Search results for: large language models

Authors: Puneet Katyal, Punit Kumar

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A great deal of efforts has been done in the field of thermal effects in electrohydrodynamic lubrication (TEHL) during the last five decades. The focus was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of TEHL model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology and thermal conductivity in EHL point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. Using a simplified thermal EHL model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed TEHL characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for correct lubricant behaviour.

Keywords: TEHL, shear thinning, rheology, conductivity

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Authors: Oluseyi Adunola Bamisaiye

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The frequency of occurrence of earth tremor in Nigeria has increased tremendously in recent years. Slow earthquakes/ tremor have preceded some large earthquakes in some other regions of the world and the Nigerian case may not be an exception. Timely and careful investigation of these tremors may reveal their relation to large earthquakes and provides important clues to constrain the slip rates on tectonic faults. Thus making it imperative to keep under watch and also study carefully the tectonically active terrains within the country, in order to adequately forecast, prescribe mitigation measures and in order to avoid a major disaster. This report provides new evidence of a slow slip transient in a strongly locked seismogenic zone of the Okemesi fold belt. The aim of this research is to investigate the different methods of earth tremor monitoring using fault slip analysis and mapping of Okemesi hills, which has been the most recent epicenter to most of the recent tremors.

Keywords: earth tremor, fault slip, intraplate activities, plate tectonics

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Authors: Seyed Hamed Hashemi Sohi, Gerald Jo Denoga

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Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation.

Keywords: metal cutting, smoothed particle hydrodynamics, constitutive models, experimental, cutting forces analyses

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Authors: R. W. Chan, Kan Kan Chan

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Augmented Reality (AR), with the affordance of bridging between real world and virtual world, brings users immersive experience. It has been applied in education gradually and even come into practice in student daily learning. However, a systematic review shows that there are limited researches in the area of vocabulary acquisition in early childhood education. Since kindergarten is a key stage where children acquire language and AR as an emerging and potential technology to support the vocabulary acquisition, this study aims to explore its value in in real classroom with teacher’s view. Participants were a class of 5 to 6 years old kids studying in a Macau school that follows Cambridge curriculum and emphasizes multicultural ethos. There were 11 boys, 13 girls, and in a total of 24 kids. They learnt animal vocabulary using mobile device and AR flashcards, IPad to scan AR flashcards and interact with pop-up virtual objects. In order to estimate the effectiveness of using Augmented Reality, children attended vocabulary pre-posttest. In addition, teacher interview was administrated after this learning activity to seek practitioner’s opinion towards this technology. For data analysis, paired samples t-test was utilized to measure the instructional effect based on the pre-posttest data. Result shows that Augmented Reality could significantly enhance children vocabulary learning with large effect size. Teachers indicated that children enjoyed the AR learning activity but clear instruction is needed. Suggestions for the future implementation of vocabulary acquisition using AR are suggested.

Keywords: augmented reality, kindergarten children, vocabulary learning, Macau

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Mary Rosa Espinosa-Ochoa

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The study of overgeneralization in inflectional morphology provides evidence for understanding how a child's mind works when applying linguistic patterns in a novel way. High-frequency inflectional forms in the input cause inappropriate use in contexts related to lower-frequency forms. Children learn verbs as lexical items and new forms develop only gradually, around their second year: most of the utterances that children produce are closely related to what they have previously produced. Spanish has a complex verbal system that inflects for person, mood, and tense. Approximately 200 verbs are irregular, and bare roots always require an inflected form, which represents a challenge for the memory. The aim of this research is to investigate i) what kinds of overgeneralization errors children make in verb production, ii) to what extent these errors are related to verb forms previously produced, and iii) whether the overgeneralized verb components are also frequent in children’s linguistic inventory. It consists of a high-density longitudinal study of a middle-class girl (1;11,24-2;02,24) from Mexico City, whose utterances were recorded almost daily for three months to compile a unique corpus in the Spanish language. Of the 358 types of inflected verbs produced by the child, 9.11% are overgeneralizations. Not only are inflected forms (verbal and pronominal clitics) overgeneralized, but also verbal roots. Each of the forms can be traced to previous utterances, and they show that the child is detecting morphological patterns. Neither verbal roots nor inflected forms are associated with high frequency patterns in her own speech. For example, the child alternates the bare roots of an irregular verb, cáye-te* and cáiga-te* (“fall down”), to express the imperative of the verb cá-e-te (fall down.IMPERATIVE-PRONOMINAL.CLITIC), although cay-ó (PAST.PERF.3SG) is the most frequent form of her previous complete inventory, and the combined frequency of caer (INF), cae (PRES.INDICATIVE.3SG), and caes (PRES.INDICATIVE.2SG) is the same as that of as caiga (PRES.SUBJ.1SG and 3SG). These results provide evidence that a) two forms of the same verb compete in the child’s memory, and b) although the child uses her own inventory to create new forms, these forms are not necessarily frequent in her memory storage, which means that her mind is more sensitive to external stimuli. Language acquisition is a developing process, given the sensitivity of the human mind to linguistic interaction with the outside world.

