Search results for: doubling time

Authors: Muhajirin Gafar

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In Indonesia, Azan not only used as a reminder or call to prayer, its also used at the birth of a child, as the direction of the Prophet Muhammad PBUH, but also become part of a 'tradition’ to echoed in obsequies or the funeral, even there is a tradition in which the Azan echoed in the four corners of the grave. This tradition has become a necessity and has become part of the local Islamic culture preserved from time to time, although it certainly can not be known legal basis underlying the tradition. Based on the phenomenon, this paper proposed three research objective, namely: 1) To described the history about tradition Azan in funeral, 2) To analyze some of the postulates supporting the occurrence of the tradition, 3) To find out the postulates/ hadist which has been arranged in accordance with the instructions of the Prophet Muhammad PBUH about the rules of funeral. To reconstruct the history of the emergence of events azan tradition in the funeral this research used historical method, while the second and third objective used library research. Data and facts systematically processed and analyzed so as to be able to answer the questions of what, who, where, when, how, and why an event occurred. Finally, this research used Takhrij al-hadith a method to look at the validity of the arguments of the hadith. Result found that tradition of Azan in funeral has been around since the presence of Islam in Indonesia. This tradition continued and became a local Islamic culture which spread almost all over Indonesia, even considered part of religious guidance. While there are no decisive postulates which can be accounted for this tradition, except ‘qiyas’ postulates which are not appropriate. Most Indonesian Muslim put Azan as the first priority to do in funeral while oblivious other compulsory things that must be recited when lay down the corpse. They tend to assume that this tradition is a part of Islamic local culture.

Keywords: Azan, tradition, qiyas, Islamic local, hadist

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Authors: Safa'a M. Rasheed, Saba A. Gheni, Wadood T. Mohamed

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Phenolic compounds are the most carcinogenic pollutants in waste water in effluents of refineries and pulp industry. Catalytic wet air oxidation is an efficient industrial treatment process to oxidize phenolic compounds into unharmful organic compounds. Mode of flow of the fluid to be treated is a dominant factor in determining effectiveness of the catalytic process. The present study aims to obtain a mathematical model describing the conversion of phenolic compounds as a function of the process variables; mode of flow (trickling and pulsing), temperature, pressure, along with a high concentration of phenols and a platinum supported alumina catalyst. The model was validated with the results of experiments obtained in a fixed bed reactor. High pressure and temperature were employed at 8 bar and 140 °C. It has been found that conversion of phenols is highly influenced by mode of flow and the change is caused by changes occurred in hydrodynamic regime at the time of pulsing flow mode, thereby a temporal variation in wetting efficiency of platinum prevails; which in turn increases and/or decreases contact time with phenols in wastewater. The model obtained was validated with experimental results, and it is found that the model is a good agreement with the experimental results.

Keywords: wastewater, phenol, pulsing flow, wet oxidation, high pressure

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Authors: Harshdeep Singh, Kuljeet Singh Anand

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Background: Cerebrovascular Accidents (CVA) cause abnormal or asymmetrical tendon reflexes contributing to motor impairments. Since the tendon reflexes are mediated by the spinal cord, their effects on cognitive performances are overlooked. This study aims to find the contributions of tendon reflexes on the performance of the Flanker task. Methods: A total population of 46 mixed subjects with movement disorders were recruited for the study. Deep tendon reflexes (DTR) of the biceps, triceps and brachioradialis were assessed for both upper extremities. Later, the Flanker task was performed on all the subjects, and the mean Reaction Time (RT) along with both the congruent and incongruent stimuli were evaluated. For the final analysis, the Kruskal Wallis test was performed to see the difference between the DTR and the performance of the Flanker Task. Results: The Kruskal Wallis test results showed a significant difference between the DTR scores, X²(2) = 11.328, p= 0.023 with the mean RT of the flanker task and X²(2) = 9.531, p= 0.049 with mean RT of the Incongruent Stimuli. Whereas the result found a non-significant difference in the mean RT of the Congruent Stimuli. Conclusion: Each DTR score is distributed differently with the mean RT of the flanker task and for the incongruent stimuli as well. Therefore, the tendon reflexes in PD may be contributing to the performance of the Flanker Task and may be an indicator of abnormal cognitive performance. Further research is needed to evaluate how the RTs are distributed with each DTR score.

