Search results for: sterile insect technique

Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

Procedia PDF Downloads 296

Authors: Nermin Mahmoud Gohar, Aisha Tarek Noour

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Learner satisfaction has been a vital field of interest in the literature. Accordingly, the paper will explore the reasons behind individual differences in motivation and satisfaction. This study examines the effect of both; Herzberg’s and Maslow’s theories on learners satisfaction. A self-administered questionnaire was used to collect data from learners who were geographically widely spread around the College of Maritime Transport and Technology (CMTT) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. One hundred and fifty undergraduates responded to a questionnaire survey. Respondents were drawn from two branches in Alexandria and Port Said. The data analysis used was SPSS 22 and AMOS 18. Factor analysis technique was used to find out the dimensions under study verified by Herzberg’s and Maslow’s theories. In addition, regression analysis and structural equation modeling were applied to find the effect of the above-mentioned theories on maritime transport learners’ satisfaction. Concerning the limitation of this study, it used the available number of learners in the CMTT due to the relatively low population in this field.

Keywords: motivation, satisfaction, needs, education, Herzberg’s and Maslow’s theories

Procedia PDF Downloads 435

Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

Procedia PDF Downloads 386

Authors: M. Aruna

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Emphasis on the advancement of new materials and technology has been there for the past few decades. The global development towards using cheap and durable materials from renewable resources contributes to sustainable development. An experimental investigation of mechanical behaviour of sisal fiber-reinforced concrete is reported for making a suitable building material in terms of reinforcement. Fibre reinforced composite is one such material, which has reformed the concept of high strength. Sisal fibres are abundantly available in the hot areas. The sisal fiber has emerged as a reinforcing material for concretes, used in civil structures. In this work, properties such as hardness and tensile strength of sisal fibre reinforced cement composites with 6, 12, 18, and 24% by weight of sisal fibres were assessed. Sisal fiber reinforced cement composite slabs with long sisal fibers were manufactured using a cast hand layup technique. Mechanical response was measured under tension. The high energy absorption capacity of the developed composite system was reflected in high toughness values under tension respectively.

Keywords: sisal fibre, fiber-reinforced concrete, mechanical behaviour, composite materials

Procedia PDF Downloads 260

Authors: A. A. Salisu, M. Y. Yakasai, K. M. Aujara

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Sisal leaves were subjected to enzymatic retting method to extract the sisal fibre. A portion of the fibre was pretreated with alkali (NaOH), and further treated with benzoyl chloride and silane treatment reagents. Both the treated and untreated Sisal fibre composites were used to fabricate the composite by hand lay-up technique using unsaturated polyester resin. Tensile, flexural, water absorption, density, thickness swelling and chemical resistant tests were conducted and evaluated on the composites. Results obtained for all the parameters showed an increase in the treated fibre compared to untreated fibre. FT-IR spectra results ascertained the inclusion of benzoyl and silane groups on the fibre surface. Scanning electron microscopy (SEM) result obtained showed variation in the morphology of the treated and untreated fibre. Chemical modification was found to improve adhesion of the fibre to the matrix, as well as physico-mechanical properties of the composites.

Keywords: chemical resistance, density test, polymer matrix sisal fibre, thickness swelling

Procedia PDF Downloads 436

Authors: A. Hemmati, H. Mirsaeedghazi, M. Aboonajmi

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Carrot juice is one of the most nutritious foods that are consumed around the world. Large particles in carrot juice causing turbid appearance make some problems in the concentration process such as off-flavor due to the large particles burnt on the walls of evaporators. Microfiltration (MF) is a pressure driven membrane separation method that can clarify fruit juices without enzymatic treatment. Fouling is the main problem in the membrane process causing reduction of permeate flux. Ultrasound as a cleaning technique was applied at 20 kHz to reduce fouling in membrane clarification of carrot juice using dead-end MF system with polyvinylidene fluoride (PVDF) membrane. Results showed that application of ultrasound waves reduce diphasic characteristic of carrot juice and permeate flux increased. Evaluation of different membrane fouling mechanisms showed that application of ultrasound waves changed creation time of each fouling mechanism. Also, its behavior was changed with varying transmembrane pressure.

