Search results for: flight test data

Authors: Lucia Carrion Gordon, Maria Gabriela Lopez Yanez

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This project focuses on heritage concepts and their importance in every evolving and changing Digital Era where system solutions have to be sustainable, efficient and suitable to the basic needs. The prototype has to cover the principal requirements for the case studies. How to preserve the sociological ideas of dances in Ecuador like ‘La Bomba’ is the best example and challenge to preserve the intangible data. The same idea is applicable with books and music. The History and how to keep it, is the principal mission of Heritage Preservation. The dance of La Bomba is rooted on a specific movement system whose main part is the sideward hip movement. La Bomba´s movement system is the surface manifestation of a whole system of knowledge whose principal characteristics are the historical relation of Chote˜nos with their land and their families.

Keywords: digital preservation, heritage, IT management, data, metadata, ontology, serendipity

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Authors: Durvi Yogesh Vagani

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This research paper explores the effectiveness of Research-informed teaching and Case-based teaching in enhancing the retention and recall of memory during discussions among university students. Additionally, it investigates the impact of using Artificial Intelligence (AI) tools on the quality of research conducted by students and its correlation with better recollection. The study hypothesizes that Case-based teaching will lead to greater recall and storage of information. The research gap in the use of AI in educational settings, particularly with actual participants, is addressed by leveraging a multi-method approach. The hypothesis is that the use of AI, such as ChatGPT and Bard, would lead to better retention and recall of information. Before commencing the study, participants' attention levels and IQ were assessed using the Digit Span Test and the Wechsler Adult Intelligence Scale, respectively, to ensure comparability among participants. Subsequently, participants were divided into four conditions, each group receiving identical information presented in different formats based on their assigned condition. Following this, participants engaged in a group discussion on the given topic. Their responses were then evaluated against a checklist. Finally, participants completed a brief test to measure their recall ability after the discussion. Preliminary findings suggest that students who utilize AI tools for learning demonstrate improved grasping of information and are more likely to integrate relevant information into discussions compared to providing extraneous details. Furthermore, Case-based teaching fosters greater attention and recall during discussions, while Research-informed teaching leads to greater knowledge for application. By addressing the research gap in AI application in education, this study contributes to a deeper understanding of effective teaching methodologies and the role of technology in student learning outcomes. The implication of the present research is to tailor teaching methods based on the subject matter. Case-based teaching facilitates application-based teaching, and research-based teaching can be beneficial for theory-heavy topics. Integrating AI in education. Combining AI with research-based teaching may optimize instructional strategies and deepen learning experiences. This research suggests tailoring teaching methods in psychology based on subject matter. Case-based teaching suits practical subjects, facilitating application, while research-based teaching aids understanding of theory-heavy topics. Integrating AI in education could enhance learning outcomes, offering detailed information tailored to students' needs.

Keywords: artificial intelligence, attention, case-based teaching, memory recall, memory retention, research-informed teaching

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Dêivisson Alves Anjos, Blenda Fonseca Aires Teles, Queitiane Castro Costa

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Fire is one of the biggest dangers for factories, warehouses, mills, among other places, causing unimaginable damage, because besides the material damage also directly affects the lives of workers who are likely to suffer death or very serious consequences. This protection of the lives of these people should be taken seriously, always seeking safety. Thus investment in security and monitoring equipment must be high, so you can prevent or reduce the impacts of a possible fire. Our device, made in PIC micro controller monitors the temperature and the presence of gas in the environment, it sends the data via Bluetooth device to a developed in LabVIEW interface saves these data continuously and alert if the temperature exceeds the allowed or some gas is detected. Currently the device is in operation and can perform several tests, as well as use in different areas for which you need anti-fire protection.

