Search results for: short form

Authors: Beverly Redman

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With the Theatre Season of 2020-2021 cancelled due to COVID-19 at Purdue University, Fort Wayne, IN, USA, faculty directors found themselves scrambling to create theatre production opportunities for their students in the Department of Theatre. Redman, Chair of the Department, found her community to be suffering from anxieties brought on by a confluence of issues: the global-scale Covid-19 Pandemic, the United States’ Black Lives Matter protests erupting in cities all across the country and the coming Presidential election, arguably the most important and most contentious in the country’s history. Redman wanted to give her students the opportunity to speak not only on these issues but also to be able to record who they were at this time in their personal lives, as well as in this broad socio-political context. She also wanted to invite them into an experience of feeling empathy, too, at a time when empathy in this world seems to be sorely lacking. Returning to a mode of Devising Theatre she had used with community groups in the past, in which storytelling and re-enactment of participants’ life events combined with oral history documentation practices, Redman planned The Shared Breath Project. The process involved three months of workshops, in which participants alternated between theatre exercises and oral history collection and documentation activities as a way of generating original material for a theatre production. The goal of the first half of the project was for each participant to produce a solo piece in the form of a monologue after many generations of potential material born out of gammes, improvisations, interviews and the like. Along the way, many film and audio clips recorded the process of each person’s written documentation—documentation prepared by the subject him or herself but also by others in the group assigned to listen, watch and record. Then, in the second half of the project—and only once each participant had taken their own contributions from raw improvisatory self-presentations and through the stages of composition and performative polish, participants then exchanged their pieces. The second half of the project involved taking on each other’s words, mannerisms, gestures, melodic and rhythmic speech patterns and inhabiting them through the rehearsal process as their own, thus the title, The Shared Breath Project. Here, in stage two the acting challenges evolved to be those of capturing the other and becoming the other through accurate mimicry that embraces Denis Diderot’s concept of the Paradox of Acting, in that the actor is both seeming and being simultaneous. This paper shares the carefully documented process of making the live-streamed theatre production that resulted from these workshops, writing processes and rehearsals, and forming, The Shared Breath Project, which ultimately took the students’ Realist, life-based pieces and edited them into a single unified theatre production. The paper also utilizes research on the Paradox of Acting, putting a Post-Structuralist spin on Diderot’s theory. Here, the paper suggests the limitations of inhabiting the other by allowing that the other is always already a thing impenetrable but nevertheless worthy of unceasing empathetic, striving and delving in an epoch in which slow, careful attention to our fellows is in short supply.

Keywords: otherness, paradox of acting, oral history theatre, devised theatre, political theatre, community-based theatre, peoples’ theatre

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Syed Aziz Rasool, Ayesha Zaman

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Poverty is one of the most important problems for any developing nation. Workers’ remittances and investment plays a crucial role in development of any country by reducing the poverty level in Pakistan. This research studies the relationship between workers’ remittances and poverty alleviation. It also focused the significant effect on poverty reduction. This study uses time series data for the period of 1972-2013. Autoregressive Distributed Lag (ARDL)Model and Error Correction (ECM)Model has been used in order to find out the long run and short run relationship between the worker’s remittances and poverty level respectively. Thus, inflow of remittances showed the significant and negative impact on poverty level. Moreover, coefficient of error correction model explains the adjustment towards convergence and it has highly significant and negative value. According to this research, Policy makers should strongly focus on positive and effective policies to attract more remittances. JELCODE: JEL: J61

Keywords: ECM, ARDL, AIC, SC

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Authors: Kerri Alderson

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There is pervasive awareness by post secondary faculty that written feedback on course assignments is inconsistently reviewed by students. In order to support student success and growth, a novel method of providing feedback was sought, and screen casting - short, narrated “movies” of audio visual instructor feedback on students’ scholarly papers - was provided as an alternative to traditional means. An overview of the teaching and learning experience as well as the user-friendly software utilized will be presented. This study covers an overview of this more direct, student-centered medium for providing feedback using technology familiar to post secondary students. Reminiscent of direct personal contact, the personalized video feedback is positively evaluated by students as a formative medium for student growth in scholarly writing.