Keywords: cerebrovascular accidents, deep tendon reflexes, flanker task, reaction time, congruent stimuli, incongruent stimuli

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Authors: Shaibu Salifu, Ofori Boachie

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Philanthropy is part and parcel of African identity; it is intrinsically embedded in the life of Africans where at any point in time people contribute to philanthropy through giving or receiving. Even though, research on corporate philanthropy has gained attention in the academic space of Ghana, little have been done on the effects of corporate foundation giving on female labour force participation in Ghana. We investigate the effects of corporate foundations giving on female labour force participation in Ghana. We applied convenient and purposive sampling techniques to collect qualitative data from thirty (30) women in Ghana through interviews and open-ended questionnaires. We used Nvivo to carryout analysis on the data and our results indicate that corporate foundation giving has significant effect on female labour force participation in Ghana. In addition, contrary to the feminization U-Shape Hypothesis, evidence suggest that, to a larger extent marriage and fertility (birth) of women positively contribute to the female labour force participation in Ghana. Nevertheless, the study was limited by the number of women who were interviewed, time constraints of women for elaborate discussions on the issues (constructs) of the study and fear of victimization by authorities on most of their responses to the interviews. The findings have implications for all stakeholders of philanthropy: academia, governments, civil society organizations, corporate foundations, women of Ghana and other relevant bodies.

Keywords: corporate philanthropy, corporate foundations, corporate foundation giving, female labour force participation, women, Ghana

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Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Yulia Irnidayanti , J. J. Josua, A. Sugianto

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Jakarta Bay with 13 rivers that flow into, the environment has deteriorated and is the most polluted bays in Asia. The entry of waste into the waters of the Bay of Jakarta has caused pollution. Heavy metal contamination has led to pollution levels and may cause toxicity to organisms that live in the sea, down to the cellular level and may affect the ecological balance. Various ways have been conducted to measure the impact of environmental degradation, such as by measuring the levels of contaminants in the environment, including measuring the accumulation of toxic compounds in the tissues of organisms. Biological responses or biomarkers known as a sensitive indicator but need relevant predictions. In heavy metal pollution monitoring, analysis of aquatic biota is very important from the analysis of the water itself. The content of metals in aquatic biota will usually always be increased from time to time due to the nature of metal bioaccumulation, so the aquatic biota is best used as an indicator of metal pollution in aquatic environments. The results of the content analysis results of sea water in coastal estuaries Angke, Kaliadem and Panimbang detected heavy metals cadmium, mercury, lead, but did not find zinc metal. Based on the results of protein electrophoresis methallotionein found heavy metals in the tissues hepatopancreas, gills and muscles, and also the mRNA expression of has detected.

Keywords: gills, heavy metal, hepatopancreas, metallothionein, muscle

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Cansu Arslan Turan, Tuba Cimilli Ozturk, Ebru Unal Akoglu, Kemal Aygun, Ecem Deniz Kırkpantur, Ozge Ecmel Onur

