Search results for: permittivity measurement techniques
5651 Motion Planning and Posture Control of the General 3-Trailer System
Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai
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This paper presents a set of artificial potential field functions that improves upon; in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general 3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.Keywords: artificial potential fields, 3-trailer systems, motion planning, posture
Procedia PDF Downloads 4315650 MIM and Experimental Studies of the Thermal Drift in an Ultra-High Precision Instrument for Dimensional Metrology
Authors: Kamélia Bouderbala, Hichem Nouira, Etienne Videcoq, Manuel Girault, Daniel Petit
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Thermal drifts caused by the power dissipated by the mechanical guiding systems constitute the main limit to enhance the accuracy of an ultra-high precision cylindricity measuring machine. For this reason, a high precision compact prototype has been designed to simulate the behaviour of the instrument. It ensures in situ calibration of four capacitive displacement probes by comparison with four laser interferometers. The set-up includes three heating wires for simulating the powers dissipated by the mechanical guiding systems, four additional heating wires located between each laser interferometer head and its respective holder, 19 Platinum resistance thermometers (Pt100) to observe the temperature evolution inside the set-up and four Pt100 sensors to monitor the ambient temperature. Both a Reduced Model (RM), based on the Modal Identification Method (MIM) was developed and optimized by comparison with the experimental results. Thereafter, time dependent tests were performed under several conditions to measure the temperature variation at 19 fixed positions in the system and compared to the calculated RM results. The RM results show good agreement with experiment and reproduce as well the temperature variations, revealing the importance of the RM proposed for the evaluation of the thermal behaviour of the system.Keywords: modal identification method (MIM), thermal behavior and drift, dimensional metrology, measurement
Procedia PDF Downloads 4005649 Ionic Liquid Effects on Metal Ion-Based Extractions of Olefin/Paraffin Hydrocarbon
Authors: Ellen M. Lukasik
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In coordination and support of the Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR) Research Experience for Teachers (RET) at the University of Texas at Austin and under the guidance and direction of Professor Joan Brennecke, this study examined the addition of silver in an ionic liquid used to separate cyclohexane from cyclohexene. We recreated the liquid-liquid separation experimental results from the literature on cyclohexene, cyclohexane, and [allylmim][Tf2N] to verify our method, then evaluated the separation performance of silver - ionic liquid (IL) mixtures by various characterization techniques. To introduce the concepts of this research in high school education, a lesson plan was developed to instruct students on the principles of liquid-liquid separation.Keywords: ionic liquids, liquid-liquid separation, hydrocarbon, research experience for teachers
Procedia PDF Downloads 1095648 Parallel Computing: Offloading Matrix Multiplication to GPU
Authors: Bharath R., Tharun Sai N., Bhuvan G.
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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks
Procedia PDF Downloads 635647 Towards a Conscious Design in AI by Overcoming Dark Patterns
Authors: Ayse Arslan
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One of the important elements underpinning a conscious design is the degree of toxicity in communication. This study explores the mechanisms and strategies for identifying toxic content by avoiding dark patterns. Given the breadth of hate and harassment attacks, this study explores a threat model and taxonomy to assist in reasoning about strategies for detection, prevention, mitigation, and recovery. In addition to identifying some relevant techniques such as nudges, automatic detection, or human-ranking, the study suggests the use of major metrics such as the overhead and friction of solutions on platforms and users or balancing false positives (e.g., incorrectly penalizing legitimate users) against false negatives (e.g., users exposed to hate and harassment) to maintain a conscious design towards fairness.Keywords: AI, ML, algorithms, policy, system design
Procedia PDF Downloads 1245646 Effects of Surface Insulation of Silicone Rubber Composites in HVDC
Authors: Min-Hae Park, Ju-Na Hwang, Cheong-won Seo, Ji-Ho Kim, Kee-Joe Lim
