Search results for: high performance fiber reinforced concrete

Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: H. Jalahi, A. Yazdanpanah Nozari

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Background and Purpose: Assessment of learners’ performance is an important factors in teaching-learning process. When a factor is sensitive and has high influence on life, their assessment should be done precisely. Thinking dispositions are very important factors in medical education because of its specific condition. In this study a model is designed for fostering thinking dispositions of learners in which authentic assessment is an important element. Materials and Methods: Objective based research is developmental, and such a model was not designed for curricula. Data collection and comparing approaches about assessment and analyzing current assessments offered applied proposals. Results: Based on research findings, the current assessments are response-based, that is students instead of product of response, only offers the specific response which the teachers expects; but authentic assessment is a form of assessment in which students are asked to perform real-word tasks that demonstrate meaningful application of essential knowledge and skills. Conclusion: Because of the difficulties and unexpected problems in life and individuals needs to lifelong learning and conditions in medical course that require decision making in specific times, we must pay attention to reach thinking dispositions and it should be included in curriculum. Authentic assessment as an important aspect of curriculum can help fostering thinking dispositions of learners. Using this kind of assessments which focus on application of information and skills to solve real-word tasks have more important role in medical courses.

Keywords: assessment, authentic, medical courses, developmental

Procedia PDF Downloads 353

Authors: Zohreh Bang Tavakoli, Shuktika Chatterjee

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This study investigates the fiscal policy impact on countries’ economic growth in developing countries with a different external debt level. The fiscal policy effectiveness has been re-emphasized in the global financial crisis of 2008 with the external debt as its new contemporary driver (Ruščáková and Semančíková, 2016). According to Bouakez, (2014 ) different theories have proposed the economic consequence of fiscal policy, specifically for developing countries. However, fiscal policy literature is lacking research regarding the fiscal policy’s effectiveness with the external debt’s contributions through comprehensive study (Canh, 2018). Also, according to scholars, high levels of external debt will influence economic growth. First, through foreign resources and channel of investment in which high level of debt decreases the amount of foreign investment in the developing countries. Second, through the deterioration of foreign investors and fiscal policies related to a high level of debt (Cordella, et.al., 2010). Therefore, this study proposed that only countries with a low external debt level and appropriate fiscal policies and good quality institutions can gain the proper quantity and quality of foreign investors, which will help the economic growth. For this, this research is examining the impact of fiscal policy on developing countries' economic growth in the situation of different external debt levels.

Keywords: fiscal policy, external debt, gross domestic product, developing countries

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Authors: Junhai Liao, Yansong Shen, Aibing Yu

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A 3D numerical model is developed to simulate the complicated in-furnace combustion phenomena in the lower part of an ironmaking blast furnace (BF) while using pulverized coal injection (PCI) technology to reduce the consumption of relatively expensive coke. The computational domain covers blowpipe-tuyere-raceway-coke bed in the BF. The model is validated against experimental data in terms of gaseous compositions and coal burnout. Parameters, such as coal properties and some key operational variables, play an important role on the performance of coal combustion. Their diverse effects on different combustion characteristics are examined in the domain, in terms of gas compositions, temperature, and burnout. The heat generated by the combustion of upgraded Victorian brown coal is able to meet the heating requirement of a BF, hence making upgraded brown coal injected into BF possible. It is evidenced that the model is suitable to investigate the mechanism of the PCI operation in a BF. Prediction results provide scientific insights to optimize and control of the PCI operation. This model cuts the cost to investigate and understand the comprehensive combustion phenomena of upgraded Victorian brown coal in a full-scale BF.

Keywords: blast furnace, numerical study, pulverized coal injection, Victorian brown coal

Procedia PDF Downloads 230

Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: A. Shishkin, V. Mironovs, D. Goljandin, A. Korjakins

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The goal of this work is to develop sustainable and durable ceramic cellular structures using widely available natural resources- clay and milled waste glass. Present paper describes method of obtaining clay ceramic foam (CCF) with addition of milled waste glass in 5, 7 and 10 wt% by direct foaming with high speed mixer-disperser (HSMD). For more efficient clay and waste glass milling and mixing, the high velocity disintegrator was used. The CCF with 5, 7, and 10 wt% were obtained at 900, 950, 1000 and 1050 °C firing temperature and they have demonstrated mechanical compressive strength for all 12 samples ranging from 3.8 to 14.3 MPa and porosity 76-65%. Obtained CCF has compressive strength 14.3 MPa and porosity 65.3%.