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Although the mechanism of action is not well known, Intravenous Lipid Emulsion (ILE) has been shown to be effective in the treatment of lipophilic drug intoxications. It is thought that ILE probably separate the lipophilic drugs from target tissue by creating a lipid-rich compartment in the plasma. The second theory is that ILE provides energy to myocardium with high dose free fatty acids activating the voltage gated calcium channels in the myocytes. In this study, the effects of ILE treatment on digoxin overdose which are frequently observed in emergency departments was searched in an animal model in terms of cardiac side effects and survival. The study was carried out at Yeditepe University, Faculty of Medicine-Experimental Animals Research Center Labs in December 2015. 40 Sprague-Dawley rats weighing 300-400 g were divided into 5 groups randomly. As the pre-treatment, the first group received saline, the second group received lipid, the third group received DigiFab, and the fourth group received DigiFab and lipid. Following that, digoxin was infused to all groups until death except the control group. First arrhythmia and cardiac arrest occurrence times were recorded. As no medication causing arrhythmia was infused, Group 5 was excluded from the statistical analysis performed for the comparisons of first arrhythmia and death time. According to the results although there was no significant difference in the statistical analysis comparing the four groups, as the rats, only exposed to digoxin intoxication were compared with the rats pre-treated with ILE in terms of first arrhythmia time and cardiac arrest occurrence times, significant difference was observed between the groups. According to our results, using DigiFab treatment, intralipid treatment, intralipid and DigiFab treatment for the rats exposed to digoxin intoxication makes no significant difference in terms of the first arrhythmia and death occurrence time. However, it is not possible to say that at the doses we use in the study, ILE treatment might be successful at least as a known antidote. The fact that the statistical significance between the two groups is not observed in the inter-comparisons of all the groups, the study should be repeated in the larger groups.

Keywords: arrhytmia, cardiac arrest, DigiFab, digoxin intoxication

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Authors: Sofiene Amara, Mohamed Ali Bahri, Sabri Gaied Chortane

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The purpose of this study was to examine the effect of personal goal setting on psychological parameters (cognitive anxiety, somatic anxiety, and self-confidence) and the 50m freestyle performance. 30 young swimmers participated in this investigation, and was divided into three groups, the first group (G1, n = 10, 14 ± 0.7 years old) was prepared for the competition without a fixed target (method 1), the second group (G2, n = 10, 14 ± 0.9 years old) was oriented towards a vague goal 'Do your best' (method 2), while the third group (G3, n = 10, 14 ± 0, 5 years old) was invited to answer a goal that is difficult to reach according to a goal-setting interval (GST) (method 3). According to the statistical data of the present investigation, the cognitive and somatic anxiety scores in G1 and G3 were higher than in G2 (G1-G2, G3-G2: cognitive anxiety, P = 0.000, somatic anxiety: P = 0.000 respectively). On the other hand, the self-confidence score was lower in G1 compared with the other two groups (G1-G2, G3-G2: P = 0.02, P = 0.03 respectively). Our assessment also shows that the 50m freestyle time performance was improved better by method 3 (pre and post-Test: P = 0.006, -2.5sec, 7.83%), than by method 2 (pre and Post-Test: P = 0.03; -1sec; 3.24%), while, performance remained unchanged in G1 (P > 0.05). To conclude, the setting of a difficult goal by GST is more effective to improve the chronometric performance in the 50m freestyle, but at the same time increased the values ​​of the cognitive and somatic anxiety. For this, the mental trainers and the staff technical, invited to develop models of mental preparation associated with this method of setting a goal to help swimmers on the psychological level.

Keywords: cognitive anxiety, goal setting, performance of swimming freestyle, self-confidence, somatic anxiety