Keywords: education, pedagogy, screen casting, student feedback, teaching and learning

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Authors: Adelakun O. Johnson

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The quest to mitigate the probable adverse effects of geopolitical risk on FDI inflows tends to result in more frequent changes in economic policies and, as a result, heightened policy uncertainty. In this regard, we extend the literature on the dynamics of FDI inflows to include the hypothesis of the possibility of geopolitical risk escalating the adverse effects of economic policy uncertainty on FDI inflows. To test the robustness of this hypothesis, we use the cases of different economic groups characterized by different levels of economic development and varying degrees of FDI confidence. Employing an ARDL-based dynamic panel data model that accounts for both non-stationarity and heterogeneity effects, we show result that suggests GPR and EPU retard the inflows of FDI in both economies but mainly in the short-run situation. In the long run, however, higher EPU not attributed to GPR is likely to boost the inflows of FDI rather than retarding, at least in the case of the G7 economy.

Keywords: FDI inflows, geopolitical risk, economic policy uncertainty, panel ARDL model

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: MIkheil Pipia, Nazibrola Beglarashvili

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Modern anthropogenic changes in climate can affect the microphysical and electrical properties of clouds, such as the conditions that cause intense hail and lightning. At the same time, the effect of the impact largely depends on the physical-geographical conditions and the ecological situation. It should be noted that the growth of anthropogenic pollution in the atmosphere has a significant impact on the dynamics of hail processes. For the statistical analysis of the number of hail days against the background of modern climate change, the average number of hail days at the stations according to decades was used, which allows to weaken short-term fluctuations and reveal long-term changes. In order to determine the dynamics of hail days in Eastern Georgia, the observation data of some meteorological stations from 1951-2000 were analyzed. In total, the data of 41 meteorological stations of Eastern Georgia about hail for the period of 1961-2018 have been processed.

Keywords: climate, meteorology phenomena, anthropocenic influence, hail

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Authors: Patrik Scajev, Pavels Onufrijevs, Algirdas Mekys, Tadas Malinauskas, Dominykas Augulis, Liudvikas Subacius, Kuo-Chih Lee, Jevgenijs Kaupuzs, Arturs Medvids, Hung Hsiang Cheng

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In this study, we focused on the optoelectronic properties of the photodiodes prepared by using 200 nm thick Ge₀.₉₅Sn₀.₀₅ epitaxial layers on Ge/n-Si substrate with aluminum contacts. Photodiodes were formed on non-irradiated and Nd: YAG laser irradiated Ge₀.₉₅Sn₀.₀₅ layers. The samples were irradiated by pulsed Nd: YAG laser with 136.7-462.6 MW/cm² intensity. The photodiodes were characterized by using short laser pulses with the wavelength in the 2.0-2.6 μm range. The laser-irradiated diode was found more sensitive in the long-wavelength range due to laser-induced Sn atoms redistribution providing formation of graded bandgap structure. Sub-millisecond photocurrent relaxation in the diodes revealed their suitability for image sensors. Our findings open the perspective for improving the photo-sensitivity of GeSn alloys in the mid-infrared by pulsed laser processing.

Keywords: GeSn, laser processing, photodetector, infrared

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Authors: Mohammad Reza Ostad Ali Naghi Kashani

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Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing. Although ERP projects are expensive, time consuming, and complex, there are some successful experiences. These days, developing countries are striving to implement ERP projects successfully; however, there are many obstacles. Therefore, these projects would be failed or partially failed. This paper concerns the implementation of a successful ERP implementation, IFS, in Iran at Dana Geophysics Company (DGC). After a short review of ERP and ERP market in Iran, we propose a three phases deployment methodology (phase 1: Preparation and Business Process Management (BPM) phase 2: implementation and phase 3: testing, golive-1 (pilot) and golive-2 (final)). Then, we present five guidelines (Project Management, Change Management, Business Process Management (BPM), Training& Knowledge Management, and Technical Management), which were chose as work streams. In this case study we present lessons learned in Project management and Business process Management.

