a real observer is then designed based on the virtual observer, and consequently a real observer-based robust predictive control is designed for polytopic LPV systems. Moreover, the proposed observer can entirely assure that all system states and sensor faults are estimated. As a result, and based on both observers, a robust fault-tolerant predictive control is then established via the Lyapunov method where sufficient conditions are proposed, for stability analysis and control purposes, in linear matrix inequalities (LMIs) form. Finally, simulation results are given to show the effectiveness of the proposed approach.

Keywords: linear parameter varying systems, fault-tolerant predictive control, observer-based control, sensor faults, input constraints, linear matrix inequalities

Procedia PDF Downloads 189
2908 Novel Adaptive Radial Basis Function Neural Networks Based Approach for Short-Term Load Forecasting of Jordanian Power Grid

Authors: Eyad Almaita

Abstract:

In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

Procedia PDF Downloads 328
2907 Design and Development of Herbal Formulations: Challenges and Solutions

Authors: B. Sathyanarayana

Abstract:

As per the report of World Health Organization, more than 80% of world population uses medicines made from herbal and natural materials. They have stood the test of time for their safety, efficacy, cultural acceptability and lesser side effects. Quality assurance and control measures, such as national quality specification and standards for herbal materials, good manufacturing practices (GMP) for herbal medicines, labelling, and licensing schemes for manufacturing, imports and marketing, should be in place in every country where herbal medicines are regulated. These measures are vital for ensuring the safety and efficacy of herbal medicines. In the case of herbal products challenge begins at the stage of designing itself except the classical products. Selection of herbal ingredients, officinal parts to be used, proportions are vital. Once the formulation is designed one should take utmost care to produce the standardized product of assured quality and safety. Quality control measures should cover the validation of quality and identity of raw materials, in process control (as per SOP and GMP norms) and at the level of final product. Quality testing, safety and efficacy studies of the final product are required to ensure the safe and effective use of the herbal products in human beings. Medicinal plants being the materials of natural resource are subjected to great variation making it really difficult to fix quality standards especially in the case of polyherbal preparations. Manufacturing also needs modification according to the type of ingredients present. Hence, it becomes essential to develop Standard operative Procedure for a specific herbal product. Present paper throws a light on the challenges that are encountered during the design and development of herbal products.

Keywords: herbal product, challenges, quality, safety, efficacy

Procedia PDF Downloads 486
2906 The Relationship among Perceived Risk, Product Knowledge, Brand Image and the Insurance Purchase Intention of Taiwanese Working Holiday Youths

Authors: Wan-Ling Chang, Hsiu-Ju Huang, Jui-Hsiu Chang

Abstract:

In 2004, the Ministry of Foreign Affairs Taiwan launched ‘An Arrangement on Working Holiday Scheme’ with 15 countries including New Zealand, Japan, Canada, Germany, South Korea, Britain, Australia and others. The aim of the scheme is to allow young people to work and study English or other foreign languages. Each year, there are 30,000 Taiwanese youths applied for participating in the working holiday schemes. However, frequent accidents could cause huge medical expenses and post-delivery fee, which are usually unaffordable for most families. Therefore, this study explored the relationship among perceived risk toward working holiday, insurance product knowledge, brand image and insurance purchase intention for Taiwanese youths who plan to apply for working holiday. A survey questionnaire was distributed for data collection. A total of 316 questionnaires were collected for data analyzed. Data were analyzed using descriptive statistics, independent samples T-test, one-way ANOVA, correlation analysis, regression analysis and hierarchical regression methods of analysis and hypothesis testing. The results of this research indicate that perceived risk has a negative influence on insurance purchase intention. On the opposite, product knowledge has brand image has a positive influence on the insurance purchase intention. According to the mentioned results, practical implications were further addressed for insurance companies when developing a future marketing plan.

Keywords: insurance product knowledges, insurance purchase intention, perceived risk, working holiday

Procedia PDF Downloads 238
2905 DLtrace: Toward Understanding and Testing Deep Learning Information Flow in Deep Learning-Based Android Apps

Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

Abstract:

With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

Procedia PDF Downloads 146
2904 The Impact of Surface Roughness and PTFE/TiF3/FeF3 Additives in Plain ZDDP Oil on the Friction and Wear Behavior Using Thermal and Tribological Analysis under Extreme Pressure Condition

Authors: Gabi N. Nehme, Saeed Ghalambor

Abstract:

The use of titanium fluoride and iron fluoride (TiF3/FeF3) catalysts in combination with polutetrafluoroethylene (PTFE) in plain zinc dialkyldithiophosphate (ZDDP) oil is important for the study of engine tribocomponents and is increasingly a strategy to improve the formation of tribofilm and to provide low friction and excellent wear protection in reduced phosphorus plain ZDDP oil. The influence of surface roughness and the concentration of TiF3/FeF3/PTFE were investigated using bearing steel samples dipped in lubricant solution @100°C for two different heating time durations. This paper addresses the effects of water drop contact angle using different surface finishes after treating them with different lubricant combination. The calculated water drop contact angles were analyzed using Design of Experiment software (DOE) and it was determined that a 0.05 μm Ra surface roughness would provide an excellent TiF3/FeF3/PTFE coating for antiwear resistance as reflected in the scanning electron microscopy (SEM) images and the tribological testing under extreme pressure conditions. Both friction and wear performance depend greatly on the PTFE/and catalysts in plain ZDDP oil with 0.05% phosphorous and on the surface finish of bearing steel. The friction and wear reducing effects, which was observed in the tribological tests, indicated a better micro lubrication effect of the 0.05 μm Ra surface roughness treated at 100°C for 24 hours when compared to the 0.1 μm Ra surface roughness with the same treatment.

Keywords: scanning electron microscopy, ZDDP, catalysts, PTFE, friction, wear

Procedia PDF Downloads 340
2903 Juvenile Justice in Maryland: The Evidence Based Approach to Youth with History of Victimization and Trauma

Authors: Gabriela Wasileski, Debra L. Stanley

Abstract:

Maryland efforts to decrease the juvenile criminality and recidivism shifts towards evidence based sentencing. While in theory the evidence based sentencing has an impact on the reduction of juvenile delinquency and drug abuse; the assessment of juveniles’ risk and needs usually lacks crucial information about juvenile’s prior victimization. The Maryland Comprehensive Assessment and Service Planning (MCASP) Initiative is the primary tool for developing and delivering a treatment service plan for juveniles at risk. Even though it consists of evidence-based screening and assessment instruments very little is currently known regarding the effectiveness and the impact of the assessment in general. In keeping with Maryland’s priority to develop successful evidence-based recidivism reduction programs, this study examined results of assessments based on MCASP using a representative sample of the juveniles at risk and their assessment results. Specifically, it examined: (1) the results of the assessments in an electronic database (2) areas of need that are more frequent among delinquent youth in a system/agency, (3) the overall progress of youth in an agency’s care (4) the impact of child victimization and trauma experiences reported in the assessment. The project will identify challenges regarding the use of MCASP in Maryland, and will provide a knowledge base to support future research and practices.

Keywords: Juvenile Justice, assessment of risk and need, victimization and crime, recidivism

Procedia PDF Downloads 301