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Polymeric insulators are high hardness, corrosion resistant, lightweight and also good dielectric strength in electric equipment. For such reasons, the amount of polymeric insulators is increased consistently abroad. The current outdoor insulators are replaced by polymeric insulators. Silicone rubber of polymeric insulators is widely used in insulation materials for outdoor application since it has excellent electrical characteristics and high surface hydrophobic. However, it can be evade exposure to pollutant on surface using at outdoor. It also improve the pollution for dust and smoke due to the large are increasing, because most of the industrial area in which the electric power loads are concentrated are located at the coastal area with salt attack. Thus it is important to detect the main cause of the deterioration for outdoor insulation materials. But there has no standards for valuation to apply reliably and determine accurately deterioration under DC, still lacks DC characteristic researches in proportion to AC. In addition, a lot of ATH was added to improve tracking resistivity of silicone rubber, although the problem has been brought up about falling sharply mechanical properties. Therefore, we might compare surface resistivities of silicone rubber compounding of three kinds of filler. In this paper, specimens of silicone rubber composite usable as outdoor insulators were prepared. Micro-silica (SiO2), nano- alumina (Al2O3) and nano-ATH (Al(OH)3) were used in additives. The study aims to investigate properties of DC surface insulation on silicone rubber composite which were filled with various fillers from surface resistivity measurement and salt-fog test.Keywords: composite, silicone rubber, surface insulation, HVDC
Procedia PDF Downloads 4095645 Synthesis, Characterization and Antibacterial Activity of Metalloporphyrins: Role of Central Metal Ion
Authors: Belete B. Beyene, Ayenew M. Mihirteu, Misganaw T. Ayana, Amogne W. Yibeltal
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Modification of synthetic porphyrins is one of the promising strategies in an attempt to get molecules with desired properties and applications. Here in, we report synthesis, photophysical characterization and antibacterial activity of 5, 10, 15, 20-tetrakis-(4- methoxy carbonyl phenyl) porphyrin M(II); where M = Co, Fe, Ni, Zn. Metallation of the ligand was confirmed by using UV–Vis spectroscopy and ESI-Ms measurement, in which the number of Q bands in absorption spectra of the ligand decreased from four to one or two as a result of metal insertion to the porphyrin core. The antibacterial activity study of the complexes toward two Gram-positive (Staphylococcus aureus (S. aureus) and Streptococcus pyogenes (s. pyogenes)) and two Gram-negative (Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae)) bacteria by disc diffusion method showed a promising inhibitory activity. The complexes exhibited highest activities at highest concentration and were better than the activity of free base ligand, the salts, and blank solution. This could be explained on the basis of Overton's concept of cell permeability and Tweed's Chelation theory. An increased lipo-solubility enhances the penetration of the complexes into the lipid membrane and interferes with the normal activities of the bacteria. Our study, therefore, showed that the growth inhibitory effect of these metalloporphyrins is generally in order of ZnTPPCOOMe > NiTPPCOOMe > CoTPPCOOMe> FeTPPCOOMe, which may be attributed to the better lipophilicity and binding of the complex with the cellular components.Keywords: porphyrins, metalloporphyrins, spectral property, antibacterial activity, synthesis
Procedia PDF Downloads 795644 Ceramic Employees’ Occupational Health and Safety Training Expectations in Turkey
Authors: Erol Karaca
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This study aims to analyze ceramic employees’ occupational health and safety training expectations. To that general objective, the study tries to examine whether occupational health and safety training expectations of ceramic employees meaningfully differentiate depending on demographic features and professional, social and economic conditions. For this purpose, the research data was collected through “Questionnaire of Occupational Health and Safety Training Expectation” (QSOHSTE) consisting of 25 open and close-ended questions developed by the researcher on the base of the literature review. QSOHSTE was applied to 125 ceramic employees working in Kutahya, Turkey. Data obtained from questionnaires were analyzed via SPSS 21. The findings, obtained from the study, revealed that employees’ agreement level to occupational health and safety training expectation statements is generally high-level. These findings also reveals that employees have various expectations about occupational health and safety training. These expectations are increasing sensitivity towards occupational health and safety training about the prevention of occupational accidents and diseases, contributing occupational health and safety training in establishing healthy and safe working environment, requiring occupational health and safety training before starting work, in case of changing working equipment and new technological applications, necessity of measurement and evaluation after occupational health and safety training. Besides these findings, employees’ agreement level to occupational health and safety training expectation statements also varies in terms of educational level, professional seniority, income level and perception of economic condition.Keywords: occupational health and safety, occupational training, occupational expectation, professional seniority
