Search results for: Just in Time

Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

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Authors: Sara Segura, Diego Nuñez, Miryam Villamil

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In this work, we studied the microscale interaction of foreign substances with blood inside an artificial transparent artery system that represents medium and small muscular arteries. This artery system had channels ranging from 75 μm to 930 μm and was fabricated using glass and transparent polymer blends like Phenylbis(2,4,6-trimethylbenzoyl) phosphine oxide, Poly(ethylene glycol) and PDMS in order to be monitored in real time. The setup was performed using a computer controlled precision micropump and a high resolution optical microscope capable of tracking fluids at fast capture. Observation and analysis were performed using a real time software that reconstructs the fluid dynamics determining the flux velocity, injection dependency, turbulence and rheology. All experiments were carried out with fully computer controlled equipment. Interactions between substances like water, serum (0.9% sodium chloride and electrolyte with a ratio of 4 ppm) and blood cells were studied at microscale as high as 400nm of resolution and the analysis was performed using a frame-by-frame observation and HD-video capture. These observations lead us to understand the fluid and mixing behavior of the interest substance in the blood stream and to shed a light on the use of implantable devices for drug delivery at arteries with different Endothelial dysfunction. Several substances were tested using the artificial artery system. Initially, Milli-Q water was used as a control substance for the study of the basic fluid dynamics of the artificial artery system. However, serum and other low viscous substances were pumped into the system with the presence of other liquids to study the mixing profiles and behaviors. Finally, mammal blood was used for the final test while serum was injected. Different flow conditions, pumping rates, and time rates were evaluated for the determination of the optimal mixing conditions. Our results suggested the use of a very fine controlled microinjection for better mixing profiles with and approximately rate of 135.000 μm3/s for the administration of drugs inside arteries.

Keywords: artificial artery, drug delivery, microfluidics dynamics, arteriosclerosis

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Authors: Kobid Panthi, Suttisak Soralump, Suriyon Prempramote

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In June 27, 2014 slope movement was observed in upstream side of Khlong Pa Bon Dam, Thailand. The slide did not have any major catastrophic impact on the dam structure but raised a very important question; why did the slide occur after 10 years of operation? Various site investigations (Bore Hole Test, SASW, Echo Sounding, and Geophysical Survey), laboratory analysis and numerical modelling using SIGMA/W and SLOPE/W were conducted to determine the cause of slope movement. It was observed that the dam had undergone the greatest differential drawdown in its operational history in the year 2014 and was termed as the major cause of movement. From the laboratory tests, it was found that the shear strength of clay had decreased with a period of time and was near its residual value. The cyclic movement of water, i.e., reservoir filling and emptying was coined out to be the major cause for the reduction of shear strength. The numerical analysis was carried out using a modified cam clay (MCC) model to determine the strain softening behavior of the clay. The strain accumulation was observed in the slope with each reservoir cycle triggering the slope failure in 2014. It can be inferred that if there was no major drawdown in 2014, the slope would not have failed but eventually would have failed after a long period of time. If there was no major drawdown in 2014, the slope would not have failed. However, even if there hadn’t been a drawdown, it would have failed eventually in the long run.

Keywords: slope movement, strain softening, residual strength, modified cam clay

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Fagner Luiz P. Salles, Janaina C. Oliveira, Ivair P. Cesar

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Statement of the Problem: Auriculotherapy (AT) is a TCM technique, which uses seeds instead of needles, based physiologically on the mechanical stimulation of the cranial nerves. In the context of understanding the new concept of health of the WHO, the AT is an integrative approach for achieving Global Health Care so as to achieve the global health care concerns. This study aimed to evaluate the effect of auriculotherapy on pain and sleep quality in patients with chronic pain. Methodology and Theoretical Orientation: This study was performed between February and March 2017 at the Faculdade Estácio de Sá de Vitória, Brazil. The pain evaluation was through VAS in 4 periods: maximum, minimum, average and at the time of evaluation; the evaluation of sleep quality was used the Pittsburgh Sleep Quality Index. Socio-demographic data included: gender, age, use of medication and BMI. All data are presented as mean (standard deviation), Teste Mann-Whitney and T-student with P-values < 0.05 were regarded as significant. Findings: Participated in this study thirty-two individuals with age (M = 43.18, SD = 17.86), the time with pain in years (M = 3.67, SD = 3.68), 81.7% were female, 75% of the individuals used medication and BMI (M = 26.67; SD = 6.20). The pain presented improvement in the maximum level and the average of the pain and sleep quality before did not have statistically significant results. Conclusion and Significance: This study showed that TA is efficacy for reduction levels of pain. However, AT was not effective in improving sleep quality.