Keywords: pic, bluetooth, fire, temperature, gas, LabVIEW

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization

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Authors: T. Hamaishi, Y. Morinaga, H. Morita

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Introduction: Rice consumption in Japan has decreased, and Japanese government has recommended use of rice flour in order to expand the consumption of rice. There are two major protein components present in flour, called gliadin and glutenin. Gluten forms when water is added to flour and is mixed. As mixing continues, glutenin interacts with gliadin to form viscoelastic matrix of gluten. Rice flour bread does not expand as much as wheat flour bread. Because rice flour is not included gluten, it cannot construct gluten network in the dough. In recent years, some food additives have been used for dough-improving agent in bread making, especially surfactants has effect in order to improve dough extensibility. Therefore, we focused to fatty acid salt which is one of anionic surfactants. Fatty acid salt is a salt consist of fatty acid and alkali, it is main components of soap. According to JECFA(FAO/WHO Joint Expert Committee on Food Additives), salts of Myristic(C14), Palmitic(C16) and Stearic(C18) could be used as food additive. They have been evaluated ADI was not specified. In this study, we investigated to improving bread-making properties of rice flour dough adding fatty acid salt. Materials and methods: The sample of fatty acid salt is myristic (C14) dissolved in KOH solution to a concentration of 350 mM and pH 10.5. Rice dough was consisted of 100 g of flour using rice flour and wheat gluten, 5 g of sugar, 1.7 g of salt, 1.7g of dry yeast, 80 mL of water and fatty acid salt. Mixing was performed for 500 times by using hand. The concentration of C14K in the dough was 10 % relative to flour weight. Amount of gluten in the dough was 20 %, 30 % relative to flour weight. Dough expansion ability test was performed to measure physical property of bread dough according to the methods of Baker’s Yeast by Japan Yeast Industry Association. In this test, 150 g of dough was filled from bottom of the cylinder and fermented at 30 °C，85 % humidity for 120 min on an incubator. The height of the expansion in the dough was measured and determined its expansion ability. Results and Conclusion: Expansion ability of rice dough with gluten content of 20 %, 30% showed 316 mL, 341 mL for 120 min. When C14K adding to the rice dough, dough expansion abilities were 314 mL, 368 mL for 120 min, there was no significant difference. Conventionally it has been known that the rice flour dough contain gluten of 20 %. The considerable improvement of dough expansion ability was achieved when added C14K to wheat flour. The experimental result shows that c14k adding to the rice dough with gluten content more than 20 % was not improving bread-making properties. In conclusion, rice bread made with gluten content more than 20 % without C14K has been suggested to contribute to the formation of the sufficient gluten network.

Keywords: expansion ability, fatty acid salt, gluten, rice flour dough

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Authors: Fatma Acheuk, Idir Bitam, Leila Bendifallah, Malika Ramdani, Fethia Barika

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Phytochemical study of the plant Artemisia judaica showed the presence of various groups of natural products: saponins, tannins, coumarins, flavonoids, carbohydrates, and reducer compounds. However alkaloids are present as traces. The crude ethanol extract of the test plant presented significant insecticidal activity on mosquito larvae in stage I, II, and III. The LD50 highlighted the excellent insecticidal effect of the tested extract. Similarly, the LT50 are achieved early with high doses. The results obtained are encouraging and suggest the possibility of using the secondary metabolites of this plant such as bio-insecticide.

Keywords: Atamisia judaica, crud extract, mosquito, insecticidal activity

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Authors: Sara Ali Alokley, Mansour Saleh Albarrak

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This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

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Authors: Nawaporn Thongnut

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The objective was to study the process and how to prepare the accounting of the Thai temples and to study the performance and quality in the accounting preparation of the temples in accordance with the regulation. The population was the accountants and individuals involved in the accounting preparation of 17 temples in the suburban Bangkok. The measurement used in this study was questionnaire. The statistics used in the analysis are the descriptive statistic. The data was presented in the form of percentage tables to describe the data on the demographic characteristics. The study found that temple wardens were responsible for the accounting and reporting of the temples. Abbots were to check the accuracy of the accounts in the monasteries. Mostly, there was no account auditing of the monasteries from the outside. The practice when receiving income for most of the monasteries had been keeping financial document in an orderly manner.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Man Guo, Wenyong Tan

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By combining spatial syntax with data obtained from field visits, this paper interprets the internal relationship between spatial morphology and spatial cognition in Lidukou Village. By comparing the obtained data, it is recognized that the spatial integration degree of Lidukou Village is positively correlated with the spatial cognitive intention of local villagers. The part with a higher spatial cognitive degree within the village is distributed along the axis mainly composed of Shuxiang Road. And the accessibility of historical relics is weak, and there is no systematic relationship between them. Aiming at the morphological problem of Lidukou Village, optimization strategies have been proposed from multiple perspectives, such as optimizing spatial mechanisms and shaping spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: A.D. Susanti, W. B. Sediawan, S.K. Wirawan, Budhijanto, Ritmaleni