Keywords: ceramic foam, waste glass, clay foam, glass foam, open cell, direct foaming

Procedia PDF Downloads 294

Authors: Ali Maji

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Highway development is an important factor for economic growth and development in both developed and developing countries. In Nigeria about two-third of transportation of goods and persons are done through highway network. It was this that made highway investment to enjoy position of relative high priority on the list of government expenditure programmes in Nigeria today. The paper noted that despite expansion of public investment in highway construction and maintenance of them, road traffic accident is increasing rate. This has acted as a drain of human capital which is a key to economic growth and development in Nigeria. In order to avoid this, the paper recommend introduction of Highway Safety Education (HSE) in Nigerian’s education system and investment in train transportation among other as a sure measure for curtailing highway accident.

Keywords: accident rate, high way development, human capital, national development

Procedia PDF Downloads 267

Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Ghulam Murshid

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Carbon dioxide is one of the major greenhouse gas (GHG) contributors. It is an obligation of the industry to reduce the amount of carbon dioxide emission to the acceptable limits. Tremendous research and studies are reported in the past and still the quest to find the suitable and economical solution of this problem needed to be explored in order to develop the most plausible absorber for carbon dioxide removal. Amino acids are reported by the researchers as a potential solvent for absorption of carbon dioxide to replace alkanolamines due to its ability to resist oxidative degradation, low volatility due to its ionic structure and higher surface tension. In addition, the introduction of promoter-like piperazine to amino acid helps to further enhance the solubility. In this work, the effect of piperazine on thermophysical properties and solubility of β-Alanine aqueous solutions were studied for various concentrations. The measured physicochemical properties data was correlated as a function of temperature using least-squares method and the correlation parameters are reported together with it respective standard deviations. The effect of activator piperazine on the CO2 loading performance of selected amino acid under high-pressure conditions (1bar to 10bar) at temperature range of (30 to 60)oC was also studied. Solubility of CO2 decreases with increasing temperature and increases with increasing pressure. Quadratic representation of solubility using Response Surface Methodology (RSM) shows that the most important parameter to optimize solubility is system pressure. The addition of promoter increases the solubility effect of the solvent.

Keywords: amino acids, co2, global warming, solubility

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Authors: Tao Chen, ShiHua Liu, JiWei Zhang

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Assembly of the proton exchange membrane fuel cells (PEMFC) has a very important influence on its performance and efficiency. The various components of PEMFC stack are usually locked and fixed by bolts. Locking bolt will cause the deformation of the bipolar plate and the other components, which will affect directly the deformation degree of the integral parts of the PEMFC as well as the performance of PEMFC. This paper focuses on the object of three-cell stack of PEMFC. Finite element simulation is used to investigate the deformation of bipolar plate caused by quantity and layout of bolts, bolt locking pressure, and bolt locking sequence, etc. Finally, we made a conclusion that the optimal combination packaging scheme was adopted to assemble the fuel cell stack. The scheme was in use of 3.8 MPa locking pressure imposed on the fuel cell stack, type Ⅱ of four locking bolts and longitudinal locking method. The scheme was obtained by comparatively analyzing the overall displacement contour of PEMFC stack, absolute displacement curve of bipolar plate along the given three paths in the Z direction and the polarization curve of fuel cell. The research results are helpful for the fuel cell stack assembly.

Keywords: bipolar plate, deformation, finite element simulation, fuel cell, locking bolt

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Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

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When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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Authors: Messaouda Annab

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The rapid development of technology has led to an important context in which different languages and structures are used in the same conversations. This paper investigates the practice of language borrowing within social media platform, namely, Facebook among Algerian Vernacular Arabic (AVA) students. In other words, this study will explore how Algerian students have incorporated lexical English borrowing in their online conversations. This paper will examine the relationships between language, culture and identity among a multilingual group. The main objective is to determine the cultural and linguistic functions that borrowing fulfills in social media and to explain the possible factors underlying English borrowing. The nature of the study entails the use of an online research method that includes ten online Facebook conversations in the form of private messages collected from Bachelor and Masters Algerian students recruited from the English department at the University of Oum El-Bouaghi. The analysis of data revealed that social media platform provided the users with opportunities to shift from one language to another. This practice was noticed in students’ online conversations. English borrowing was the most relevant language performance in accordance with Arabic which is the mother tongue of the chosen sample. The analysis has assumed that participants are skilled in more than one language.