Keywords: business process management, critical success factors, ERP, project management

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Authors: Pompilia Buzatu, Hazim Qiblawey, Albert Odai, Jana Jamaleddin, Mustafa Nasser, Simon J. Judd

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Membrane bioreactor (MBR) technology is challenged by the tendency for the membrane permeability to decrease due to ‘clogging’. Clogging includes ‘sludging’, the filling of the membrane channels with sludge solids, and ‘ragging’, the aggregation of short filaments to form long rag-like particles. Both sludging and ragging demand manual intervention to clear out the solids, which is time-consuming, labour-intensive and potentially damaging to the membranes. These factors impact on costs more significantly than membrane surface fouling which, unlike clogging, is largely mitigated by the chemical clean. However, practical evaluation of MBR clogging has thus far been limited. This paper presents the results of recent work attempting to quantify sludging and clogging based on simple bench-scale tests. Results from a novel ragging simulation trial indicated that rags can be formed within 24-36 hours from dispersed < 5 mm-long filaments at concentrations of 5-10 mg/L under gently agitated conditions. Rag formation occurred for both a cotton wool standard and samples taken from an operating municipal MBR, with between 15% and 75% of the added fibrous material forming a single rag. The extent of rag formation depended both on the material type or origin – lint from laundering operations forming zero rags – and the filament length. Sludging rates were quantified using a bespoke parallel-channel test cell representing the membrane channels of an immersed flat sheet MBR. Sludge samples were provided from two local MBRs, one treating municipal and the other industrial effluent. Bulk sludge properties measured comprised mixed liquor suspended solids (MLSS) concentration, capillary suction time (CST), particle size, soluble COD (sCOD) and rheology (apparent viscosity μₐ vs shear rate γ). The fouling and sludging propensity of the sludge was determined using the test cell, ‘fouling’ being quantified as the pressure incline rate against flux via the flux step test (for which clogging was absent) and sludging by photographing the channel and processing the image to determine the ratio of the clogged to unclogged regions. A substantial difference in rheological and fouling behaviour was evident between the two sludge sources, the industrial sludge having a higher viscosity but less shear-thinning than the municipal. Fouling, as manifested by the pressure increase Δp/Δt, as a function of flux from classic flux-step experiments (where no clogging was evident), was more rapid for the industrial sludge. Across all samples of both sludge origins the expected trend of increased fouling propensity with increased CST and sCOD was demonstrated, whereas no correlation was observed between clogging rate and these parameters. The relative contribution of fouling and clogging was appraised by adjusting the clogging propensity via increasing the MLSS both with and without a commensurate increase in the COD. Results indicated that whereas for the municipal sludge the fouling propensity was affected by the increased sCOD, there was no associated increased in the sludging propensity (or cake formation). The clogging rate actually decreased on increasing the MLSS. Against this, for the industrial sludge the clogging rate dramatically increased with solids concentration despite a decrease in the soluble COD. From this was surmised that sludging did not relate to fouling.

Keywords: clogging, membrane bioreactors, ragging, sludge

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Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

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An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification

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Authors: Ju-Na Hwang, Min-Hae Park, Kee-Joe Lim

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Many studies have been conducted on DC transmission. Of power apparatus for DC transmission, High Voltage Direct Current (HVDC) cable systems are being evaluated because of the increase in power demand and transmission distance. Therefore, dc insulation characteristics of Liquid Silicone Rubber (LSR), which has various advantages such as short curing time and the ease of maintenance, were investigated to assess its performance as a HVDC insulation material for cable joints. The electrical performance of LSR added to Nano-Aluminum Trihydrate (ATH) was confirmed by measurements of the breakdown strength and electrical conductivity. In addition, field emission scanning electron microscope (FE-SEM) was used as a means of confirmation of nano-filler dispersion state. The LSR nano-composite was prepared by compounding LSR filled nano-sized ATH filler. The DC insulation properties of LSR added to nano-sized ATH fillers were found to be superior to those of the LSR without filler.

Keywords: liquid silicone rubber, nano-composite, HVDC insulation, cable joints

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Authors: Seyyed Mohammad Amin Mousavi Sagharchi, Elham Javanroudi