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Oryzanol content in rice bran oil (RBO) naturally has high antioxidant activity. Its reviewed has several health properties and high interested in pharmacy, cosmetics, and nutrition’s. Because of the low concentration of oryzanol in crude RBO (0.9-2.9%) then its need to be further processed for practical usage, such as via adsorption process. In this study, investigation and adjustment of adsorption equilibrium models were conducted through the kinetic data approachments. Mathematical modeling on kinetics of batch adsorption of oryzanol separation from RBO has been set-up and then applied for equilibrium results. The size of adsorbent particles used in this case are usually relatively small then the concentration in the adsorbent is assumed to be not different. Hence, the adsorption rate is controlled by the rate of oryzanol mass transfer from the bulk fluid of RBO to the surface of silica gel. In this approachments, the rate of mass transfer is assumed to be proportional to the concentration deviation from the equilibrium state. The equilibrium models applied were Langmuir, coefficient distribution, and Freundlich with the values of the parameters obtained from equilibrium results. It turned out that the models set-up can quantitatively describe the experimental kinetics data and the adjustment of the values of equilibrium isotherm parameters significantly improves the accuracy of the model. And then the value of mass transfer coefficient per unit adsorbent mass (kca) is obtained by curve fitting.

Keywords: adsorption equilibrium, adsorption kinetics, oryzanol, rice bran oil

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Authors: Hsin-Ping Huang, Shyankay Jou

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Resistive switching of aluminum nitride (AlNx) thin film was demonstrated in a TaN/AlNx/TiN memory cell that was prepared by sputter deposition techniques. The memory cell showed bipolar switching of resistance between +3.5 V and –3.5 V. The resistance ratio of high resistance state (HRS) to low resistance state (HRS), RHRS/RLRS, was about 2 over 100 cycles of endurance test. Both the LRS and HRS of the memory cell exhibited ohmic conduction at low voltages and Poole-Frenkel emission at high voltages. The electrical conduction in the TaN/AlNx/TiN memory cell was possibly attributed to the interactions between charges and defects in the AlNx film.

Keywords: aluminum nitride, nonvolatile memory, resistive switching, thin films

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

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Authors: M. Hijazi, A. Zeki, A. Ismail

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An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This paper presents a review on the published researches of Arabic Text Classification using classical data representation, Bag of words (BoW), and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.

Keywords: Arabic text classification, Arabic WordNet, bag of words, conceptual representation, semantic relations

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Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

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Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

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The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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Authors: Elisavet Arsenaki

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Paracetamol overdose is associated with significant and possibly permanent consequences including hepatotoxicity, acute and chronic liver failure, and death. This quality improvement project explores the prevalence of accidental iatrogenic paracetamol overdose in hospital patients with a low body weight, defined as <50kg and assesses the impact of educational posters in trying to reduce it. The study included all adult inpatients on the admissions ward, a short stay ward for patients requiring 12-72 hour treatment, and consisted of three cycles. Each cycle consisted of 3 days of data collection in a given month (data collection for cycle 1 occurred in January 2022, February 2022 for cycle 2 and March 2022 for cycle 3). All patients given paracetamol had their prescribed dose checked against their charted weight to identify the percentage of adult inpatients <50kg who were prescribed 1g of paracetamol instead of 500mg. In the first cycle of the audit, data were collected from 83 patients who were prescribed paracetamol on the admissions ward. Subsequently, four A4 educational posters were displayed across the ward, on two separate occasions and with a one-month interval in between each poster display. The aim of this was to remind prescribing doctors of their responsibility to check patient body weight prior to prescribing paracetamol. Data were collected again one week after each round of poster display, from 72 and 70 patients respectively. Over the 3 cycles with a cumulative 225 patients, 15 weighed <50kg (6.67%) and of those, 5 were incorrectly prescribed 1g of paracetamol, yielding a 33.3% prevalence of accidental iatrogenic paracetamol overdose in adult inpatients. In cycle 1 of the project, 3 out of 6 adult patients weighing <50kg were overdosed on paracetamol, meaning that 50% of low weight patients were prescribed the wrong dose of paracetamol for their weight. In the second data collection cycle, 1 out of 5 <50kg patients were overdosed (20%) and in the third cycle, 1 out of 4 (25%). The use of educational posters resulted in a lower prevalence of accidental iatrogenic paracetamol overdose in low body weight adult inpatients. However, the differences observed were statistically insignificant (p value 0.993 and 0.995 respectively). Educational posters did not induce a significant decrease in the prevalence of accidental iatrogenic paracetamol overdose. More robust strategies need to be employed to further decrease paracetamol overdose in patients weighing <50kg.