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Authors: Salome Schulze

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The delay of students in completing their dissertations is a worldwide problem. At the University of South Africa where this research was done, only about a third of the students complete their studies within the required period of time. This study explored the reasons why the students interrupted their studies, and why they resumed their research at a later stage. If this knowledge could be utilised to improve the throughput of doctoral students, it could have significant economic benefits for institutions of higher education while at the same time enhancing their academic prestige. To inform the investigation, attention was given to key theories concerning the learning of doctoral students, namely the situated learning theory, the social capital theory and the self-regulated learning theory, based on the social cognitive theory of learning. Ten students in the faculty of Education were purposefully selected on the grounds of their poor progress, or of having been in the system for too long. The collection of the data was in accordance with a Finnish study, since the two studies had the same aims, namely to investigate student engagement and disengagement. Graphic elicitation interviews, based on visualisations were considered appropriate to collect the data. This method could stimulate the reflection and recall of the participants’ ‘stories’ with very little input from the interviewer. The interviewees were requested to visualise, on paper, their journeys as doctoral students from the time when they first registered. They were to indicate the significant events that occurred and which facilitated their engagement or disengagement. In the interviews that followed, they were requested to elaborate on these motivating or challenging events by explaining when and why they occurred, and what prompted them to resume their studies. The interviews were tape-recorded and transcribed verbatim. Information-rich data were obtained containing visual metaphors. The data indicated that when the students suffered a period of disengagement, it was sometimes related to a lack of self-regulated learning, in particular, a lack of autonomy, and the inability to manage their time effectively. When the students felt isolated from the academic community of practice disengagement also occurred. This included poor guidance by their supervisors, which accordingly deprived them of significant social capital. The study also revealed that situational factors at home or at work were often the main reasons for the students’ procrastinating behaviour. The students, however, remained in the system. They were motivated towards a renewed engagement with their studies if they were self-regulated learners, and if they felt a connectedness with the academic community of practice because of positive relationships with their supervisors and of participation in the activities of the community (e.g., in workshops or conferences). In support of their learning, networking with significant others who were sources of information provided the students with the necessary social capital. Generally, institutions of higher education cannot address the students’ personal issues directly, but they can deal with key institutional factors in order to improve the throughput of doctoral students. It is also suggested that graphic elicitation interviews be used more often in social research that investigates the learning and development of the students.

Keywords: doctoral students, engaging and disengaging experiences, graphic elicitation interviews, student procrastination

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a real-time simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three Velmex XSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: surgical robot, haptic feedback, MATLAB, strain gage, simulink

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Authors: Gerald Todd

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Recent advances in random epistemologies and ubiquitous theory have paved the way for web services. Given the current status of linear-time communication, cyberinformaticians compellingly desire the exploration of link-level acknowledgements. In order to realize this purpose, we concentrate our efforts on disconfirming that DHTs and model checking are mostly incompatible.

Keywords: LAN, cyberinformatics, model checking, communication

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Authors: Ravneet Kaur

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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.

Keywords: requirements management, Agile

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Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Aderonke A. Okoya, Oluwaseun A. Somoye, Omotayo S. Amuda, Ifeanyi E. Ofoezie

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This study assessed the efficiency of Hydroxyapatite Powder (HAP) in the removal of dyes in wastewater in comparison with Commercial Activated Carbon (CAC). This was with a view to developing cost effective method that could be more environment friendly. The HAP and CAC were used as adsorbent while Indigo dye was used as the adsorbate. The batch adsorption experiment was carried out by varying initial concentrations of the indigo dye, contact time and adsorbent dosage. Adsorption efficiency was classified by adsorption Isotherms using Langmuir, Freundlich and D-R isotherm models. Physicochemical parameters of a textile industry wastewater were determined before and after treatment with the adsorbents. The results from the batch experiments showed that at initial concentration of 125 mg/L of adsorbate in simulated wastewater, 0.9276 ± 0.004618 mg/g and 3.121 ± 0.006928 mg/g of indigo adsorbed per unit time (qt) of HAP and CAC respectively. The ratio of HAP to CAC required for the removal of indigo dye in simulated wastewater was 2:1. The isotherm model of the simulated wastewater fitted well to Freundlich model, the adsorption intensity (1/n) presented 1.399 and 0.564 for HAP and CAC, respectively. This revealed that the HAP had weaker bond than the electrostatic interactions which were present in CAC. The values of some physicochemical parameters (acidity, COD, Cr, Cd) of textile wastewater when treated with HAP decreased. The study concluded that HAP, an environment-friendly adsorbent, could be effectively used to remove dye from textile industrial wastewater with added advantage of being regenerated.