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Introduction: Tuberculosis (TB) is a known disease with hidden features caused by Mycobacterium tuberculosis (MTB). This disease, which is one of the 10 deadliest in the world, has caused millions of deaths in recent decades. Furthermore, TB is responsible for infecting about 30% population of world. Like any infection, TB can activate the immune system by locating and colonization in the human body, especially in the alveoli. TB is granulomatosis, so MTB can absorb the host’s immune cells and other cells to form granuloma. Method: Different databases (e.g., PubMed) were recruited to prepare this paper and fulfill our goals to search and find effective papers and investigations. Results: Immune response to MTB is related to T cell killers and contains CD1, CD4, and CD8 T lymphocytes. CD1 lymphocytes can recognize glycolipids, which highly exist in the Mycobacterial fatty cell wall. CD4 lymphocytes and macrophages form granuloma, and it is the main line of immune response to Mycobacteria. On the other hand, CD8 cells have cytolytic function for directly killing MTB by secretion of granulysin. Other functions and secretion to the deal are interleukin-12 (IL-12) by induction of expression interferon-γ (INF-γ) for macrophages activation and creating a granuloma, and tumor necrosis factor (TNF) by promoting macrophage phagolysosomal fusion. Conclusion: Immune cells in battle with MTB are macrophages, dendritic cells (DCs), neutrophils, and natural killer (NK) cells. These immune cells can recognize the Mycobacterium by various receptors, including Toll-like receptors (TLRs), Nod-like receptors (NLRs), and C-type lectin receptors (CLRs) located in the cell surface. In human alveoli exist about 50 dendritic macrophages, which have close communication with other immune cells in the circulating system and epithelial cells to deal with Mycobacteria. Against immune cells, MTB handles some factors (e.g., cordfactor, O-Ag, lipoarabinomannan, sulfatides, and adenylate cyclase) and practical functions (e.g., inhibition of macrophages).

Keywords: mycobacterium tuberculosis, immune responses, immunological mechanisms, respiratory tuberculosis

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Authors: Biswanath Swain

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Ethical relativism, as an ethical perspective, holds that moral worth of a course of action is dependent on a particular space and time. Moral rightness or wrongness of a course of action varies from space to space and from time to time. In short, ethical relativism holds that morality is relative to the context. If we reflect conscientiously on the scope of this perspective, we will find that it is wide-spread amongst the marketers involved in the offshore business. However, the irony is that most of the marketers gone along with ethical relativism in their offshore business have been found to be unsuccessful in terms of loss in market-share and bankruptcy. The upshot is purely self-defeating in nature for the marketers. GSK in China and Nestle Maggi in India are some of the burning examples of that sort. The paper argues and recommends that a marketer, as an alternative, should have recourse to Kantian ethical perspective to deliberate courses of action sensitive to offshore business as Kantian ethical perspective is logically and methodologically sound in nature.

Keywords: business, course of action, Kant, morality, offshore, relativism

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Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Mohsen Sanayei, Jerzy Szpunar

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The present study investigates the effects of deformation strain and annealing temperature on the formation of twin boundaries, deformation and recrystallization texture evolution and grain boundary networks and connectivity. The resulting microstructures were characterized using Electron Backscatter Diffraction (EBSD) and X-Ray Diffraction (XRD) both immediately following small amount of deformation and after short time annealing at high temperature to correlate the micro and macro texture evolution of these alloys. Furthermore, this study showed that the process of grain boundary engineering, consisting cycles of deformation and annealing, is found to substantially reduce the mass and size of random boundaries and increase the proportion of low Coincidence Site Lattice (CSL) grain boundaries.

Keywords: coincidence site lattice, grain boundary engineering, electron backscatter diffraction, texture, x-ray diffraction

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Authors: E. Dahlen

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Inflation can be calculated from either the prices of consumer products or from salaries. This paper presents a logical exercise that shows it is easier to calculate inflation from salaries than from consumer products. While the prices of consumer products may change due to technological advancement, such as automation, which must be corrected for, salaries do not. If technological advancements are not accounted for within calculations based on consumer product prices, inflation can be confused with real wage changes, since both inflation and real wage changes affect the prices of consumer products. The method employed in this paper is a logical exercise. Logical arguments are presented that suggest the existence of many different feasible ways by which inflation can be determined. Then a short mathematical exercise will be presented which shows that one of these methods –using salaries – contains the fewest number of unknown parameters, and hence, is the preferred method, since the risk of mistakes is lower. From the results, it can be concluded that salaries, rather than consumer products, should be used to calculate inflation.