Keywords: iatrogenic, overdose, paracetamol, patient, safety

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Authors: Sautma Ronni Basana, Zeplin Jiwa Husada Tarigan, Widjojo Suprapto

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Companies have already implemented the Enterprise Resource Planning (ERP) system to increase the data integration so that they can improve their business performance. Although some companies have managed to implement the ERP well, they still need to improve gradually so that the ERP functions can be optimized. To obtain a faster and more accurate data, the key users and IT department have to customize the process to suit the needs of the company. In reality, sustaining the ERP technology system requires soft and hard ERP so it enables to improve the business performance of the company. Soft and hard ERP are needed to build a tough system to ensure the integration among departments running smoothly. This research has three questions. First, is the soft ERP bringing impacts to the hard ERP and system integration. Then, is the hard ERP having impacts to the system integration. Finally, is the business performance of the manufacturing companies is affected by the soft ERP, hard ERP, and system integration. The questionnaires are distributed to 100 manufacturing companies in East Java, and are collected from 90 companies which have implemented the ERP, with the response rate of 90%. From the data analysis using PLS program, it is obtained that the soft ERP brings positive impacts to the hard ERP and system integration for the companies. Then, the hard ERP brings also positive impacts to the system integration. Finally, the business process performance of the manufacturing companies is affected by the system integration, soft ERP, and hard ERP simultaneously.

Keywords: soft ERP, hard ERP, system integration, business performance

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Authors: Gonzalo García-Reyes

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Conformastat spherically symmetric exact solutions of Einstein's field equations representing matter distributions made of fluid both perfect and anisotropic from given solutions of Poisson's equation of Newtonian gravity are investigated. The approach is used in the construction of new relativistic models of thick spherical shells and three-component models of galaxies (bulge, disk, and dark matter halo), writing, in this case, the metric in cylindrical coordinates. In addition, the circular motion of test particles (rotation curves) along geodesics on the equatorial plane of matter configurations and the stability of the orbits against radial perturbations are studied. The models constructed satisfy all the energy conditions.

Keywords: general relativity, exact solutions, spherical symmetry, galaxy, kinematics and dynamics, dark matter

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Authors: Eno Jah Tabogo

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The aim of this research is to identify and examine current deficiencies in entrepreneurial training in improving the performance of small businesses in sub Saharan Africa economies. This research achieves this by examining the course content, training methods, and profiles of trainers and trainees of small business service providers in Sub Saharan Africa (SSA) to identify training deficiencies in improving small businesses. Data was for the analysis was collected from a sample of four entrepreneurial training providers in SSA. These four providers served an average of 1,500 trainees. Questionnaire was used to collect data via face to face and through telephone. Face validity was determined by distributing the questionnaire among a group of colleagues, followed by a group discussion to strengthen the validity of the questionnaire. Interviews were also held with managers of training programs. Content and descriptive statistics was used to analyse the data collected. The results indicated only 25% of the training content were entrepreneurial. In terms of service provided, both business, entrepreneurial, technical and after-care services were identified. It was also discovered that owners of training firms had no formal entrepreneurship background. The paper contributes by advocating for a comprehensive entrepreneurship-training program for successful small business enterprises. Recommendations that could help sustain emerging small business enterprises and direction for further research are presented.

Keywords: entrepreneurship, emerging markets, small business, training

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Authors: Cahyaningsih Cahyaningsih, Fu'ad Rakhman

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This study examines empirically the association between corporate social responsibility (CSR) and tax avoidance. This study also investigates the effect of earnings on the relation between CSR and tax avoidance. Effective tax rate (ETR) and cash effective tax rate (CETR) were used to measure tax avoidance. Corporate social responsibility fund (CSRF) and corporate social responsibility disclosure (CSRD) were used as proxies for CSR. Test was conducted for public firms which were listed in the Indonesia Stock Exchange during the period of 2011-2014. Based on slack resource theory, this study finds that the relation between CSR and tax avoidance is moderated by earnings.

