Search results for: computational finance.

Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias

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Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.

Keywords: automatic clustering, bioinformatics tool, gene ontology, protein sequence annotation, semantic similarity search

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Authors: A. Bakhtiar, B. Purwanggono, N. Metasari

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PT XYZ is a bottled drinking water company. To preserve production resources owned by the company so that the resources could be utilized well, it has implemented maintenance management system, which has important role in company's profitability, and is one of the factors influenced overall company's performance. Yet, up to now the company has never measured maintenance activities' contribution to company's performance. Performance evaluation is done according to adapted Balanced Scorecard model fitted to maintenance function context. This model includes six perspectives: innovation and growth, production, maintenance, environment, costumer, and finance. Actual performance measurement is done through Analytic Hierarchy Process and Objective Matrix. From the research done, we can conclude that the company's maintenance function is categorized in moderate performance. But, there are some indicators which has high priority but low performance, which are: costumers' complain rate, work lateness rate, and Return on Investment.

Keywords: Maintenance, performance, balanced scorecard, objective matrix.

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Authors: Tomáš Brabenec

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Cost contribution arrangements (CCAs) and Cost sharing agreements (CCAs) belong to the tools of modern finance management. Costs spend by associated enterprises on developing producing or obtaining assets, services or rights (in general - benefits) are used for tax optimizing too. The main purpose of joint research and development, producing or obtaining benefits is to lower these costs as much as possible or to maximize the benefits. In this article is mentioned the problematic of transfer pricing and arm's length principle with connection of CCAs, CSAs. Next, there is mentioned how to settle participation shares of the total cost and benefits contributions with respect to the OECD Transfer pricing for MNEs Guidelines and with respect to other significant regulations.

Keywords: Arm's length principle, Cost contribution arrangements, Cost sharing agreements, Reasonable anticipated benefits, Relevant costs, Transfer prices.

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: Finance, machine learning, opening price, stock market.

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Authors: Yuri Bizzoni, Marianne Reboul

Abstract:

Our program compares French and Italian translations of Homer’s Odyssey, from the XVIth to the XXth century. We focus on the third point, showing how distributional semantics systems can be used both to improve alignment between different French translations as well as between the Greek text and a French translation. Although we focus on French examples, the techniques we display are completely language independent.

Keywords: Translation studies, machine translation, computational linguistics, distributional semantics.

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Authors: Manpreet Singh, Parvinder Singh, Suman

Abstract:

The data is available in abundance in any business organization. It includes the records for finance, maintenance, inventory, progress reports etc. As the time progresses, the data keep on accumulating and the challenge is to extract the information from this data bank. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of business. For the development of accurate and required information for particular problem, business analyst needs to develop multidimensional models which give the reliable information so that they can take right decision for particular problem. If the multidimensional model does not possess the advance features, the accuracy cannot be expected. The present work involves the development of a Multidimensional data model incorporating advance features. The criterion of computation is based on the data precision and to include slowly change time dimension. The final results are displayed in graphical form.

Keywords: Multidimensional, data precision.

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Authors: V.K.Ananthashayana, Geetha.K.S

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In this paper, a recursive algorithm for the computation of 2-D DCT using Ramanujan Numbers is proposed. With this algorithm, the floating-point multiplication is completely eliminated and hence the multiplierless algorithm can be implemented using shifts and additions only. The orthogonality of the recursive kernel is well maintained through matrix factorization to reduce the computational complexity. The inherent parallel structure yields simpler programming and hardware implementation and provides log 1 2 3 2 N N-N+ additions and N N 2 log 2 shifts which is very much less complex when compared to other recent multiplierless algorithms.

Keywords: DCT, Multilplerless, Ramanujan Number, Recursive.

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Authors: Azwadi Ali

Abstract:

The survival of publicly listed companies largely depends on their stocks being liquidly traded. This goal can be achieved when new investors are attracted to invest on companies- stocks. Among different groups of investors, individual investors are generally less able to objectively evaluate companies- risks and returns, and tend to be emotionally biased in their investing decisions. Therefore their decisions may be formed as a result of perceived risks and returns, and influenced by companies- images. This study finds that perceived risk, perceived returns and trust directly affect individual investors- trading decisions while attitude towards brand partially mediates the relationships. This finding suggests that, in courting individual investors, companies still need to perform financially while building a good image can result in their stocks being accepted quicker than the stocks of good performing companies with hidden images.