Procedia PDF Downloads 4535643 Detect QOS Attacks Using Machine Learning Algorithm
Authors: Christodoulou Christos, Politis Anastasios
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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping
Procedia PDF Downloads 655642 Overview and Future Opportunities of Sarcasm Detection on Social Media Communications
Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef
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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis
Procedia PDF Downloads 4595641 Correlation between Clinical Measurements of Static Foot Posture in Young Adults
Authors: Phornchanok Motantasut, Torkamol Hunsawong, Lugkana Mato, Wanida Donpunha
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Identifying abnormal foot posture is important for prescribing appropriate management in patients with lower limb disorders and chronic non-specific low back pain. The normalized navicular height truncated (NNHt) and the foot posture index-6 (FPI-6) have been recommended as the common, simple, valid, and reliable static measures for clinical application. The NNHt is a single plane measure while the FPI-6 is a triple plane measure. At present, there is inadequate information about the correlation between the NNHt and the FPI-6 for categorizing foot posture that leads to a difficulty of choosing the appropriate assessment. Therefore, the present study aimed to determine the correlation between the NNHt and the FPI-6 measures in adult participants with asymptomatic feet. Methods: A cross-sectional descriptive study was conducted in 47 asymptomatic individuals (23 males and 24 females) aged 28.89 ± 7.67 years with body mass index 21.73 ± 1.76 kg/m². The right foot was measured twice by the experienced rater using the NNHt and the FPI-6. A sequence of the measures was randomly arranged for each participant with a 10-minute rest between the tests. The Pearson’s correlation coefficient (r) was used to determine the relationship between the measures. Results: The mean NNHt score was 0.23 ± 0.04 (ranged from 0.15 to 0.36) and the mean FPI-6 score was 4.42 ± 4.36 (ranged from -6 to +11). The Pearson’s correlation coefficient among the NNHt score and the FPI-6 score was -0.872 (p < 0.01). Conclusion: The present finding demonstrates the strong correlation between the NNHt and FPI-6 in adult feet and implies that both measures could be substituted for each other in identifying foot posture.Keywords: foot posture index, foot type, measurement of foot posture, navicular height
Procedia PDF Downloads 1415640 Beyond the Effect on Children: Investigation on the Longitudinal Effect of Parental Perfectionism on Child Maltreatment
Authors: Alice Schittek, Isabelle Roskam, Moira Mikolajczak
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Background: Perfectionistic strivings (PS) and perfectionistic concerns (PC) are associated with an increase in parental burnout (PB), and PB causally increases violence towards the offspring. Objective: To our best knowledge, no study has ever investigated whether perfectionism (PS and PC) predicts violence towards the offspring and whether PB could explain this link. We hypothesized that an increase in PS and PC would lead to an increase in violence via an increase in PB. Method: 228 participants responded to an online survey, with three measurement occasions spaced two months apart. Results: Contrary to expectations, cross-lagged path models revealed that violence towards the offspring prospectively predicts an increase in PS and PC. Mediation models showed that PB is not a significant mediator. The results of all models did not change when controlling for social desirability. Conclusion: The present study shows that violence towards the offspring increases the risk of PS and PC in parents, which highlights the importance of understanding the effect of child maltreatment on the whole family system and not just on children. Results are discussed in light of the feeling of guilt experienced by parents. Considering the insignificant mediation effect, PB research should slowly shift towards more (quasi) causal designs, allowing to identify which significant correlations translate into causal effects. Implications: Clinicians should focus on preventing child maltreatment as well as treating parental perfectionism. Researchers should unravel the effects of child maltreatment on the family system.Keywords: maltreatment, parental burnout, perfectionistic strivings, perfectionistic concerns, perfectionism, violence