Keywords: inflection, morphology, child language acquisition, Spanish

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Authors: Jing Li Hong

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This study compared Michel Foucault’s thoughts and the Chan School’s thoughts on the idea of healing. Healing is not an unfamiliar idea in Buddhist thoughts. The paired concepts of illness and medicine are often used as a metaphor to describe the relationship between people and truth. Foucault investigated the topic of care of self in his later studies and dedicated a large portion of his final semester course at the Collège de France in 1984 to discuss the meaning of Socrates’s offering of a sacrifice to the god of medicine in Phaedo. Foucault indicated a key preposition in ancient philosophy, namely healing. His idea of healing also addressed the relationship between subject and truth. From this relationship, Foucault unraveled his novel study on truth, namely the technologies of the self, with an emphasis on the care of self. Whereas numerous philosophers ask obvious questions such as ‘what is truth’ and ‘how to learn about truth,’ Foucault proposed distinct questions such as ‘what is our relationship to truth’ and ‘how does our relationship with truth turn us into who we are now?’ Thus, healing in both Buddhist and Foucault’s thoughts is related to the relationship between being and truth. This study first reviews Buddhist and Foucault’s ideas of healing to explicate what is illness and what is medicine. Because Buddhist thoughts cover an extensive scope, this study focuses on the thoughts of the Chan School. The second part is a discussion on medicine (treatment), specifically what is used as the medicine for the illness in both thoughts, and how can this medicine treat the illness. This part includes a description and comparison of the use of concepts of negation in these two thought groups. Finally, the subjects that practice the technologies of the self in both groups are compared from the idea of care of self; in other words, the differences between the subjects formed by the different relationships between being and truth are analyzed.

Keywords: Chan, heterogeneous, living style, language of paradox, Michel Foucault, negation, parrhesia, the care of self

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Authors: Jing-Gang Xie

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The research, in this case, considers the integration of the Quantum Field Theory and the General Relativity Theory. As two successful models in explaining behaviors of particles, they are incompatible since they work at different masses and scales of energy, with the evidence that regards the description of black holes and universe formation. It is so considering previous efforts in merging the two theories, including the likes of the String Theory, Quantum Gravity models, and others. In a bid to prove an actionable experiment, the paper’s approach starts with the derivations of the existing theories at present. It goes on to test the derivations by applying the same initial assumptions, coupled with several deviations. The resulting equations get similar results to those of classical Newton model, quantum mechanics, and general relativity as long as conditions are normal. However, outcomes are different when conditions are extreme, specifically with no breakdowns even for less than Schwarzschild radius, or at Planck length cases. Even so, it proves the possibilities of integrating the two theories.

Keywords: general relativity theory, particles, photons, Quantum Gravity Model, gravitational frequency shift

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Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Background & aims: Reading is a receptive skill whose importance could involve abilities' variance from linguistic standard. Several evidences support the hypothesis stating that the more you read the better you write, with a different impact for speech language therapists (SLTs) who use audio-visual aids and computer-assisted language instruction (CALI) and those who do not. Methods: Here we made use of audio-visual aids and CALI for teaching reading skill to a group of 40 students of special needs of both sexes (range between 8 and 18 years old) at al-Malādh school for teaching students of special needs in Dhamar (Yemen) while another group of the same number is taught using ordinary teaching methods. Pre-and-posttests have been administered at the beginning and the end of the semester (Before and after teaching the reading course). The purpose was to understand the differences between the levels of the students of special needs to see to what extent audio-visual aids and CALI are useful for them. The two groups were taught by the same instructor under the same circumstances in the same school. Both quantitative and qualitative procedures were used to analyze the data. Results: The overall findings revealed that audio-visual aids and CALI are very useful for teaching reading to students of special needs and this can be seen in the scores of the treatment group’s subjects (7.0%, in post-test vs.2.5% in pre-test). In comparison to the scores of the second group’s subjects (where audio-visual aids and CALI were not used) (2.2% in both pre-and-posttests), the first group subjects have overcome reading tasks and this can be observed in their performance in the posttest. Compared with males, females’ performance was better (1466 scores (7.3%) vs. 1371 scores (6.8%). Qualitative and statistical analyses showed that such comprehension is absolutely due to the use of audio-visual aids and CALI and nothing else. These outcomes confirm the evidence of the significance of using audio-visual aids and CALI as effective means for teaching receptive skills in general and reading skill in particular.