Keywords: borrowing, language performance, linguistic background, social media

Procedia PDF Downloads 143

Authors: Subal Kar, Amitesh Kumar, A. Majumder, S. K. Ghosh, S. Saha, S. S. Sikdar, T. K. Saha

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CRLH (composite right/left-handed) based and SRR (split-ring resonator) based filters have been designed at microwave frequency which can provide better performance compared to conventional edge-coupled band-pass filter designed around the same frequency, 2.45 GHz. Both CRLH and SRR are unit cells used in metamaterial design. The primary aim of designing filters with such structures is to realize size reduction and also to realize novel filter performance. The CRLH based filter has been designed in microstrip transmission line, while the SRR based filter is designed with SRR loading in waveguide. The CRLH based filter designed at 2.45 GHz provides an insertion loss of 1.6 dB with harmonic suppression up to 10 GHz with 67 % size reduction when compared with a conventional edge-coupled band-pass filter designed around the same frequency. One dimensional (1-D) SRR matrix loaded in a waveguide shows the possibility of realizing a stop-band with sharp skirts in the pass-band while a stop-band in the pass-band of normal rectangular waveguide with tailoring of the dimensions of SRR unit cells. Such filters are expected to be very useful for communication systems at microwave frequency.

Keywords: BPF, CRLH, harmonic, metamaterial, SRR and waveguide

Procedia PDF Downloads 417

Authors: Shimaa A. Higazy, Olfat E. El-Azabawy, Ahmed M. Al-Sabagh, Notaila M. Nasser, Eman A. Khamis

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In this work, two novel Schiff base polymers (PSB1 and PSB₂) with extra-high protective barrier features were facilely prepared via Polycondensation reactions. They were applied for the first time as effective corrosion inhibitors in the sour corrosive media of petroleum environments containing hydrogen sulfide (H₂S) gas. For studying the polymers' inhibitive action on the carbon steel, numerous corrosion testing methods including potentiodynamic polarization (PDP), open circuit potential, and electrochemical impedance spectroscopy (EIS) have been employed at various temperatures (298-328 K) in the oil wells formation water with H₂S concentrations of 100, 400, and 700 ppm as aggressive media. The activation energy (Ea) and other thermodynamic parameters were computed to describe the mechanism of adsorption. The corrosion morphological traits and steel samples' surfaces composition were analyzed by field emission scanning electron microscope and energy dispersive X-ray analysis. The PSB2 inhibited sour corrosion more effectively than PSB1 when subjected to electrochemical testing. The 100 ppm concentration of PSB2 exhibited 82.18 % and 81.14 % inhibition efficiencies at 298 K in PDP and EIS measurements, respectively. While at 328 K, the inhibition efficiencies were 61.85 % and 67.4 % at the same dosage and measurements. These poly Schiff bases exhibited fascinating performance as corrosion inhibitors in sour environment. They provide a great corrosion inhibition platform for the sustainable future environment.

Keywords: schiff base polymers, corrosion inhibitors, sour corrosive media, potentiodynamic polarization, H₂S concentrations

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Authors: R. H. Hwang, J. H. Park, K. B. Yi