Keywords: Carrot juice, Dead end, Microfiltration, Ultrasound

Procedia PDF Downloads 319

Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

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This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

Procedia PDF Downloads 324

Authors: Murtala Sale

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The use of instructional materials is an indispensable tool that enhances qualitative teaching and learning especially at the primary level. Instructional materials are used to facilitate comprehension of ideas in the learners as well as ensure long term retention of ideas and topics taught to pupils. This study examined the relevance of using instructional materials in primary schools in Katsina State, Nigeria. It employed survey design using cluster sampling technique. The questionnaire was used to gather data for analysis, and statistical and frequency tables were used to analyze the data gathered. The results show that teachers and students alike have realized the effectiveness of modern instructional materials in teaching and learning for the attainment of set objectives in the basic primary education policy. It also discovered that reluctance in the use of instructional materials will hamper the achievement of qualitative primary education. The study therefore suggests that there should be the provision of adequate and up-to-date instructional materials to all primary schools in Katsina State for effective teaching and learning process.

Keywords: instructional materials, effective teaching, learning quality, indispensable aspect

Procedia PDF Downloads 252

Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

Procedia PDF Downloads 341

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

Procedia PDF Downloads 339

Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

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The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

Procedia PDF Downloads 288

Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Lakshminarayanan, Vijayaraghavan, Krishnamurthy

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The ever-increasing demand for high efficiency in automotive and aerospace applications requires new materials to suit to high temperature applications. The Ceramic Matrix Composites nowadays find its applications for high strength and high temperature environments. In this paper, Al2O3 and Sic ceramic materials are taken in particulate form as matrix and reinforcement respectively. They are blended together in Ball Milling and compacted in Cold Compaction Machine by powder metallurgy technique. Scanning Electron Microscope images are taken for the samples in order to find out proper blending of powders. Micro harness testing is also carried out for the samples in Vickers Micro Hardness Testing Equipment. Surface grinding of the samples is also carried out in Surface Grinding Machine in order to find out grinding force estimates. The surface roughness of the grounded samples is also taken in Surface Profilometer. These are yielding promising results.

Keywords: ceramic matrix composite, cold compaction, material characterization, particulate and surface grinding

Procedia PDF Downloads 242

Authors: R. Ziaie Moayed, A. Mahigir

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Stone column technique has been successfully employed to improve the load-settlement characteristics of foundations. A series of finite element numerical analyses of harmonic dynamic loading have been conducted on strengthened raft footing to study the effects of single and group stone columns on settlement of circular footings. The settlement of circular raft footing that improved by single and group of stone columns are studied under harmonic dynamic loading. This loading is caused by heavy machinery foundations. A detailed numerical investigation on behavior of single column and group of stone columns is carried out by varying parameters like weight of machinery, loading frequency and period. The result implies that presence of single and group of stone columns enhanced dynamic behavior of the footing so that the maximum and residual settlement of footing significantly decreased. 

Keywords: finite element analysis, harmonic loading, settlement, stone column

Procedia PDF Downloads 371

Authors: Wojciech Kulesza

Abstract:

The north-western part of the Poland, specifically West Pomerania and Lubuskie provinces, from several years are the subject of research of the Department of Archaeology of Early Middle Ages of Institute of Archaeology of Nicolaus Copernicus University in Toruń. This area has a dense network of rivers and numerous lakes, where many of them are connected to the southern part of the Baltic Sea. During the many years of research in this area, archaeologists discovered the remains of the early Middle Ages settlement located on several islands and in most cases were encountered relics of early Middle Ages bridges linking those islands with the mainland. During the excavation, work was carried out both under water and on land for the accurate identification of islands and adjacent to them underwater areas. The result of this work is a graphic documentation, made in a three-dimensional technique, not only for the underwater trenches but also relics of bridges and objects discovered during exploration, which as the main theme will be presented in the full presentation.