Keywords: reading, receptive skills, audio-visual aids, CALI, students, special needs, SLTs

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Authors: Irene Lami, Silvia Micheli, Jan Radimský, Joost van de Weijer

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The present study examines gender agreement in Italian compounds with "capo-". Compounds containing "capo-" as the first element is highly productive in Italian and are attested from the earliest stages of the language, with "capo" indicating a prominent role in a group. This type of compound has become progressively more productive over time, establishing itself in the language to indicate human referents with a leadership role over someone or something belonging to both subordinate and coordinate compound categories. In light of the debates on the use of inclusive language, especially with regard to female professional titles in Italian, the gender agreement of the word "capo" is investigated, which in addition to social resistance, also encounters etymological resistance. Regarding the gender agreement of the word "capo-" as the first element of compounds, in addition to social and etymological resistances, morphological constraints must also be considered. In our experiment, 190 native informants were asked to match the gender of the given the word in a sentence, thinking of female referents. The results confirm a scalar hypothesis of gender agreement (i.e., titles traditionally attributed to women > titles traditionally attributed to men > the word "capo" in isolation > the word "capo-" as an element of subordinate compound > the word “capo-“ as an element of a coordinate compound). A significant interplay with number marking is also shown, as words are inflected in gender when the trait +plural is present. Moreover, the results show that, contrary to what is prescriptively established, speakers do inflect the word "capo" according to gender, in limited instances, even when this is found as a compound element, even though to a lesser extent than words that only have social hinders and not etymological or morphological ones. The results appear to show that, although a morphological obstacle is visible, sociolinguistic claims seem to be able to divert these obstacles. This study appears particularly suitable for replication tests over the next few decades, which, if society opens up further to claims of inclusiveness, could further corroborate this trend.

Keywords: compounds, gender inflection, Italian, morphology

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Authors: Francis Mugabi, Kevin Duffy, Joseph J. Y. T Mugisha, Obiora Collins

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Bluetongue virus (BTV) has 27 serotypes, with some of them coexisting in patchy (different) environments, which make its control difficult. Wind-aided midge movement is a known mechanism in the spread of BTV. However, its effects on the probability of coexistence of multiple BTV serotypes are not clear. Deterministic and stochastic models for r BTV serotypes in n discrete patches connected by midge and/or cattle movement are formulated and analyzed. For the deterministic model without midge and cattle movement, using the comparison principle, it is shown that if the patch reproduction number R0 < 1, i=1,2,...,n, j=1,2,...,r, all serotypes go extinct. If R^j_i0>1, competitive exclusion takes place. Using numerical simulations, it is shown that when the n patches are connected by midge movement, coexistence takes place. To account for demographic and movement variability, the deterministic model is transformed into a continuous-time Markov chain stochastic model. Utilizing a multitype branching process, it is shown that the midge movement can have a large effect on the probability of coexistence of multiple BTV serotypes. The probability of coexistence can be brought to zero when the control interventions that directly kill the adult midges are applied. These results indicate the significance of wind-aided midge movement and vector control interventions on the coexistence and control of multiple BTV serotypes in patchy environments.

Keywords: bluetongue virus, coexistence, multiple serotypes, midge movement, branching process

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Authors: Y. Bhatt, N. Ghosh, N. Tiwari

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Acreage response function are modeled taking account of expected harvest prices, weather related variables and other non-price variables allowing for partial adjustment possibility. At the outset, based on the literature on price expectation formation, we explored suitable formulations for estimating the farmer’s expected prices. Assuming that farmers form expectations rationally, the prices of food and biofuel crops are modeled using time-series methods for possible ARCH/GARCH effects to account for volatility. The prices projected on the basis of the models are then inserted to proxy for the expected prices in the acreage response functions. Food crop acreages in different growing states are found sensitive to their prices relative to those of one or more of the biofuel crops considered. The required percentage improvement in food crop yields is worked to offset the acreage loss.