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Nitrous oxide (N2O) is now distinguished as an environmental pollutant. N2O is one of the representative greenhouse gases and N2O is produced by both natural and anthropogenic sources. So, it is very important to reduce N2O. N2O abatement processes are various processes such as HC-SCR, NH3-SCR and decomposition process. Among them, decomposition process is advantageous because it does not use a reducing agent. N2O decomposition is a reaction in which N2O is decomposed into N2 and O2. There are noble metals, transition metal ion-exchanged zeolites, pure and mixed oxides for N2O decomposition catalyst. Among the various catalysts, cobalt-based catalysts derived from hydrotalcites gathered much attention because spinel catalysts having large surface areas and high thermal stabilities. In this study, the effect of promoter and K addition on the activity was compared and analyzed. Co3O4 catalysts for N2O decomposition were prepared by co- precipitation method. Ce and Zr were added during the preparation of the catalyst as promoter with the molar ratio (Ce or Zr) / Co = 0.05. In addition, 1 wt% K2CO3 was doped to the prepared catalyst with impregnation method to investigate the effect of K on the catalyst performance. Characterizations of catalysts were carried out with SEM, BET, XRD, XPS and H2-TPR. The catalytic activity tests were carried out at a GHSV of 45,000 h-1 and a temperature range of 250 ~ 375 ℃. The Co3O4 catalysts showed a spinel crystal phase, and the addition of the promoter increased the specific surface area and reduced the particle and crystal size. It was exhibited that the doping of K improves the catalytic activity by increasing the concentration of Co2+ in the catalyst which is an active site for catalytic reaction. As a result, the K-doped catalyst showed higher activity than the promoter added. Also, it was found through experiments that Co2+ concentration and reduction temperature greatly affect the reactivity.

Keywords: Co₃O4, K-doped, N₂O decomposition, promoter

Procedia PDF Downloads 156

Authors: Umar Jaafar, Mungadi

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Plant growth, biochemical parameters, cytotoxic ion sequestration and ionic in balance were determined for spinach in response to varied concentrations of NaCl. The plant show decline in all vegetative parameters measured. Free proline content increase with increasing salt concentration and differ significantly (p<0.05) while the glycine betaine insignificantly (p>0.05) affected by concentration of NaCl. Salinity increases the cytotoxic ions, sodium chlorine ion and calcium with corresponding decrease in potassium ion concentrations. The ionic balance (Na+/K+) is low due to high content of potassium ion in plant accumulation ranging from 7700 to 6500 mg/kg. It can be concluded that the osmolyte accumulations, high number of leaves are possible indicators of salt tolerance in the spinach.

Keywords: spinach, salinity, osmolyte, cytotoxic

Procedia PDF Downloads 345

Authors: I. Tzoka, V. A. Chirayath, A. Brandt, J. Asaadi, Melvin J. Aviles, Stephen Clarke, Stefan Cwik, Michael R. Foley, Cole J. Hamel, Alexey Lyashenko, Michael J. Minot, Mark A. Popecki, Michael E. Stochaj, S. Shin

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Micro-channel plate photo-multiplier tubes (MCP-PMTs) have become ubiquitous and are widely considered potential candidates for next generation High Energy Physics experiments due to their picosecond timing resolution, ability to operate in strong magnetic fields, and low noise rates. A key factor that determines the applicability of MCP-PMTs in their lifetime, especially when they are used in high event rate experiments. We have developed a novel method for the investigation of the aging behavior of an MCP-PMT on an accelerated basis. The method involves exposing a localized region of the MCP-PMT to photons at a high repetition rate. This pixel-based method was inspired by earlier results showing that damage to the photocathode of the MCP-PMT occurs primarily at the site of light exposure and that the surrounding region undergoes minimal damage. One advantage of the pixel-based method is that it allows the dynamics of photo-cathode damage to be studied at multiple locations within the same MCP-PMT under different operating conditions. In this work, we use the pixel-based accelerated lifetime test to investigate the aging behavior of a 20 cm x 20 cm Large Area Picosecond Photo Detector (LAPPD) manufactured by INCOM Inc. at multiple locations within the same device under different operating conditions. We compare the aging behavior of the MCP-PMT obtained from the first lifetime test conducted under high gain conditions to the lifetime obtained at a different gain. Through this work, we aim to correlate the lifetime of the MCP-PMT and the rate of ion feedback, which is a function of the gain of each MCP, and which can also vary from point to point across a large area (400 $cm^2$) MCP. The tests were made possible by the uniqueness of the LAPPD design, which allows independent control of the gain of the chevron stacked MCPs. We will further discuss the implications of our results for optimizing the operating conditions of the detector when used in high event rate experiments.