Keywords: corporate social responsibility disclosure, corporate social responsibility fund, earnings, tax avoidance

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Authors: Olajumoke Adetoun Ojeleye

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The study assessed the safety culture, mindfulness and safe behaviors of students residing in the halls of residence of Obafemi Awolowo University (OAU), Ile Ife, Nigeria. The objectives of the study were to assess the level of safety mindfulness of students residing in the halls of residence of OAU, examine their safety culture and establish whether these students are involved in unsafe practices. The study employed a cross-sectional research design and instrument used for data collection was a self-structured, self-administered questionnaire. The questionnaire was tested for validity and reliability with its reliability coefficient at 0.71 before being used for data collection. Respondents were selected by multi-stage sampling technique and the sample size was 530. Data collection took 2 weeks and analysed using descriptive statistical techniques. Results showed that about half of the respondents’ population (49.8%) was between the ages of 20-24 years. There were more males (56.2%) than females (43.8%). Although data demonstrated that majority (91.7%) of the respondents are highly safety minded and the safety culture of an equally high proportion (83.4%) was adjudged fair, a lot of improvement is needed in the area of alerting or informing management of impending dangers and studying the hall handbook to internalize its contents. The study further showed that only 43.6% of respondents had good safety practices and behaviors and majority (56.4%) had fair safety practices and behaviors. One accidental discovery of the study is the finding that not a few of the students squat their counterparts. The study recommended the establishment of clearly written out complaint procedure that is accessible and available to all hall residents, building more hostels with adequate facilities to address the issue of overcrowding and also putting systems in place in order to encourage residents to report incidences/accidents.

Keywords: safe behaviours, safety culture, safety mindfulness, student

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Authors: Arijit Saha, Hassan Kassem, Leo Hoening

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Ongoing climate change demands the increasing use of renewable energies. Wind energy plays an important role in this context since it can be applied almost everywhere in the world. To reduce the costs of wind turbines and to make them more competitive, simulations are very important since experiments are often too costly if at all possible. The wind turbine on a vast open area experiences the turbulence generated due to the atmosphere, so it was of utmost interest from this research point of view to generate the turbulence through various Inlet Turbulence Generation methods like Precursor cyclic and Kaimal Spectrum Exponential Coherence (KSEC) in the computational simulation domain. To be able to validate computational fluid dynamic simulations of wind turbines with the experimental data, it is crucial to set up the conditions in the simulation as close to reality as possible. This present work, therefore, aims at investigating the turbulent inflow strategy and boundary conditions of KSEC and providing a comparative analysis alongside the Precursor cyclic method for Large Eddy Simulation within the context of wind energy applications. For the generation of the turbulent box through KSEC method, firstly, the constrained data were collected from an auxiliary channel flow, and later processing was performed with the open-source tool PyconTurb, whereas for the precursor cyclic, only the data from the auxiliary channel were sufficient. The functionality of these methods was studied through various statistical properties such as variance, turbulent intensity, etc with respect to different Bulk Reynolds numbers, and a conclusion was drawn on the feasibility of KSEC method. Furthermore, it was found necessary to verify the obtained data with DNS case setup for its applicability to use it as a real field CFD simulation.

Keywords: Inlet Turbulence Generation, CFD, precursor cyclic, KSEC, large Eddy simulation, PyconTurb

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

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Authors: Zahra Sadeghian

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This paper reports on the geometrical parameters optimized of the stationary point for the 2,3-Bis(furan-2-yl)pyrazino[2,3-f][1,10]phenanthroline. The calculations are performed using density functional theory (DFT) method at the B3LYP/LanL2DZ level. We determined bond lengths and bond angles values for the compound and calculate the amount of bond hybridization according to the natural bond orbital theory (NBO) too. The energy of frontier orbital (HOMO and LUMO) are computed. In addition, calculated data are accurately compared with the experimental result. This comparison show that the our theoretical data are in reasonable agreement with the experimental values.