Keywords: acreage response function, biofuel, food security, sustainable development

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Authors: Ahmad S. Mohd Noor, Emma A. Sirajudin, Nur F. Mat Zain

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Reliability is an important property for knowledge repository system. National Marine Bioinformatics System or NABTICS is a marine knowledge repository portal aimed to provide a baseline for marine biodiversity and a tool for researchers and developers. It is intended to be a large and growing online database and also a metadata system for inputs of research analysis. The trends of present large distributed systems such as Cloud computing are the delivery of computing as a service rather than a product. The goal of this research is to make NABTICS a system of greater availability by integrating it with Cloud based Neighbor Replication and Failure Recovery (NRFR). This can be achieved by implementation of NABTICS into distributed environment. As a result, the user can experience minimum downtime while using the system should the server is having a failure. Consequently the online database application is said to be highly available.

Keywords: cloud, availability, distributed system, marine repository, database replication

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Authors: Mehmood Faisal

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In this globalization era, the supply chain management has acquired strategic importance in diverse business environments. In the current highly competitive business environment, the success of any business considerably depends on the efficiency of the supply chain. The importance of petroleum industry cannot be avoided in the global market; however, supply chain management in the petroleum industry is facing various challenges, particularly in the logistics area. These logistical challenges have a main influence on the cost of crude oil; therefore, the opportunities to save cost in logistics still do exist. The large oil producing companies are undertaking future contracts through 'swaps or options' practice that saves their millions of dollars. The objective of this paper is to throw light on the supply chain challenges and opportunities in the oil industry and on swap practices which are widely employed by large oil producing companies around the world, such as Chevron Corporation, Saudi Arabian Oil Company, BP and Exxon Mobil.

Keywords: logistics, oil industry, swap practice, supply chain management

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Authors: Dewi Indah Irianti

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Introduction: Street children include one of the populations at risk of HIV infection. Their vulnerability to these situations is increased by their lack of understanding of the changes associated with adolescence, the lack of knowledge and skills which could help them to make healthy choices. Social integration increased AIDS knowledge among migrant workers in Thailand. Although social integration has been incorporated into health research in other areas, it has received less attention in AIDS prevention research. This factor has not been integrated into models for HIV prevention. Objectives: The goal of this review is to summarize available knowledge about factors related to HIV/AIDS knowledge and to examine whether social integration was reviewed among street children. Methodology: This study performed a systematic search for English language articles published between January 2006 and March 2016 using the following keywords in various combination: street children, HIV/AIDS knowledge and social integration from the following bibliographic databases: Scopus, ProQuest, JSTOR, ScienceDirect, SpringerLink, EBSCOhost, Sage Publication, Clinical Key, Google Web, and Google Scholar . Results: A total of 10 articles met the inclusion criteria were systematically reviewed. This study reviews the existing quantitative and qualitative literature regarding the HIV/AIDS knowledge of street children in many countries. The study locations were Asia, the Americas, Europe, and Africa. The most determinants associated with HIV/AIDS knowledge among street children are age and sex. In this review, social integration that may be associated with HIV/AIDS knowledge among street children has not been investigated. Conclusion: To the best of the author’s knowledge, this study found that there is no research examining the relationship of social integration with the HIV knowledge among street children. This information may assist in the development of relevant strategies and HIV prevention programs to improve HIV knowledge and decrease risk behaviors among street children.

Keywords: HIV/AIDS knowledge, review, social integration, street children

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Authors: Meshal M. Abdullah, Rusty A. Feagin, Layla Musawi