Keywords: electron multipliers (vacuum), LAPPD, lifetime, micro-channel plate photo-multipliers tubes, photoemission, time-of-flight

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Authors: D. Alromi, A. Alansari, S. Alghamdi, E. Jambi

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As the need for water is increasing globally, and the available water resources are barely meeting the current quality of life and economy. Air conditioning (AC) condensate water could be explored as an alternative water source, which could be considered within the global calculations of the water supply. The objective of this study is to better understand the potential for recovery of condensate water from air conditioning systems. The results generated so far showed that the AC produces a high quantity of water, and data analysis revealed that the amount of water is positively and significantly correlated with the humidity (P <= 0.05). In the meantime, the amount of heavy metals has been measuring using ICP-OES. The results, in terms of quantity, clearly show that the AC can be used as an alternative source of water, especially in the regions characterized by high humidity. The results also showed that the amount of produced water depends on the type of AC.

Keywords: air conditioning systems, water quantity, water resources, wastewater

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Modupe Beatrice Adeyinka

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European Languages are languages of literature, science and technology. Whereas, African languages are of literature, both written and oral, making it difficult for Yoruba, the African language of Kwa linguistic classification, to neatly and accurately translate European scientific and technological words, expressions and technologies. Unless a pragmatic and communicative approach is adopted, equivalence of European technical and scientific texts might be a mission impossible for Yoruba scholars. In view of the aforementioned difficult task, this paper tends to highlight the need for a thorough study and evaluation of English or French words, expressions, idiomatic expressions, technical and scientific terminologies then, trying to find ways of adopting them to Yoruba environment through interpretative translation.

Keywords: communication, high technology, translation, Yoruba language

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

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Authors: Shahbaa F. Bdewi, Bakhtyar K. Aziz, Ayad A. R. Mutar

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Nano-materials show different surface properties due to their high surface area and active sites. This study investigates the feasibility of using nano-MgO (NMO) for removing Congo red (CR) dye from wastewater. NMO was prepared by molten salt method. Equilibrium experiments show the equilibrium was reached after 120 minutes and maximum adsorption efficiency was obtained in acidic media up to pH 6. Isotherm studies revealed the favorability of the adsorption process. The overall adsorption process was spontaneous and endothermic in nature with a maximum adsorption capacity of 1100 mg g-1 at 40°C as estimated from Langmuir isotherm. The adsorption kinetics was found to follow pseudo second-order rate equation. Relatively high activation energy (180.7 kJ mol-1) was obtained which is consistent with chemisorption mechanism for the adsorption process.

Keywords: adsorption, congo red, magnesium oxide, nanoparticles

Procedia PDF Downloads 195

Authors: Kristin Murray

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The proposed paper exams prologues in 20th and 21st century American literature in order to show how Native American writer Tommy Orange’s Prologue in his 2018 novel There, Thereis different. In an interview about his 2018 novel There, There, explains he feels “a kind of burden to catch the general reader up with what really happened, because history has got it so wrong and still continue to” (Laubernds). Orange, thus, includes a “Prologue” in his novel to do this work, catching readers upon Native Americans and their history. Prologues are usually from the narrator’s voice, a character’s voice, or even from a fictionalized version of the author, but the tone of Orange’s “Prologue” is that of a non-fictional first-person essayist. Examining prologues in American literature posits Orange’s prologue outside the norm. This paper also examines other introductory sections, the preface, in particular. The research and examination reveal that Orange is adding his personal voice in the Prologue to the multiple narratorsof the novel, and his is the voice of a writer who knows that his audience comes to his novel with a plethora of misinformation. The truths he tells are horrifying and hopeful. He tells of Thanksgiving as a “land deal” and a “successful massacre,” but he also tellsreaders how urban Indians have found a sense of the land, even through concrete. Native American writers contributed and still contribute to the genre of autobiography in ways that have changed our understanding of this genre. This examination of Orange’s Prologue reveals the new and unexpected way to view this often under-examined introductory section, the prologue.