Keywords: Poland, underwater archaeology, Nicolaus Copernicus University, early middle ages

Procedia PDF Downloads 245

Authors: M. Saadi, S. E. H. Abaidia, M. Y. Mokeddem.

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We present the results of a systematic and comparative study of the bulk, the structural properties, and phonon calculations of aluminum alloys using several exchange–correlations functional theory (DFT) with different plane-wave basis pseudo potential techniques. Density functional theory implemented by the Vienna Ab Initio Simulation Package (VASP) technique is applied to calculate the bulk and the structural properties of several structures. The calculations were performed for within several exchange–correlation functional and pseudo pententials available in this code (local density approximation (LDA), generalized gradient approximation (GGA), projector augmented wave (PAW)). The lattice dynamic code “PHON” developed by Dario Alfè was used to calculate some thermodynamics properties and phonon dispersion relation frequency distribution of Aluminium alloys using the VASP LDA PAW and GGA PAW results. The bulk and structural properties of the calculated structures were compared to different experimental and calculated works.

Keywords: DFT, exchange-correlation functional, LDA, GGA, pseudopotential, PAW, VASP, PHON, phonon dispersion

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Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

Procedia PDF Downloads 162

Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

Procedia PDF Downloads 332

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

Procedia PDF Downloads 129

Authors: A. Chateauneuf, M. Mostoufi, D. Vyncke

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Monte Carlo (MC) simulation is a technique that provides approximate solutions to a broad range of mathematical problems. A drawback of the method is its high computational cost, especially in a high-dimensional setting, such as estimating the Tail Value-at-Risk for large portfolios or pricing basket options and Asian options. For these types of problems, one can construct an upper bound in the convex order by replacing the copula by the comonotonic copula. This comonotonic upper bound can be computed very quickly, but it gives only a rough approximation. In this paper we introduce the Comonotonic Monte Carlo (CoMC) simulation, by using the comonotonic approximation as a control variate. The CoMC is of broad applicability and numerical results show a remarkable speed improvement. We illustrate the method for estimating Tail Value-at-Risk and pricing basket options and Asian options when the logreturns follow a Black-Scholes model or a variance gamma model.

Keywords: control variate Monte Carlo, comonotonicity, option pricing, scientific computing

Procedia PDF Downloads 515

Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

Procedia PDF Downloads 307

Authors: Shahbaz Pervez, Aljawharah Almuhana, Zahida Parveen, Samina Naz, Hira Tariq, Seyed Hosseini, Muhammad Awais Azam

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With the latest development in the field of cutting-edge technologies, there is a rapid increase in the use of technology-oriented gadgets. In a recent scenario of the tech era, there is increasing demand to fulfill our day-to-day routine tasks with the help of technological gadgets. We are living in an era of technology where trends have been changing, and a race to introduce a new technology gadget has already begun. Smart cities are getting more popular with every passing day; city councils and governments are under enormous pressure to provide the latest services for their citizens and equip them with all the latest facilities. Thus, ultimately, they are going more into smart cities infrastructure building, providing services to their inhabitants with a single click from their smart devices. This trend is very exciting, but on the other hand, if some incident of security breach happens due to any weaker link, the results would be catastrophic. This paper addresses potential security and privacy breaches with a possible solution by using Blockchain technology in IoT enabled environment.