Keywords: 2, 3-Bis(furan-2-yl)pyrazino[2, 3-f][1, 10]phenanthroline, density functional theory, theorical calculations, LanL2DZ level, B3LYP level

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Authors: Rodrigo Fernandes da Silva, Daniela Maira Cardozo, Paulo Cesar Martins Alves, Sophie Françoise Derchain, Fernando Guimarães

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T-reg lymphocytes are important for the control of peripheral tolerance. They control the adaptive immune system and prevent autoimmunity through its suppressive action on CD4+ and CD8+ lymphocytes. The suppressive action also includes B lymphocytes, dendritic cells, monocytes/macrophages and recently, studies have shown that T-reg are also able to inhibit NK cells, therefore they exert their control of the immune response from innate to adaptive response. Most tumors express self-ligands, therefore it is believed that T-reg cells induce tolerance of the immune system, hindering the development of successful immunotherapies. T-reg cells have been linked to the suppression mechanisms of the immune response against tumors, including ovarian cancer. The goal of this study was to disclose the sub-population of the expanded CD3+ lymphocytes reported by previous studies, using the long-term culture model designed by Carlens et al 2001, to generate effector cell suspensions enriched with cytotoxic CD3-CD56+ NK cells, from PBMC of ovarian neoplasia patients. Methods and Results: Blood was collected from 12 patients with ovarian neoplasia after signed consent: 7 benign (Bng) and 5 malignant (Mlg). Mononuclear cells were separated by Ficoll-Paque gradient. Long-term culture was conducted by a 21 day culturing process with SCGM CellGro medium supplemented with anti-CD3 (10ng/ml, first 5 days), IL-2 (1000UI/ml) and FBS (10%). After 21 days of expansion, there was an increase in the population of CD3+ lymphocytes in the benign and malignant group. Within CD3+ population, there was a significant decrease in the population of CD4+ lymphocytes in the benign (median Bgn D-0=73.68%, D-21=21.05%) (p<0.05) and malignant (median Mlg D-0=64.00%, D-21=11.97%) (p < 0.01) group. Inversely, after 21 days of expansion, there was an increase in the population of CD8+ lymphocytes within the CD3+ population in the benign (median Bgn D-0=16.80%, D-21=38.56%) and malignant (median Mlg D-0=27.12%, D-21=72.58%) group. However, this increase was only significant on the malignant group (p<0.01). Within the CD3+CD4+ population, there was a significant increase (p < 0.05) in the population of T-reg lymphocytes in the benign (median Bgn D-0=9.84%, D-21=39.47%) and malignant (median Mlg D-0=3.56%, D-21=16.18%) group. Statistical analysis inter groups was performed by Kruskal-Wallis test and intra groups by Mann Whitney test. Conclusion: The CD4+ and CD8+ sub-population of CD3+ lymphocytes shifts with the culturing process. This might be due to the process of the immune system to produce a cytotoxic response. At the same time, T-reg lymphocytes increased within the CD4+ population, suggesting a modulation of the immune response towards cells of the immune system. The expansion of the T-reg population can hinder an immune response against cancer. Therefore, an immunotherapy using this expansion procedure should aim to halt the expansion of T-reg or its immunosuppresion capability.

Keywords: regulatory T cells, CD8+ T cells, CD4+ T cells, NK cell expansion

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Authors: C. Busuioc, S. Jinga, E. Pavel

Abstract:

Optical lithography is a key technique in the development of sub-5 nm patterns for the semiconductor industry. We have already reported that the best results obtained with respect to direct laser writing process on active media, such as glass-ceramics, are achieved only when the energy of the laser radiation is absorbed in discrete quantities. Further, we need to clarify the role of active centers concentration in silver nanocrystals natural generation, as well as in fluorescent rare-earth nanostructures formation. As a consequence, samples with different compositions were prepared. SEM, AFM, TEM and STEM investigations were employed in order to demonstrate that few nm width lines can be written on fluorescent photosensitive glass-ceramics, these being efficient absorbers. Moreover, we believe that the experimental data will lead to the best choice in terms of active centers amount, laser power and glass-ceramic matrix.