Keywords: inflation, logic, math, real wages

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Authors: Geraldine Ambe

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Cameroon is a country in a country in Central Africa. Before the first World War, Germany colonized Cameroon, including some parts of Gabon, Chad, Nigeria, and the Central African Republic. After the war, the United Nations divided most of the colony into Britain and France. In 1960, Eastern Cameroon (‘La Republique du Cameroon’) gained its independence from France while British Southern Cameroons obtained its independence from Britain. The two entities agreed to live together as a federal state officially called the Federal Republic of Cameroon. In 1962, the name of the name of the country was changed from the Federal Republic of Cameroon to the United Republic of Cameroon, while the Prime Minister of Western Cameroon was moved to Yaounde. In 1984, President Paul Biya singlehandedly changed the name to the Republic of Cameroon, implying that Southern Cameroon is not recognized in the union again. From the words of Am Cohen, the two territories came together to form a federal government with one currency, one army, and one foreign policy like states in the United States of America. However, the name Republic of Cameroon (‘La Republique du Cameroun’) does not recognize BSC, and this is exactly what has been practiced: politics of exclusion and excessive centralization in Yaounde. In 2016, teachers and Lawyers started strikes to call the attention of the government on the inhalation of the English culture/people. They were greeted with guns, causing the radicalization of the youths. The civil society came together to form a union to address the issues facing the people, and the government took their leaders and sentenced them to live imprisonment. The consequence was a civil war with nobody to dialogue with. Out of Cameroon, more than half a million people from BSC have been taking dangerous trips through the air, land, and sea. In the jungles and the deserts, the snow of Europe, these people have been seen for the last 4 years. This paper will present some personalities, political fractions, and their stands of decentralization, federalism, and independence as the war continues. The paper will further look at the consequence of this crisis on migration in Central and Eastern Europe.

Keywords: British Southern Cameroons, decolonization, Second World War, dialogue, civil war, immigration

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Authors: Maryam Mousivand

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Subculture is one of the important concepts in social sciences and the field of cultural studies, which falls under the huge concept of culture. In general, subculture is a kind of movement and experience of collective resistance that is manifested by a population as a reaction against the acceptance of official identities approved by custom and society. Subcultures exist in the virtual world in the new era, and they emerged in various forms, such as the emergence of a subculture under common concepts and interests in the form of sites, channels, and groups of virtual space, which will be discussed in this article.

Keywords: subculture, social media, cultural studies, culture

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Authors: Swati Sundararajan, , Asit B. Samui, Prashant S. Kulkarni

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The global energy crisis has led to extensive research on alternative sources of energy. The gap between energy supply and demand can be met by thermal energy storage techniques, of which latent heat storage is most effective in the form of phase change materials (PCMs). Phase change materials utilize latent heat absorbed or released over a narrow temperature range of the material undergoing phase transformation, to store energy. The latent heat can be utilized for heating or cooling purposes. It can also be used for converting to electricity. All these actions amount to minimizing the load on electricity demand. These materials retain this property over repeated number of cycles. Different PCMs differ in the phase change temperature and the heat storage capacities. Poly(ethylene glycol) (PEG) was cross-linked to hydroxyl-terminated poly(dimethyl siloxane) (PDMS) in the presence of cross-linker, tetraethyl orthosilicate (TEOS) and catalyst, dibutyltin dilaurate. Four different ratios of PEG and PDMS were reacted together, and the composition with the lowest PEG concentration resulted in the formation of a flexible solid-solid phase change membrane. The other compositions are obtained in powder form. The enthalpy values of the prepared PCMs were studied by using differential scanning calorimetry and the crystallization properties were analyzed by using X-ray diffraction and polarized optical microscopy. The incorporation of silicone moiety was expected to reduce the hydrophilic character of PEG, which was evaluated by measurement of contact angle. The membrane forming ability of this crosslinked polymer can be extended to several smart packaging, building and textile applications. The detailed synthesis, characterization and performance evaluation of the crosslinked polymer blend will be incorporated in the presentation.

Keywords: phase change materials, poly(ethylene glycol), poly(dimethyl siloxane), thermal energy storage

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Authors: Brajesh Kumar, Luis Cumbal

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An eco-friendly Citrus paradisi peel extract mediated synthesis of TiO2 nanoparticles is reported under sonication. U.V.-vis, Transmission Electron Microscopy, Dynamic Light Scattering and X-ray analyses are performed to characterize the formation of TiO2 nanoparticles. It is almost spherical in shape, having a size of 60–140 nm and the XRD peaks at 2θ = 25.363° confirm the characteristic facets for anatase form. The synthesized nano catalyst is highly active in the decomposition of methyl orange (64 mg/L) in sunlight (~73%) for 2.5 hours.