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When humans mismanage arid landscapes, soil erosion can become a primary mechanism that leads to desertification. This study focuses on applying soil erosion models to a disturbed landscape in Umm Nigga, Kuwait, and identifying its predicted change under restoration plans, The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the Demilitarized Zone (DMZ) adjacent to Iraq, and has been fenced off to restrict public access since 1994. The central objective of this project was to utilize GIS and remote sensing to compare the MPSIAC (Modified Pacific South West Inter Agency Committee), EMP (Erosion Potential Method), and USLE (Universal Soil Loss Equation) soil erosion models and determine their applicability for arid regions such as Kuwait. Spatial analysis was used to develop the necessary datasets for factors such as soil characteristics, vegetation cover, runoff, climate, and topography. Results showed that the MPSIAC and EMP models produced a similar spatial distribution of erosion, though the MPSIAC had more variability. For the MPSIAC model, approximately 45% of the land surface ranged from moderate to high soil loss, while 35% ranged from moderate to high for the EMP model. The USLE model had contrasting results and a different spatial distribution of the soil loss, with 25% of area ranging from moderate to high erosion, and 75% ranging from low to very low. We concluded that MPSIAC and EMP were the most suitable models for arid regions in general, with the MPSIAC model best. We then applied the MPSIAC model to identify the amount of soil loss between coastal and desert areas, and fenced and unfenced sites. In the desert area, soil loss was different between fenced and unfenced sites. In these desert fenced sites, 88% of the surface was covered with vegetation and soil loss was very low, while at the desert unfenced sites it was 3% and correspondingly higher. In the coastal areas, the amount of soil loss was nearly similar between fenced and unfenced sites. These results implied that vegetation cover played an important role in reducing soil erosion, and that fencing is much more important in the desert ecosystems to protect against overgrazing. When applying the MPSIAC model predictively, we found that vegetation cover could be increased from 3% to 37% in unfenced areas, and soil erosion could then decrease by 39%. We conclude that the MPSIAC model is best to predict soil erosion for arid regions such as Kuwait.

Keywords: soil erosion, GIS, modified pacific South west inter agency committee model (MPSIAC), erosion potential method (EMP), Universal soil loss equation (USLE)

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Authors: Rakesh Namdeti

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The liquid waste-wastewater- is essentially the water supply of the community after it has been used in a variety of applications. In recent years, heavy metal concentrations, besides other pollutants, have increased to reach dangerous levels for the living environment in many regions. Among the heavy metals, Lead has the most damaging effects on human health. It can enter the human body through the uptake of food (65%), water (20%), and air (15%). In this background, certain low-cost and easily available biosorbent was used and reported in this study. The scope of the present study is to remove Lead from its aqueous solution using Olea EuropaeaResin as biosorbent. The results showed that the biosorption capacity of Olea EuropaeaResin biosorbent was more for Lead removal. The Langmuir, Freundlich, Tempkin, and Dubinin-Radushkevich (D-R) models were used to describe the biosorption equilibrium of Lead Olea EuropaeaResin biosorbent, and the biosorption followed the Langmuir isotherm. The kinetic models showed that the pseudo-second-order rate expression was found to represent well the biosorption data for the biosorbent.

Keywords: novel biosorbent, central composite design, Lead, isotherms, kinetics

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Authors: M. Goliszek, M. Sobiesiak, O. Sevastyanova, B. Podkoscielna

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Lignin is one of three main constituents of biomass together with cellulose and hemicellulose. It is a complex biopolymer, which contains a large number of functional groups, including aliphatic and aromatic hydroxyl groups, carbohylic groups and methoxy groups in its structure, that is why it shows potential capacities for process of sorption. Lignin is a highly cross-linked polymer with a three-dimentional structure which can provide large surface area and pore volumes. It can also posses better dispersion, diffusion and mass transfer behavior in a field of the removal of, e.g., heavy-metal-ions or aromatic pollutions. In this work emulsion-suspension copolymerization method, to synthesize the porous microspheres of divinylbenzene (DVB), styrene (St) and lignin was used. There are also microspheres without the addition of lignin for comparison. Before the copolymerization, modification lignin with methacryloyl chloride, to improve its reactivity with other monomers was done. The physico-chemical properties of the obtained microspheres, e.g., pore structures (adsorption-desorption measurements), thermal properties (DSC), tendencies to swell and the actual shapes were also studied. Due to well-developed porous structure and the presence of functional groups our materials may have great potential in sorption processes. To estimate the sorption capabilities of the microspheres towards phenol and its chlorinated derivatives the off-line SPE (solid-phase extraction) method is going to be applied. This method has various advantages, including low-cost, easy to use and enables the rapid measurements for a large number of chemicals. The efficiency of the materials in removing phenols from aqueous solution and in desorption processes will be evaluated.

Keywords: microspheres, lignin, sorption, solid-phase extraction

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Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

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Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

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Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

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Authors: J. Bartus, J. Odrobinak

Abstract:

The paper presents a nonlinear analysis 3D model of composite steel and concrete beams with web openings using the Finite Element Method (FEM). The core of the study is the introduction of basic modeling techniques comprehending the description of material behavior, appropriate elements selection, and recommendations for overcoming problems with convergence. Results from various finite element models are compared in the study. The main objective is to observe the concrete failure mechanism and its influence on the structural performance of numerical models of the beams at particular load stages. The bearing capacity of beams, corresponding deformations, stresses, strains, and fracture patterns were determined. The results show how load-bearing elements consisting of concrete parts can be analyzed using FEM software with various options to create the most suitable numerical model. The paper demonstrates the versatility of Ansys software usage for structural simulations.