Keywords: glass-ceramics, 3D laser writing, optical disks, data storage

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

Abstract:

The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

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Authors: Abderrazak Bannari, Ghadeer Kadhem

Abstract:

The objectives of this paper are the validation and the evaluation of MBES-CARIS BASE surface data performance for bathymetric mapping of shallow water in the Kingdom of Bahrain. The latter is an archipelago with a total land area of about 765.30 km², approximately 126 km of coastline and 8,000 km² of marine area, located in the Arabian Gulf, east of Saudi Arabia and west of Qatar (26° 00’ N, 50° 33’ E). To achieve our objectives, bathymetric attributed grid files (X, Y, and depth) generated from the coverage of ship-track MBSE data with 300 x 300 m cells, processed with CARIS-HIPS, were downloaded from the General Bathymetric Chart of the Oceans (GEBCO). Then, brought into ArcGIS and converted into a raster format following five steps: Exportation of GEBCO BASE surface data to the ASCII file; conversion of ASCII file to a points shape file; extraction of the area points covering the water boundary of the Kingdom of Bahrain and multiplying the depth values by -1 to get the negative values. Then, the simple Kriging method was used in ArcMap environment to generate a new raster bathymetric grid surface of 30×30 m cells, which was the basis of the subsequent analysis. Finally, for validation purposes, 2200 bathymetric points were extracted from a medium scale nautical map (1:100 000) considering different depths over the Bahrain national water boundary. The nautical map was scanned, georeferenced and overlaid on the MBES-CARIS generated raster bathymetric grid surface (step 5 above), and then homologous depth points were selected. Statistical analysis, expressed as a linear error at the 95% confidence level, showed a strong correlation coefficient (R² = 0.96) and a low RMSE (± 0.57 m) between the nautical map and derived MBSE-CARIS depths if we consider only the shallow areas with depths of less than 10 m (about 800 validation points). When we consider only deeper areas (> 10 m) the correlation coefficient is equal to 0.73 and the RMSE is equal to ± 2.43 m while if we consider the totality of 2200 validation points including all depths, the correlation coefficient is still significant (R² = 0.81) with satisfactory RMSE (± 1.57 m). Certainly, this significant variation can be caused by the MBSE that did not completely cover the bottom in several of the deeper pockmarks because of the rapid change in depth. In addition, steep slopes and the rough seafloor probably affect the acquired MBSE raw data. In addition, the interpolation of missed area values between MBSE acquisition swaths-lines (ship-tracked sounding data) may not reflect the true depths of these missed areas. However, globally the results of the MBES-CARIS data are very appropriate for bathymetric mapping of shallow water areas.

Keywords: bathymetry mapping, multibeam echosounder systems, CARIS-HIPS, shallow water

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Authors: Byomakesh Debata, Jitendra Mahakud

Abstract:

The recent financial crisis has been characterized by massive monetary policy interventions by the Central bank, and it has amplified the importance of liquidity for the stability of the stock market. This paper empirically elucidates the actual impact of monetary policy interventions on stock market liquidity covering all National Stock Exchange (NSE) Stocks, which have been traded continuously from 2002 to 2015. The present study employs a multivariate VAR model along with VAR-granger causality test, impulse response functions, block exogeneity test, and variance decomposition to analyze the direction as well as the magnitude of the relationship between monetary policy and market liquidity. Our analysis posits a unidirectional relationship between monetary policy (call money rate, base money growth rate) and aggregate market liquidity (traded value, turnover ratio, Amihud illiquidity ratio, turnover price impact, high-low spread). The impulse response function analysis clearly depicts the influence of monetary policy on stock liquidity for every unit innovation in monetary policy variables. Our results suggest that an expansionary monetary policy increases aggregate stock market liquidity and the reverse is documented during the tightening of monetary policy. To ascertain whether our findings are consistent across all periods, we divided the period of study as pre-crisis (2002 to 2007) and post-crisis period (2007-2015) and ran the same set of models. Interestingly, all liquidity variables are highly significant in the post-crisis period. However, the pre-crisis period has witnessed a moderate predictability of monetary policy. To check the robustness of our results we ran the same set of VAR models with different monetary policy variables and found the similar results. Unlike previous studies, we found most of the liquidity variables are significant throughout the sample period. This reveals the predictability of monetary policy on aggregate market liquidity. This study contributes to the existing body of literature by documenting a strong predictability of monetary policy on stock liquidity in an emerging economy with an order driven market making system like India. Most of the previous studies have been carried out in developing economies with quote driven or hybrid market making system and their results are ambiguous across different periods. From an eclectic sense, this study may be considered as a baseline study to further find out the macroeconomic determinants of liquidity of stocks at individual as well as aggregate level.

Keywords: market liquidity, monetary policy, order driven market, VAR, vector autoregressive model

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