Keywords: eco-friendly, TiO2 nanoparticles, citrus paradisi, TEM

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Fazeera Ujin, Kamran Shavarebi Ali, Zarina Yasmin Hanur Harith

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This research paper reports on the feasibility and viability of eggshells ash and its effects on the water content and setting time of cement. An experiment was carried out to determine the quantity of water required in order to follow standard cement paste of normal consistency in accordance with MS EN 196-3:2007. The eggshells ash passing the 90µm sieve was used in the investigation. Eggshells ash with percentage of 0%, 0.1%, 0.5%, 1.0%, 1.5% and 2.0% were constituted to replace the cement. Chemical properties of both eggshells ash and cement are compared. From the results obtained, both eggshells ash and cement have the same chemical composition and primary composition which is the calcium compounds. Results from the setting time show that by adding the eggshells ash to the cement, the setting time of the cement decreases. In short, the higher amount of eggshells ash, the faster the rate of setting and apply to all percentage of eggshells ash that were used in this investigation. Both initial and final setting times fulfill the setting time requirements by Malaysian Standard. Hence, it is suggested that eggshells ash can be used as an admixture in concrete mix.

Keywords: construction materials, eggshells ash, solid waste, setting time

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

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Authors: Numra Qayyum, Samina Sarwat, Noor ul Ain

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Bilingual speakers generally can speak both languages with the same competency without mixing them intentionally and making mistakes, but sometimes errors occur in language selection. This quantitative study particularly deals with the language errors made by Urdu-English bilinguals. In this research, researchers have given special attention to the part played by bottom-up priming and top-down cognitive control in these errors. Unstable Urdu-English bilingual participants termed pictures and were prompted to shift from one language to another under the pressure of time. Different situations were given to manipulate the participants. The long and short runs trials of the same language were also given before switching to another language. The study is concluded with the findings that bilinguals made more errors when switching to the first language from their second language, and these errors are large in number, especially when a speaker is switching from L2 (second language) to L1 (first language) after a long run. When the switching is reversed, i.e., from L2 to LI, it had no effect at all. These results gave the clear responsibility of all these errors to top-down cognitive control.

Keywords: bottom up priming, language error, language switching, top down cognitive control

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Authors: Harpa Ragnarsdóttir, Magnús Kjartan Gíslason, Kristín Briem, Guðný Lilja Oddsdóttir

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Introduction: Whiplash-Associated Disorder (WAD) is a health problem characterized by motor, neurological and psychosocial symptoms, stressing the need for a multimodal treatment approach. To achieve individualized multimodal approach, prognostic factors need to be identified early using validated patient-reported and objective outcome measures. The aim of this study is to demonstrate the degree of association between patient-reported and clinical outcome measures of WAD patients in the subacute phase. Methods: Individuals (n=41) with subacute (≥1, ≤3 months) WAD (I-II), medium to high-risk symptoms, or neck pain rating ≥ 4/10 on the Visual Analog Scale (VAS) were examined. Outcome measures included measurements for movement control (Butterfly test) and cervical active range of motion (cAROM) using the NeckSmart system, a computer system using an inertial measurement unit (IMU) that connects to a computer. The IMU sensor is placed on the participant’s head, who receives visual feedback about the movement of the head. Patient-reported neck disability, pain intensity, general health, self-perceived handicap, central sensitization, and difficulties due to dizziness were measured using questionnaires. Excel and R statistical software were used for statistical analyses. Results: Forty-one participants, 15 males (37%), 26 females (63%), mean (SD) age 36.8 (±12.7), underwent data collection. Mean amplitude accuracy (AA) (SD) in the Butterfly test for easy, medium, and difficult paths were 2.4mm (0.9), 4.4mm (1.8), and 6.8mm (2.7), respectively. Mean cAROM (SD) for flexion, extension, left-, and right rotation were 46.3° (18.5), 48.8° (17.8), 58.2° (14.3), and 58.9° (15.0), respectively. Mean scores on the Neck Disability Index (NDI), VAS, Dizziness Handicap Inventory (DHI), Central Sensitization Inventory (CSI), and 36-Item Short Form Survey RAND version (RAND) were 43% (17.4), 7 (1.7), 37 (25.4), 51 (17.5), and 39.2 (17.7) respectively. Females showed significantly greater deviation for AA compared to males for easy and medium Butterfly paths (p<0.05). Statistically significant moderate to strong positive correlation was found between the DHI and easy (r=0.6, p=0.05), medium (r=0.5, p=0.05)) and difficult (r=0.5, p<0.05) Butterfly paths, between the total RAND score and all cAROMs (r between 0.4-0.7, p≤0.05) except flexion (r=0.4, p=0.7), and between the NDI score and CSI (r=0.7, p<0.01), VAS (r=0.5, p<0.01), and DHI (r=0.7, p<0.01) scores respectively. Discussion: All patient-reported and objective measures were found to be outside the reference range. Results suggest females have worse movement control in the neck in the subacute WAD phase. However, no statistical difference based on gender was found in patient-reported measures. Suggesting females might have worse movement control than males in general in this phase. The correlation found between DHI and the Butterfly test can be explained because the DHI measures proprioceptive symptoms like dizziness and eye movement disorders that can affect the outcome of movement control tests. A correlation was found between the total RAND score and cAROM, suggesting that a reduced range of motion affects the quality of life. Significance: The NeckSmart system can detect abnormalities in cAROM, fine movement control, and kinesthesia of the neck. Results suggest females have worse movement control than males. Results show a moderate to a high correlation between several patient-reported and objective measurements.