Keywords: native american literature, prologues, prefaces, 20th century american literature

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Authors: Guenther Schuh, Michael Riesener, Jan Kantelberg

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Due to the fugacity of markets and the reduction of product lifecycles, manufacturing companies from high-wage countries are nowadays faced with the challenge to place more innovative products within even shorter development time on the market. At the same time, volatile customer requirements have to be satisfied in order to successfully differentiate from market competitors. One potential approach to address the explained challenges is provided by agile values and principles. These agile values and principles already proofed their success within software development projects in the form of management frameworks like Scrum or concrete procedure models such as Extreme Programming or Crystal Clear. Those models lead to significant improvements regarding quality, costs and development time and are therefore used within most software development projects. Motivated by the success within the software industry, manufacturing companies have tried to transfer agile mechanisms of action to the development of hardware products ever since. Though first empirical studies show similar effects in the agile development of hardware products, no comprehensive procedure model for the design of development iterations has been developed for hardware development yet due to different constraints of the domains. For this reason, this paper focusses on the design of agile product development processes by transferring mechanisms of action used in agile software development towards product development. This is conducted by decomposing the individual systems 'product development' and 'agile software development' into relevant elements and symbiotically composing the elements of both systems in respect of the design of agile product development processes afterwards. In a first step, existing product development processes are described following existing approaches of the system theory. By analyzing existing case studies from industrial companies as well as academic approaches, characteristic objectives, activities and artefacts are identified within a target-, action- and object-system. In partial model two, mechanisms of action are derived from existing procedure models of agile software development. These mechanisms of action are classified in a superior strategy level, in a system level comprising characteristic, domain-independent activities and their cause-effect relationships as well as in an activity-based element level. Within partial model three, the influence of the identified agile mechanism of action towards the characteristic system elements of product development processes is analyzed. For this reason, target-, action- and object-system of the product development are compared with the strategy-, system- and element-level of agile mechanism of action by using the graph theory. Furthermore, the necessity of existence of activities within iteration can be determined by defining activity-specific degrees of freedom. Based on this analysis, agile product development processes are designed in form of different types of iterations within a last step. By defining iteration-differentiating characteristics and their interdependencies, a logic for the configuration of activities, their form of execution as well as relevant artefacts for the specific iteration is developed. Furthermore, characteristic types of iteration for the agile product development are identified.

Keywords: activity-based process model, agile mechanisms of action, agile product development, degrees of freedom

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Authors: Nimra Parvez, Nawaz Ahmed

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Workplace aggression not only is a proven safety and health issue but it also is a problem witnessed at workplace which has far-reaching consequences. It hinders the overall productivity of the organizations and individual employees. The current study examined employee turnover intentions as a result of workplace aggression. The study was conducted on employees from the private sector. Self-report questionnaires that measured the workplace aggression and turnover intentions of employees were used to target a sample size of 200 employees. In the hypothesis, it was assumed that high levels of workplace aggression at any organization will result in subsequent high levels of employee turnover intentions. It was therefore identified that there has been a relationship between workplace aggression and employee turnover intentions. The results determined a positive relationship between the workplace bullying behaviors towards the individuals and the turnover intention.

Keywords: bullying, organizational commitment, turnover intention, workplace aggression

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Authors: Syed Toqueer Akhter, Muhammad Awais

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Pakistan is a country which is gifted by naturally abundant resources these resources are a pioneer towards a prospect and developed country. Pakistan is the fourth largest exporter of the textile in the world and with the passage of time the competitiveness of these exports is subject to a decline. With a lot of International players in the textile world like China, Bangladesh, India, and Sri Lanka, Pakistan needs to put up a lot of effort to compete with these countries. This research paper would determine the impact of Foreign Direct Investment upon technological diffusion and that how significantly it may be affecting on export performance of the country. It would also demonstrate that with the increase in Foreign Direct Investment, technological diffusion, strong property rights, and using different policy tools, export competitiveness of the country could be improved. The research has been carried out using time series data from 1995 to 2013 and the results have been estimated by using competing Econometrics modes such as Robust regression and Generalized least squares so that to consolidate the impact of the Foreign Investments and Technological diffusion upon export competitiveness comprehensively. Distributed Lag model has also been used to encompass the lagged effect of policy tools variables used by the government. Model estimates entail that 'FDI' and 'Technological Diffusion' do have a significant impact on the competitiveness of the exports of Pakistan. It may also be inferred that competitiveness of Textile Sector requires integrated policy framework, primarily including the reduction in interest rates, providing subsides, and manufacturing of value added products.