Procedia PDF Downloads 765639 AI-Enabled Smart Contracts for Reliable Traceability in the Industry 4.0
Authors: Harris Niavis, Dimitra Politaki
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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.Keywords: blockchain, data quality, industry4.0, product quality
Procedia PDF Downloads 1945638 Improving the Quality of Staff Performance with a Talent-Driven Approach: Case Study of SAIPA Automotive Manufacturing Company in Iran
Authors: Abdolmajid Mosleh, Afzal Ghasimi
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The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company
Procedia PDF Downloads 945637 Optimizing and Evaluating Performance Quality Control of the Production Process of Disposable Essentials Using Approach Vague Goal Programming
Authors: Hadi Gholizadeh, Ali Tajdin
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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.Keywords: goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression
Procedia PDF Downloads 2285636 Automatic Aggregation and Embedding of Microservices for Optimized Deployments
Authors: Pablo Chico De Guzman, Cesar Sanchez
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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.Keywords: aggregation, deployment, embedding, resource allocation
Procedia PDF Downloads 2065635 Perceived Effect of Physical Exercise on Healthy Well-Being of Pregnant Women in Imo State
Authors: Roseline Chizoba Onuoha, Rose Ngozi Uzoka
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This study aimed at investigating perceived effect of physical exercise on healthy well-being of pregnant mothers in Imo state. The study was guided by three research questions and three null hypotheses tested at 0.05 level of significance. The study was a quasi-experimental non-equivalent control group design involving pre and post tests. A sample of 92 pregnant women drawn from a total population of 922 registered pregnant women in ten randomly selected health centers in Imo State through multistage sampling technique was used. A 41 item structured instrument titled Physical Exercise Pregnancy Test (PEPT) was used for the study. The PEPT was validated by three experts from measurement and evaluation, educational psychology and health education. Crombach Alpha method was used to determine the reliability of Physical Exercise Pregnancy Test (PEPT) and reliability index of 0.82 was obtained. Mean and standard deviation were used to answer the research questions; while Analysis of Covariance (ANCOVA) was used in analyzing the hypotheses. Findings of the study revealed that physical exercise affects physical, social and emotional wellbeing scores of pregnant women. The study also indicated that intervention using physical exercise significantly enhanced healthy well-being scores of pregnant mothers who were exposed to physical exercise than those who received conventional health talks; Location has no significant interaction effect on the mean well-being scores of pregnant women via PEPT. Among recommendations made were that pregnant women should participate in physical exercise.Keywords: educational psychology, Imo state, Physical exercise, pregnant women
Procedia PDF Downloads 1405634 Evaluation of a Mindfulness and Self-Care-Based Intervention for Teachers to Enhance Mental Health
Authors: T. Noichl, M. Cramer, G. E. Dlugosch, I. Hosenfeld
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Teachers are exposed to a variety of stresses in their work context. These can have a negative impact on physical and psychological well-being. The online training ‘Better Living! Self-care for teachers’ is based on the training ‘Better Living! Self-care for mental health professionals’, which has been proven to be effective over a period of 3 years. The training for teachers is being evaluated for its effectiveness between October 2021 and March 2023 in a study funded by the German Federal Ministry of Education and Research. The aim of the training is to promote self-care and mindfulness among participants and thereby to foster well-being. The concept of self-care was already mentioned in antiquity and was also named as an imperative by philosophers such as Socrates and Epictetus. In the absence of a universal understanding of self-care today, the following definition was developed within the research group: Self-care is 1) facing oneself in a loving and appreciative way, 2) taking one's own needs seriously, and 3) actively contributing to one's own well-being. The study is designed