Keywords: Behavioral Finance, Investment, Attitude towardsBrand, Partial Least Squares

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Authors: Thomas Jin-Chee Liu

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In this paper, the thermo-electro-structural coupledfield in a cracked metal plate is studied using the finite element analysis. From the computational results, the compressive stresses reveal near the crack tip. This conclusion agrees with the past reference. Furthermore, the compressive condition can retard and stop the crack growth during the Joule heating process.

Keywords: Compressive stress, crack tip, Joule heating, finite element.

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Authors: Alexei M. Mikhailov

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The paper discusses the mathematics of pattern indexing and its applications to recognition of visual patterns that are found in video clips. It is shown that (a) pattern indexes can be represented by collections of inverted patterns, (b) solutions to pattern classification problems can be found as intersections and histograms of inverted patterns and, thus, matching of original patterns avoided.

Keywords: Artificial neural cortex, computational biology, data mining, pattern recognition.

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 μm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral geniculate nucleus, visual cortex, finite element, glaucoma, neuroprostheses.

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Authors: Angela Ralli, Eleni Galiotou

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In this paper we describe the recognition process of Greek compound words using the PC-KIMMO software. We try to show certain limitations of the system with respect to the principles of compound formation in Greek. Moreover, we discuss the computational processing of phenomena such as stress and syllabification which are indispensable for the analysis of such constructions and we try to propose linguistically-acceptable solutions within the particular system.

Keywords: Morpho-phonological parsing, compound words, two-level morphology, natural language processing.

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Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

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In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affect the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance.

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Authors: Himanshu Shekhar Maharana, S. K .Dash

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Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution. 

Keywords: Economic load dispatch, constriction factor based particle swarm optimization, dispersed particle swarm optimization, weight improved particle swarm optimization, ramp rate and constriction factor based particle swarm optimization.

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Authors: Jefri Marzal, Hong Xie, Chun Che Fung

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Visibility problems are central to many computational geometry applications. One of the typical visibility problems is computing the view from a given point. In this paper, a linear time procedure is proposed to compute the visibility subsets from a corner of a rectangular prism in an orthogonal polyhedron. The proposed algorithm could be useful to solve classic 3D problems.

Keywords: Visibility, rectangular prism, orthogonal polyhedron.

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Authors: Soon-Tai Park, Jong-Whoi Shin, Bog-Ki Min, Ik-Sub Lee, Gang-Shin Lee, Jae-Il Lee

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As the information age matures, major social infrastructures such as communication, finance, military and energy, have become ever more dependent on information communication systems. And since these infrastructures are connected to the Internet, electronic intrusions such as hacking and viruses have become a new security threat. Especially, disturbance or neutralization of a major social infrastructure can result in extensive material damage and social disorder. To address this issue, many nations around the world are researching and developing various techniques and information security policies as a government-wide effort to protect their infrastructures from newly emerging threats. This paper proposes an evaluation method for information security levels of CIIP (Critical Information Infrastructure Protection), which can enhance the security level of critical information infrastructure by checking the current security status and establish security measures accordingly to protect infrastructures effectively.

Keywords: Information Security Evaluation Methodology, Critical Information Infrastructure Protection.

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Authors: Wang Wen-long, Li Hua, Pan Sha

Abstract:

Eight difference schemes and five limiters are applied to numerical computation of Riemann problem. The resolution of discontinuities of each scheme produced is compared. Numerical dissipation and its estimation are discussed. The result shows that the numerical dissipation of each scheme is vital to improve scheme-s accuracy and stability. MUSCL methodology is an effective approach to increase computational efficiency and resolution. Limiter should be selected appropriately by balancing compressive and diffusive performance.

Keywords: Scheme; Limiter, Numerical simulation, Riemannproblem.