Keywords: adsorption isotherm, commercial activated carbon, hydroxyapatite powder, indigo dye, textile wastewater

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Authors: Benniche Omar

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We are concerned with abstract fully nonlinear differential equations having the form y’(t)=Ay(t)+f(t,y(t)) where A is an m—dissipative operator (possibly multi—valued) defined on a subset D(A) of a Banach space X with values in X and f is a given function defined on I×X with values in X. We consider a graph K in I×X. We recall that K is said to be viable with respect to the above abstract differential equation if for each initial data in K there exists at least one trajectory starting from that initial data and remaining in K at least for a short time. The viability problem has been studied by many authors by using various techniques and frames. If K is closed, it is shown that a tangency condition, which is mainly linked to the dynamic, is crucial for viability. In the case when X is infinite dimensional, compactness and convexity assumptions are needed. In this paper, we are concerned with the notion of near viability for a given graph K with respect to y’(t)=Ay(t)+f(t,y(t)). Roughly speaking, the graph K is said to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)), if for each initial data in K there exists at least one trajectory remaining arbitrary close to K at least for short time. It is interesting to note that the near viability is equivalent to an appropriate tangency condition under mild assumptions on the dynamic. Adding natural convexity and compactness assumptions on the dynamic, we may recover the (exact) viability. Here we investigate near viability for a graph K in I×X with respect to y’(t)=Ay(t)+f(t,y(t)) where A and f are as above. We emphasis that the t—dependence on the perturbation f leads us to introduce a new tangency concept. In the base of a tangency conditions expressed in terms of that tangency concept, we formulate criteria for K to be near viable with respect to y’(t)=Ay(t)+f(t,y(t)). As application, an abstract null—controllability theorem is given.

Keywords: abstract differential equation, graph, tangency condition, viability

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Authors: Laurie Dempsey

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Relationships are considered to be beneficial for emotional wellbeing, happiness and physical health. However, they are also complicated: individuals engage in a multitude of complex and volatile relationships during their lifetime, where the change to or ending of these dynamics can be deeply disruptive. As the internet is further integrated into everyday life and relationships are increasingly mediated, Media Studies’ and Sociology’s research interests intersect and converge. This study longitudinally explores how relationship change over time corresponds with the developing UK technological landscape between 2005-2018. Since the early 2000s, the use of computer-mediated communication (CMC) in the UK has dramatically reshaped interaction. Its use has compelled individuals to renegotiate how they consider their relationships: some argue it has allowed for vast networks to be accumulated and strengthened; others contend that it has eradicated the core values and norms associated with communication, damaging relationships. This research collaborated with UK media regulator Ofcom, utilising the longitudinal dataset from their Adult Media Lives study to explore how relationships and CMC use developed over time. This is a unique qualitative dataset covering 2005-2018, where the same 18 participants partook in annual in-home filmed depth interviews. The interviews’ raw video footage was examined year-on-year to consider how the same people changed their reported behaviour and outlooks towards their relationships, and how this coincided with CMC featuring more prominently in their everyday lives. Each interview was transcribed, thematically analysed and coded using NVivo 11 software. This study allowed for a comprehensive exploration into these individuals’ changing relationships over time, as participants grew older, experienced marriages or divorces, conceived and raised children, or lost loved ones. It found that as technology developed between 2005-2018, everyday CMC use was increasingly normalised and incorporated into relationship maintenance. It played a crucial role in altering relationship dynamics, even factoring in the breakdown of several ties. Three key relationships were identified as being shaped by CMC use: parent-child; extended family; and friendships. Over the years there were substantial instances of relationship conflict: for parents renegotiating their dynamic with their child as they tried to both restrict and encourage their child’s technology use; for estranged family members ‘forced’ together in the online sphere; and for friendships compelled to publicly display their relationship on social media, for fear of social exclusion. However, it was also evident that CMC acted as a crucial lifeline for these participants, providing opportunities to strengthen and maintain their bonds via previously unachievable means, both over time and distance. A longitudinal study of this length and nature utilising the same participants does not currently exist, thus provides crucial insight into how and why relationship dynamics alter over time. This unique and topical piece of research draws together Sociology and Media Studies, illustrating how the UK’s changing technological landscape can reshape one of the most basic human compulsions. This collaboration with Ofcom allows for insight that can be utilised in both academia and policymaking alike, making this research relevant and impactful across a range of academic fields and industries.