Keywords: blockchain, cybersecurity, DDOS, intrusion detection, IoT, RFID, smart devices security, smart services

Procedia PDF Downloads 119

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

Procedia PDF Downloads 150

Authors: Mahla Azimi

Abstract:

Introduction: Post-bladder catheter infection is a common and significant healthcare-associated infection that affects individuals with indwelling urinary catheters. These infections can lead to various complications, including urinary tract infections (UTIs), bacteremia, sepsis, and increased morbidity and mortality rates. This article aims to provide a comprehensive review of post-bladder catheter infections, including their causes, risk factors, clinical presentation, diagnosis, treatment options, and preventive measures. Causes and Risk Factors: Post-bladder catheter infections primarily occur due to the colonization of microorganisms on the surface of the urinary catheter. The most common pathogens involved are Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterococcus species. Several risk factors contribute to the development of these infections, such as prolonged catheterization duration, improper insertion technique, poor hygiene practices during catheter care, compromised immune system function in patients with underlying conditions or immunosuppressive therapy. Clinical Presentation: Patients with post-bladder catheter infections may present with symptoms such as fever, chills, malaise, suprapubic pain or tenderness, and cloudy or foul-smelling urine. In severe cases or when left untreated for an extended period of time, patients may develop more severe symptoms like hematuria or signs of systemic infection. Diagnosis: The diagnosis of post-bladder catheter infection involves a combination of clinical evaluation and laboratory investigations. Urinalysis is crucial in identifying pyuria (presence of white blood cells) and bacteriuria (presence of bacteria). A urine culture is performed to identify the causative organism(s) and determine its antibiotic susceptibility profile. Treatment Options: Prompt initiation of appropriate antibiotic therapy is essential in managing post-bladder catheter infections. Empirical treatment should cover common pathogens until culture results are available. The choice of antibiotics should be guided by local antibiogram data to ensure optimal therapy. In some cases, catheter removal may be necessary, especially if the infection is recurrent or associated with severe complications. Preventive Measures: Prevention plays a vital role in reducing the incidence of post-bladder catheter infections. Strategies include proper hand hygiene, aseptic technique during catheter insertion and care, regular catheter maintenance, and timely removal of unnecessary catheters. Healthcare professionals should also promote patient education regarding self-care practices and signs of infection. Conclusion: Post-bladder catheter infections are a significant healthcare concern that can lead to severe complications and increased healthcare costs. Early recognition, appropriate diagnosis, and prompt treatment are crucial in managing these infections effectively. Implementing preventive measures can significantly reduce the incidence of post-bladder catheter infections and improve patient outcomes. Further research is needed to explore novel strategies for prevention and management in this field.

Keywords: post-bladder catheter infection, urinary tract infection, bacteriuria, indwelling urinary catheters, prevention

Procedia PDF Downloads 81

Authors: S. U. Durgadsimi, S. Chouguleb, S. Belladc

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(y) Li0.5Ni0.7Zn0.05Fe2O4 + (1-y) Ba0.5Sr0.5TiO3 magnetoelectric composites with y = 0.1, 0.3 and 0.5 were prepared by a conventional standard double sintering ceramic technique. X-ray diffraction analysis confirmed the phase formation of ferrite, ferroelectric and their composites. logρdc Vs 1/T graphs reveal that the dc resistivity decreases with increasing temperature exhibiting semiconductor behavior. The plots of logσac Vs logω2 are almost linear indicating that the conductivity increases with increase in frequency i.e, conductivity in the composites is due to small polaron hopping. Dielectric constant (έ) and dielectric loss (tan δ) were studied as a function of frequency in the range 100Hz–1MHz which reveals the normal dielectric behavior except the composite with y=0.1 and as a function of temperature at four fixed frequencies (i.e. 100Hz, 1KHz, 10KHz, 100KHz). ME voltage coefficient decreases with increase in ferrite content and was observed to be maximum of about 7.495 mV/cmOe for (0.1) Li0.5Ni0.7Zn0.05Fe2O4 + (0.9) Ba0.5Sr0.5TiO3 composite.