Keywords: high technology export, robust regression, patents, technological diffusion, export competitiveness

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Authors: Khin Aye Myint, Mohd Rafii Yusop, Mohd Yusoff Abd Samad, Shairul Izan Ramlee, Mohd Din Amiruddin, Zulkifli Yaakub

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The narrow base of genetic is the main obstacle of breeding and genetic improvement in oil palm industry. In order to broaden the genetic bases, the Malaysian Palm Oil Board has been extensively collected wild germplasm from its original area of 11 African countries which are Nigeria, Senegal, Gambia, Guinea, Sierra Leone, Ghana, Cameroon, Zaire, Angola, Madagascar, and Tanzania. The germplasm collections were established and maintained as a field gene bank in Malaysian Palm Oil Board (MPOB) Research Station in Kluang, Johor, Malaysia to conserve a wide range of oil palm genetic resources for genetic improvement of Malaysian oil palm industry. Therefore, assessing the performance and genetic diversity of the wild materials is very important for understanding the genetic structure of natural oil palm population and to explore genetic resources. Principal component analysis (PCA) and Cluster analysis are very efficient multivariate tools in the evaluation of genetic variation of germplasm and have been applied in many crops. In this study, eight populations of MPOB-Senegal oil palm germplasm were studied to explore the genetic variation pattern using PCA and cluster analysis. A total of 20 yield and yield component traits were used to analyze PCA and Ward’s clustering using SAS 9.4 version software. The first four principal components which have eigenvalue >1 accounted for 93% of total variation with the value of 44%, 19%, 18% and 12% respectively for each principal component. PC1 showed highest positive correlation with fresh fruit bunch (0.315), bunch number (0.321), oil yield (0.317), kernel yield (0.326), total economic product (0.324), and total oil (0.324) while PC 2 has the largest positive association with oil to wet mesocarp (0.397) and oil to fruit (0.458). The oil palm population were grouped into four distinct clusters based on 20 evaluated traits, this imply that high genetic variation existed in among the germplasm. Cluster 1 contains two populations which are SEN 12 and SEN 10, while cluster 2 has only one population of SEN 3. Cluster 3 consists of three populations which are SEN 4, SEN 6, and SEN 7 while SEN 2 and SEN 5 were grouped in cluster 4. Cluster 4 showed the highest mean value of fresh fruit bunch, bunch number, oil yield, kernel yield, total economic product, and total oil and Cluster 1 was characterized by high oil to wet mesocarp, and oil to fruit. The desired traits that have the largest positive correlation on extracted PCs could be utilized for the improvement of oil palm breeding program. The populations from different clusters with the highest cluster means could be used for hybridization. The information from this study can be utilized for effective conservation and selection of the MPOB-Senegal oil palm germplasm for the future breeding program.

Keywords: cluster analysis, genetic variability, germplasm, oil palm, principal component analysis

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Daniel Pyle, Nicole Pyle, Ben Lignugaris-Kraft, Lawrence Maheady

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Students with disabilities are not included in general education at the same rate as their peers without disabilities. There are multiple reasons cited for why inclusion rates vary, such as teachers' lack of knowledge of the successful delivery of inclusive practices to students with the most extensive support needs. However, decades of research document effective inclusive practices associated with benefits across domains for students with disabilities. One effective inclusive practice that teachers use to improve outcomes for students with disabilities is flexible grouping. Teachers can use flexible grouping to facilitate students working collaboratively by using peer-mediated interventions (PMIs). This article describes PMIs as a flexible grouping of High Leverage Practices (HLP). There are variations of PMIs to select from when using flexible grouping. PMIs are described by varied grouping arrangements and different instructional procedures to clarify the flexibility of grouping students and students’ roles within those groupings. In support of teachers’ use of flexible grouping in inclusive general education classrooms, we identify different PMI formats teachers can use depending on the preferred grouping arrangement, explain the distinctive characteristics of PMI models to distinguish expected procedures with peers, highlight outcomes associated with PMIs, and provide an overview of evaluating PMIs effectiveness.

Keywords: peer-mediated interventions, high leverage practices, flexible grouping, general education, special education

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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