Keywords: computer mediated communication, longitudinal research, personal relationships, qualitative data

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: butterfly valve, flow coefficient, automatic CFD analysis, FSI analysis

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Authors: J. Fenianos, C. Khater, D. Brouillet

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Ecological projects are often faced with reluctance from local communities hosting the project, especially when this project involves variation from preset ideas or classical practices. This paper aims at appreciating the contribution of environmental psychology through cognitive flexibility exercises to improve the acceptability of local communities in adopting more ecological rehabilitation scenarios. The study is based on a quarry site located in Bekaa- Lebanon. Four groups were considered with different levels of involvement, as follows: Group 1 is Training (T) – 50 hours of on-site training over 8 months, Group 2 is Awareness (A) – 2 hours of awareness raising session, Group 3 is Flexibility (F) – 2 hours of flexibility exercises and Group 4 is the Control (C). The results show that individuals in Group 3 (F) who followed flexibility sessions accept comparably the ecological rehabilitation option over the more classical one. This is also the case for the people in Group 1 (T) who followed a more time-demanding “on-site training”. Another experience was conducted on a second quarry site combining flexibility with awareness-raising. This research confirms that it is possible to reduce resistance to change thanks to a limited in-time intervention using cognitive flexibility. This methodological approach could be transferable to other environmental problems involving local communities and changes in preset perceptions.

Keywords: acceptability, ecological restoration, environmental psychology, Lebanon, local communities, resistance to change

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Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

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Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Coke, iron oxide wastes, recycling, reduction

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Authors: Mohammad Tawhid Kawser, Ishrak Kabir, Sadia Sultana, Tanjim Ahmad

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A promising service category of 5G, popularly known as Ultra-Reliable Low-Latency Communications (URLLC), is devoted to providing users with the staunchest fail-safe connections in the splits of a second. The reliability of data transfer, as offered by Hybrid ARQ (HARQ), should be employed as URLLC applications are highly error-sensitive. However, the delay added by HARQ ACK/NACK and retransmissions can degrade performance as URLLC applications are highly delay-sensitive too. To improve latency while maintaining reliability, this paper proposes the use of blind transmissions of redundancy versions exploiting the frequency diversity of wide bandwidth of 5G. The blind HARQ retransmissions proposed so far consider narrow bandwidth cases, for example, dedicated short range communication (DSRC), shared channels for device-to-device (D2D) communication, etc., and thus, do not gain much from the frequency diversity. The proposal also combines blind and ACK/NACK based retransmissions for different multiplexing options between time and frequency depending on the current radio channel quality and stringency of latency requirements. The wide bandwidth of 5G justifies that the proposed blind retransmission, without waiting for ACK/NACK, is not palpably extravagant. A simulation is performed to demonstrate the improvement in latency of the proposed scheme.