Keywords: Ansys, concrete, modeling, steel

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Authors: Yu Lu

Abstract:

Fixed point theory is a basic tool for the study of the existence of Nash equilibria in game theory. This paper presents a significant generalization of the Veinott-Zhou fixed point theorem for increasing correspondences, which serves as an essential framework for investigating the existence of Nash equilibria in supermodular and quasisupermodular games. To establish our proofs, we explore different conceptions of multivalued increasingness and provide comprehensive results concerning the existence of the largest/least fixed point. We provide two distinct approaches to the proof, each offering unique insights and advantages. These advancements not only extend the applicability of the Veinott-Zhou theorem to a broader range of economic scenarios but also enhance the theoretical framework for analyzing equilibrium behavior in complex game-theoretic models. Our findings pave the way for future research in the development of more sophisticated models of economic behavior and strategic interaction.

Keywords: fixed-point, Tarski’s fixed-point theorem, Nash equilibrium, supermodular game

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Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Aayushi Somani, Siba P. Samal

Abstract:

Three-dimensional (3D) meshes are data structures, which store geometric information of an object or scene, generally in the form of vertices and edges. Current technology in laser scanning and other geometric data acquisition technologies acquire high resolution sampling which leads to high resolution meshes. While high resolution meshes give better quality rendering and hence is used often, the processing, as well as storage of 3D meshes, is currently resource-intensive. At the same time, web applications for data processing have become ubiquitous owing to their accessibility. For 3D meshes, the advancement of 3D web technologies, such as WebGL, WebVR, has enabled high fidelity rendering of huge meshes. However, there exists a gap in ability to stream huge meshes to a native client and browser application due to high network latency. Also, there is an inherent delay of loading WebGL pages due to large and complex models. The focus of our work is to identify the challenges faced when such meshes are streamed into and processed on hand-held devices, owing to its limited resources. One of the solutions that are conventionally used in the graphics community to alleviate resource limitations is mesh compression. Our approach deals with a two-step approach for random accessible progressive compression and its parallel implementation. The first step includes partition of the original mesh to multiple sub-meshes, and then we invoke data parallelism on these sub-meshes for its compression. Subsequent threaded decompression logic is implemented inside the Web Browser Engine with modification of WebGL implementation in Chromium open source engine. This concept can be used to completely revolutionize the way e-commerce and Virtual Reality technology works for consumer electronic devices. These objects can be compressed in the server and can be transmitted over the network. The progressive decompression can be performed on the client device and rendered. Multiple views currently used in e-commerce sites for viewing the same product from different angles can be replaced by a single progressive model for better UX and smoother user experience. Can also be used in WebVR for commonly and most widely used activities like virtual reality shopping, watching movies and playing games. Our experiments and comparison with existing techniques show encouraging results in terms of latency (compressed size is ~10-15% of the original mesh), processing time (20-22% increase over serial implementation) and quality of user experience in web browser.

Keywords: 3D compression, 3D mesh, 3D web, chromium, client-server architecture, e-commerce, level of details, parallelization, progressive compression, WebGL, WebVR

Procedia PDF Downloads 156

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

Abstract:

In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Analise Borg, Paul Micallef

Abstract:

Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

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Authors: Ibrahim A. Elshaer, Alaa M. Shaker

Abstract:

Several previous empirical studies have operationalized service quality as either a multidimensional or unidimensional construct. While few earlier studies investigated some practices of the assumed dimensional structure of service quality, no study has been found to have tested the construct’s dimensionality using confirmatory factor analysis (CFA). To gain a better insight into the dimensional structure of service quality construct, this paper tests its dimensionality using three CFA models (higher order factor model, oblique factor model, and one factor model) on a set of data collected from 390 British tourists visited Egypt. The results of the three tests models indicate that service quality construct is multidimensional. This result helps resolving the problems that might arise from the lack of clarity concerning the dimensional structure of service quality, as without testing the dimensional structure of a measure, researchers cannot assume that the significant correlation is a result of factors measuring the same construct.

Keywords: service quality, dimensionality, confirmatory factor analysis, Egypt

Procedia PDF Downloads 573