as a randomized wait-control group repeated-measures design with 4 (treatment group) resp. 6 (wait-control group) measurement points. Central dependent variables are self-care, mindfulness, stress, and well-being. To assess the long-term effectiveness of training participation, these constructs are surveyed at the beginning and the end of the training as well as five weeks and one year later. Based on the results of the evaluation with mental health professionals, it is expected that participation will lead to an increase in subjective well-being, self-care, and mindfulness. The first results of the evaluation study are presented and discussed with regard to the effectiveness of the training among teachers.Keywords: longitudinal intervention study, mindfulness, self-care, teachers’ mental health, well-being
Procedia PDF Downloads 1045633 Study of a Developed Model Describing a Vacuum Membrane Distillation Unit Coupled to Solar Energy
Authors: Fatma Khaled, Khaoula Hidouri, Bechir Chaouachi
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Desalination using solar energy coupled with membrane techniques such as vacuum membrane distillation (VMD) is considered as an interesting alternative for the production of pure water. During this work, a developed model of a polytetrafluoroethylene (PTFE) hollow fiber membrane module of a VMD unit of seawater was carried out. This simulation leads to establishing a comparison between the effects of two different equations of the vaporization latent heat on the membrane surface temperature and on the unit productivity. Besides, in order to study the effect of putting membrane modules in series on the outlet fluid temperature and on the productivity of the process, a simulation was executed.Keywords: vacuum membrane distillation, membrane module, membrane temperature, productivity
Procedia PDF Downloads 1975632 A Metacognitive Strategy to Improve Saudi EFL Learners’ Lecture Comprehension
Authors: Abdul Wahed Al Zumor
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Saudi EFL Students majoring in English face difficulties in academic lectures listening comprehension in content courses like linguistics, applied linguistics or literature theories. To validate this assumption, a questionnaire assessing students' lecture comprehension experience was administered. The findings have shown that Saudi EFL learners face a great challenge in lecture comprehension at advanced levels. Literature has suggested a myriad of techniques which can enhance academic lecture comprehension. This study has used "reciprocal peer-questioning and responding technique" as an integral part of the academic lecture occupying the last ten minutes. Improvement in experimental students' scores in these courses has been noticed.Keywords: EFL learners, lecture comprehension, content courses, peer questioning
Procedia PDF Downloads 6015631 Investigation of Modified Microporous Materials for Environmental Depollution
Authors: Souhila Bendenia, Chahrazed Bendenia, Hanaa Merad-Dib, Sarra Merabet, Samia Moulebhar, Sid Ahmed Khantar
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Today, environmental pollution is a major concernworldwide, threateninghumanhealth. Various techniques have been used, includingdegradation, filtration, advancedoxidationprocesses, ion exchange, membrane processes, and adsorption. The latter is one of the mostsuitablemethods, usinghighly efficient materials. In this study, NaX zeolite was modified with Cu or Ni at various rates. Following ion exchange, the samples were characterized by XRD, BET and SEM/EDX. After characterization, the exchanged zeolites were used for adsorption of various pollutants as CO2. Different thermodynamic parameters were studied such as Qst. XRD results show that the most intense peaks characteristic of 13X persist after the exchange reaction for all samples. The SEM images of our samples have uniform and regular crystal shapes. The results show that ion exhange with Cu or Ni affect the textural properties of X zeolites and prove that the exchange zeolites can be used as an adsorbent for depollution.Keywords: X zeolites (NaX), ion exchange, characterization, adsorption
Procedia PDF Downloads 975630 Screening of Thyroid Stimulating Hormone Using Paper-Based Lateral Flow Device
Authors: Pattarachaya Preechakasedkit, Kota Osada, Koji Suzuki, Daniel Citterio, Orawon Chailapakul