Keywords: auriculotherapy, chronic pain, sleep quality, integrative approach

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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: Briohny H. Spencer, Russ Chess-Williams, Catherine McDermott, Shailendra Anoopkumar-Dukie, David Christie

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Background: Prostate cancer is the second most common cancer diagnosed in men worldwide and the most prevalent in Australian men. In 2015, it was estimated that approximately 18,000 new cases of prostate cancer were diagnosed in Australia. Currently, for localised disease, androgen depravation therapy (ADT) and radiotherapy are a major part of the curative management of prostate cancer. ADT acts to reduce the levels of circulating androgens, primarily testosterone and the locally produced androgen, dihydrotestosterone (DHT), or by preventing the subsequent activation of the androgen receptor. Thus, the growth of the cancerous cells can be reduced or ceased. Radiation techniques such as brachytherapy (radiation delivered directly to the prostate by transperineal implant) or external beam radiation therapy (exposure to a sufficient dose of radiation aimed at eradicating malignant cells) are also common techniques used in the treatment of this condition. Radiotherapy (RT) has significant limitations, including reduced effectiveness in treating malignant cells present in hypoxic microenvironments leading to radio-resistance and poor clinical outcomes and also the significant side effects for the patients. Alpha1-adrenoceptor antagonists are used for many prostate cancer patients to control lower urinary tract symptoms, due to the progression of the disease itself or may arise as an adverse effect of the radiotherapy treatment. In Australia, a significant number (not a majority) of patients receive a α1-ADR antagonist and four drugs are available including prazosin, terazosin, alfuzosin and tamsulosin. There is currently limited published data on the effects of α1-ADR antagonists during radiotherapy, but it suggests these medications may improve patient outcomes by enhancing the effect of radiotherapy. Aim: To determine the impact of α1-ADR antagonists treatments on time to biochemical relapse following radiotherapy. Methods: A retrospective study of male patients receiving radiotherapy for biopsy-proven localised prostate cancer was undertaken to compare cancer outcomes for drug-naïve patients and those receiving α1-ADR antagonist treatments. Ethical approval for the collection of data at Genesis CancerCare QLD was obtained and biochemical relapse (defined by a PSA rise of >2ng/mL above the nadir) was recorded in months. Rates of biochemical relapse, prostate specific antigen doubling time (PSADT) and Kaplan-Meier survival curves were also compared. Treatment groups were those receiving α1-ADR antagonists treatment before or concurrent with their radiotherapy. Data was statistically analysed using One-way ANOVA and results expressed as mean ± standard deviation. Major findings: The mean time to biochemical relapse for tamsulosin, prazosin, alfuzosin and controls were 45.3±17.4 (n=36), 41.5±19.6 (n=11), 29.3±6.02 (n=6) and 36.5±17.6 (n=16) months respectively. Tamsulosin, prazosin but not alfuzosin delayed time to biochemical relapse although the differences were not statistically significant. Conclusion: Preliminary data for the prior and/or concurrent use of tamsulosin and prazosin showed a positive trend in delaying time to biochemical relapse although no statistical significance was shown. Larger clinical studies are indicated and with thousands of patient records yet to be analysed, it may determine if there is a significant effect of these drugs on control of prostate cancer.

Keywords: alpha1-adrenoceptor antagonists, biochemical relapse, prostate cancer, radiotherapy

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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

Abstract:

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

Procedia PDF Downloads 37