Keywords: whiplash associated disorders, car-collision, neck, trauma, subacute

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Authors: Marasovic Branka, Aljinovic Zdravka, Poklepovic Tea

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Numerical methods like binomial and trinomial trees and finite difference methods can be used to price a wide range of options contracts for which there are no known analytical solutions. American options are the most famous of that kind of options. Besides numerical methods, American options can be valued with the approximation formulas, like Bjerksund-Stensland formulas from 1993 and 2002. When the value of American option is approximated by Bjerksund-Stensland formulas, the computer time spent to carry out that calculation is very short. The computer time spent using numerical methods can vary from less than one second to several minutes or even hours. However to be able to conduct a comparative analysis of numerical methods and Bjerksund-Stensland formulas, we will limit computer calculation time of numerical method to less than one second. Therefore, we ask the question: Which method will be most accurate at nearly the same computer calculation time?

Keywords: Bjerksund and Stensland approximations, computational analysis, finance, options pricing, numerical methods

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Authors: T. Weber, D. MacKenzie

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The script in this paper describes the use of advanced simulation environment using electronic systems (microcontroller, operational amplifiers, and FPGA). The simulation was used for non-linear dynamic systems behaviour with required observer structure working with parallel real-time simulation based on state-space representation. The proposed deposited model was used for electrodynamic effects including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time and such systems. For further purpose, the spatial temperature distribution may also be used. With upon system, the uncertainties and disturbances may be determined. This provides the estimation of the more precise system states for the required system and additionally the estimation of the ionising disturbances that arise due to radiation effects in space systems. The results have also shown that a system can be developed specifically with the real-time calculation (estimation) of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. TID (Total Ionising Dose) of 1 Gy and Single Effect Transient (SET) free operation up to 50 MeVcm²/mg may assure certain functions. Single-Event Latch-up (SEL) results on the placement of several transistors in the shared substrate of an integrated circuit; ionising radiation can activate an additional parasitic thyristor. This short circuit between semiconductor-elements can destroy the device without protection and measurements. Single-Event Burnout (SEB) on the other hand, increases current between drain and source of a MOSFET and destroys the component in a short time. A Single-Event Gate Rupture (SEGR) can destroy a dielectric of semiconductor also. In order to be able to react to these processes, it must be calculated within a shorter time that ionizing radiation and dose is present. For this purpose, sensors may be used for the realistic evaluation of the diffusion and ionizing effects of the test system. For this purpose, the Peltier element is used for the evaluation of the dynamic temperature increases (dT/dt), from which a measure of the ionization processes and thus radiation will be detected. In addition, the piezo element may be used to record highly dynamic vibrations and oscillations to absorb impacts of charged particle flux. All available sensors shall be used to calibrate the spatial distributions also. By measured value of size and known location of the sensors, the entire distribution in space can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms.

Keywords: cattle, biochar, manure, microbial activity

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Authors: Bharat Singh Deora, Sushma Satpute

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Cloud computing is based on resource sharing. Like other resources which can be shareable, storage is a resource which can be shared. We can use collective resources of storage from different locations and maintain a central index table for storage details. The storage combining of different places can form a suitable data storage which is operated from one location and is very economical. Proper storage of data should improve data reliability & availability and bandwidth utilization. Also, we are moving the contents of one storage to other according to our need.

Keywords: cloud computing, cloud storage, Iaas, PaaS, SaaS

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Authors: Vinayaka Gude Divya Sampath

Abstract:

The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

Procedia PDF Downloads 147