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A paper-based lateral flow device for screening thyroid stimulating hormone (TSH) is reported. A sandwich immunoassay was performed using two mouse monoclonal TSH antibodies (anti-hTSH 5403 and 5404) as immobilized and labeled antibodies for capturing TSH samples. Test (anti-hTSH 5403) and control (goat anti-Mouse IgG) lines were fabricated on nitrocellulose membrane (NCM) using ballpoint pen printed with a speed of 3 cm/s and thickness setting of 1. The novel gold nanoparticles europium complex (AuNPs@Eu) was used as fluorescence label compared to conventional AuNPs label. The results obtained with this device can be visually assessed by the naked eyes and under UV hand lamps, and quantitative analysis can be performed using the ImageJ program. The limit of detection (LOD) under UV hand lamps (0.1 µIU/mL) provided 50-fold greater sensitivity than AuNPs (5 µIU/mL), which is suitable for both hypothyroidism and hyperthyroidism screening within 30 min. A linear relationship between the red intensity and the logarithmic concentrations of TSH was observed with a good correlation (R²=0.992). Furthermore, the device can be effectively applied for screening TSH in the spiked human serum with recovery range of 96.80-104.45% and RSD of 2.18-3.63%. Therefore, the developed device is an alternative method for TSH screening which provides a lot of advantages including low cost, short time analysis, ease of use, disposability, portability, and on-site measurement.Keywords: thyroid stimulating hormone, paper-based lateral flow, hypothyroidism, hyperthyroidism
Procedia PDF Downloads 3715629 Cooperative CDD Scheme Based On Hierarchical Modulation in OFDM System
Authors: Seung-Jun Yu, Yeong-Seop Ahn, Young-Min Ko, Hyoung-Kyu Song
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In order to achieve high data rate and increase the spectral efficiency, multiple input multiple output (MIMO) system has been proposed. However, multiple antennas are limited by size and cost. Therefore, recently developed cooperative diversity scheme, which profits the transmit diversity only with the existing hardware by constituting a virtual antenna array, can be a solution. However, most of the introduced cooperative techniques have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that uses hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.Keywords: MIMO, cooperative communication, CDD, hierarchical modulation
Procedia PDF Downloads 5535628 Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines
Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang
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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy
Procedia PDF Downloads 4835627 A Feature Clustering-Based Sequential Selection Approach for Color Texture Classification
Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi
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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix
Procedia PDF Downloads 1415626 Assessing the Spatial Distribution of Urban Parks Using Remote Sensing and Geographic Information Systems Techniques
Authors: Hira Jabbar, Tanzeel-Ur Rehman
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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)
Procedia PDF Downloads 3455625 An Examination of the Effects of Implantable Technologies on the Practices of Governmentality
Authors: Benn Van Den Ende
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Over the last three decades, there has been an exponential increase in developments in implantable technologies such as the cardiac pacemaker, bionic prosthesis, and implantable chips. The effect of these technologies has been well researched in many areas. However, there is a lack of critical research in security studies. This paper will provide preliminary findings to an ongoing research project which aims to examine how implantable technologies effect the practices of governmentality in the context of security. It will do this by looking at the practices and techniques of governmentality along with different implantable technologies which increase, change or otherwise affect governmental practices. The preliminary research demonstrates that implantable technologies have a profound effect on the practices of governmentality, while also paving the way for further research into a potential ‘new’ form of governmentality in relation to these implantable technologies.Keywords: critical security studies, governmentality, security theory, political theory, Foucault
Procedia PDF Downloads 1965624 Computational Identification of Signalling Pathways in Protein Interaction Networks
Authors: Angela U. Makolo, Temitayo A. Olagunju
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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways
Procedia PDF Downloads 5495623 Nonstationarity Modeling of Economic and Financial Time Series
Authors: C. Slim
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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.Keywords: stationarity, unit root tests, economic time series, ADF tests
Procedia PDF Downloads 4265622 Exploring Deep Neural Network Compression: An Overview
Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart
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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition
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