Keywords: 5G, URLLC, HARQ, latency, frequency diversity

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Authors: Jemma Porrett

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Background: We present a literature review examining the research surrounding tick paralysis resulting in facial nerve palsy. A case of an intra-aural paralysis tick bite resulting in unilateral facial nerve palsy is also discussed. Methods: A novel case of otoacariasis with associated ipsilateral facial nerve involvement is presented. Additionally, we conducted a review of the literature, and we searched the MEDLINE and EMBASE databases for relevant literature published between 1915 and 2020. Utilising the following keywords; 'Ixodes', 'Facial paralysis', 'Tick bite', and 'Australia', 18 articles were deemed relevant to this study. Results: Eighteen articles included in the review comprised a total of 48 patients. Patients' ages ranged from one year to 84 years of age. Ten studies estimated the possible duration between a tick bite and facial nerve palsy, averaging 8.9 days. Forty-one patients presented with a single tick within the external auditory canal, three had a single tick located on the temple or forehead region, three had post-auricular ticks, and one patient had a remarkable 44 ticks removed from the face, scalp, neck, back, and limbs. A complete ipsilateral facial nerve palsy was present in 45 patients, notably, in 16 patients, this occurred following tick removal. House-Brackmann classification was utilised in 7 patients; four patients with grade 4, one patient with grade three, and two patients with grade 2 facial nerve palsy. Thirty-eight patients had complete recovery of facial palsy. Thirteen studies were analysed for time to recovery, with an average time of 19 days. Six patients had partial recovery at the time of follow-up. One article reported improvement in facial nerve palsy at 24 hours, but no further follow-up was reported. One patient was lost to follow up, and one article failed to mention any resolution of facial nerve palsy. One patient died from respiratory arrest following generalized paralysis. Conclusions: Tick paralysis is a severe but preventable disease. Careful examination of the face, scalp, and external auditory canal should be conducted in patients presenting with otalgia and facial nerve palsy, particularly in tropical areas, to exclude the possibility of tick infestation.

Keywords: facial nerve palsy, tick bite, intra-aural, Australia

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Remy Jonkam Oben

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Using a time series approach, this study investigates how natural resources impact financial development from a global perspective over the 1980-2019 period. Some important determinants of financial development (economic growth, trade openness, population growth, and investment) have been added to the model as control variables. Unit root tests have revealed that all the variables are integrated into order one. Johansen's cointegration test has shown that the variables are in a long-run equilibrium relationship. The vector error correction model (VECM) has estimated the coefficient of the error correction term (ECT), which suggests that the short-run values of natural resources, economic growth, trade openness, population growth, and investment contribute to financial development converging to its long-run equilibrium level by a 23.63% annual speed of adjustment. The estimated coefficients suggest that global natural resource rent has a statistically-significant negative impact on global financial development in the long-run (thereby validating the financial resource curse) but not in the short-run. Causality test results imply that neither global natural resource rent nor global financial development Granger-causes each other.

Keywords: financial development, natural resources, resource curse hypothesis, time series analysis, Granger causality, global perspective

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Authors: Qiangqiang Xu, Xu Ji, Jingyang Han, Changchun Yang, Ming Li

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Replacing of complex solar concentrating unit, this paper designs a solar heat-concentrating medium-temperature steam-generating system. Solar radiation is collected by using a large solar collecting and heat concentrating plate and is converged to the metal evaporating pipe with high efficient heat transfer. In the meantime, the heat loss is reduced by employing a double-glazed cover and other heat insulating structures. Thus, a high temperature is reached in the metal evaporating pipe. The influences of the system's structure parameters on system performance are analyzed. The steam production rate and the steam production under different solar irradiance, solar collecting and heat concentrating plate area, solar collecting and heat concentrating plate temperature and heat loss are obtained. The results show that when solar irradiance is higher than 600 W/m², the effective heat collecting area is 7.6 m² and the double-glazing cover is adopted, the system heat loss amount is lower than the solar irradiance value. The stable steam is produced in the metal evaporating pipe at 100 ℃, 110 ℃, and 120 ℃, respectively. When the average solar irradiance is about 896 W/m², and the steaming cumulative time is about 5 hours, the daily steam production of the system is about 6.174 kg. In a single day, the solar irradiance is larger at noon, thus the steam production rate is large at that time. Before 9:00 and after 16:00, the solar irradiance is smaller, and the steam production rate is almost 0.

Keywords: heat concentrating, heat loss, medium temperature, solar steam production

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Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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