Keywords: XRD, dielectric constant, dielectric loss, DC and AC conductivity, ME voltage coefficient

Procedia PDF Downloads 344

Authors: Jiya Mohammed, Tsadu Shuaib, Yusuf Abdulhakeem

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The research work focuses on the cases of MHD boundary layer flow past a stretching plate with heat transfer and viscous dissipation. The non-linear of momentum and energy equation are transform into ordinary differential equation by using similarity transformation, the resulting equation are solved using Adomian Decomposition Method (ADM). An attempt has been made to show the potentials and wide range application of the Adomian decomposition method in the comparison with the previous one in solving heat transfer problems. The Pade approximates value (η= 11[11, 11]) is use on the difficulty at infinity. The results are compared by numerical technique method. A vivid conclusion can be drawn from the results that ADM provides highly precise numerical solution for non-linear differential equations. The result where accurate especially for η ≤ 4, a general equating terms of Eckert number (Ec), Prandtl number (Pr) and magnetic parameter ( ) is derived which was used to investigate velocity and temperature profiles in boundary layer.

Keywords: MHD, Adomian decomposition, boundary layer, viscous dissipation

Procedia PDF Downloads 551

Authors: Yassir Mahmood, Nadia Ehsan

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In current research stream, empirical work regarding knowledge and motivation management along their dimensions is sparse. This study partially filled this void by investigating the influence of knowledge management (tacit and explicit) and motivation management (intrinsic and extrinsic) on firm performance with the mediating effects of innovative performance. Based on the quantitative research method, data were collected through questionnaire from 284 employees working in 18 different firms across the citrus industry located in Sargodha region (Pakistan). The proposed relationships were tested through regression analysis while mediation relations were analyzed through Barron and Kenny (1986) technique. The results suggested that knowledge management (KM) and motivation management (MM) have significant positive impacts on innovative performance (IP). In addition, the role of IP as full mediator between KM and firm performance (FP) is confirmed. Also, IP proved to be a partial mediator between MM and FP. From the managerial perspective, the findings of the study are vital as some of the important constituents of FP have been highlighted. The study produced important underpinnings for managers. In last, implications for policymakers along with future research directions are discussed.

Keywords: innovative performance, firm performance, knowledge management, motivation management, Sargodha

Procedia PDF Downloads 161

Authors: A. A. Adekunle, A. M. Omoare, W. O. Oyediran

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This study was carried out to assess rural women’s skill acquisition in the processing of locust bean in Ipokia Local Government Area of Ogun State, Nigeria. Simple random sampling technique was used to select 90 women locust bean processors for this study. Data were analyzed with descriptive statistics and Pearson Product Moment Correlation. The result showed that the mean age of respondents was 40.72 years. Most (70.00%) of the respondents were married. The mean processing experience was 8.63 years. 93.30% of the respondents relied on information from fellow locust beans processors and friends. All (100%) the respondents did not acquire improved processing skill through trainings and workshops. It can be concluded that the rural women’s skill acquisition on modernized processing techniques was generally low. It is hereby recommend that the rural women processors should be trained by extension service providers through series of workshops and seminars on improved processing techniques.

Keywords: locust bean, processing, skill acquisition, rural women

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Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

Abstract:

Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

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Authors: Jaibir Sharma, Lee JaeWung, Merugu Srinivas, Navab Singh

Abstract:

This paper presents thermal annealing dewetting technique for the preparation of porous metal membrane for thin film encapsulation application. Thermal annealing dewetting experimental results reveal that pore size in porous metal membrane depend upon i.e. 1. The substrate on which metal is deposited for formation of porous metal cap membrane, 2. Melting point of metal used for porous metal cap layer membrane formation, 3. Thickness of metal used for cap layer, 4. Temperature used for porous metal membrane formation. Silver (Ag) was used as a metal for preparation of porous metal membrane by annealing the film at different temperature. Pores in porous silver film were analyzed using Scanning Electron Microscope (SEM). In order to check the usefulness of porous metal film for thin film encapsulation application, the porous silver film prepared on amorphous silicon (a-Si) was release using XeF2. Finally, guide line and structures are suggested to use this porous membrane for thin film encapsulation (TFE) application.

Keywords: dewetting, themal annealing, metal, melting point, porous

Procedia PDF Downloads 658