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Authors: Lina Sinevičienė

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Arising problems of countries’ public finances, social and demographic changes motivate scientific and policy debates on public spending size, structure and efficiency in order to meet the changing needs of society and business. The concept of sustainable development poses new challenges for scientists and policy-makers in the field of public finance. This paper focuses on the investigation of the relationship between government expenditure and country’s economic development in the context of sustainable development. Empirical analysis focuses on the data of the European Union (except Croatia and Luxemburg) countries. The study covers 2003 – 2012 years, using annual cross-sectional data. Summarizing the research results, it can be stated that governments should pay more attention to the needs that ensure sustainable development in the long-run when formulating public expenditure policy, particularly in the field of environment protection.

Keywords: Economic development, economic growth, government expenditure, sustainable development.

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Authors: Le Chi Cuong

Abstract:

X-ray diffraction is an effective mean for analyzing material properties. This paper developed a new computational software for determining the properties of crystalline materials such as elastic constants, residual stresses, surface hardness, phase components, and etc. The results computed from the X-ray diffraction method were compared to those from the traditional methods and they are in the 95% confidential limits, showing that the newly developed software has high reproducibility, opening a possibility of its commercialization.

Keywords: X-ray diffraction, Nondestructive evaluation, Hardness, Residual stress, Phase determination.

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Authors: Luciana Montera

Abstract:

DNA shuffling is a powerful method used for in vitro evolute molecules with specific functions and has application in areas such as, for example, pharmaceutical, medical and agricultural research. The success of such experiments is dependent on a variety of parameters and conditions that, sometimes, can not be properly pre-established. Here, two computational models predicting DNA shuffling results is presented and their use and results are evaluated against an empirical experiment. The in silico and in vitro results show agreement indicating the importance of these two models and motivating the study and development of new models.

Keywords: Computer simulation, DNA shuffling, in silico andin vitro comparison.

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Authors: J. Urbánek Jiří, Krahulec Josef, Johanidesová Jitka, F. Urbánek Jiří

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This paper deals with using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It serves for crisis situations investigation and modelling within the organizations of critical infrastructure. In first part of paper, it will be introduced entities, operators, and actors of DYVELOP method. It uses just three operators of Boolean algebra and four types of the entities: the Environments, the Process Systems, the Cases, and the Controlling. The Process Systems (PrS) have five “brothers”: Management PrS, Transformation PrS, Logistic PrS, Event PrS and Operation PrS. The Cases have three “sisters”: Process Cell Case, Use Case, and Activity Case. They all need for the controlling of their functions special Ctrl actors, except ENV – it can do without Ctrl. Model´s maps are named the Blazons and they are able mathematically - graphically express the relationships among entities, actors and processes. In second part of this paper, the rich blazons of DYVELOP method will be used for the discovering and modelling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission. The crisis management of energetic crisis infrastructure organization is obliged to use the cycles for successful coping of crisis situations. Several times cycling of these cases is necessary condition for the encompassment for both emergency events and the mitigation of organization´s damages. Uninterrupted and continuous cycling process brings for crisis management fruitfulness and it is good indicator and controlling actor of organizational continuity and its sustainable development advanced possibilities. The research reliable rules are derived for the safety and reliable continuity of energetic critical infrastructure organization in the crisis situation.

Keywords: Blazons, computational assistance, DYVELOP method, critical infrastructure.

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Authors: Reihaneh Rafiemanzelat, Maryam Imani Emadi

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The need to protect our cultural heritage was stressed on revitalization of historical city centers in communities. The main aim of this research is to attract finance and activities to the historical city centers through the citizens and municipalities participation while cities expanded their boundaries toward suburban areas. Today the main problems which facing to the most historical city centers, is loss of their centrality through effect of urbanization on any point of the cities which is the most important issue on neglect and abandonment of the historical central area by decentralizing living, commerce and public areas. This article evaluate the ways in which city center revitalization can be effect on vitality and viability of the central area in case of Naghshe Jahan square which situated at the center of Isfahan city, Iran. Constructed between 1598 and 1629, it is now an important historical site, and one of UNESCO's World Heritage Sites.

Keywords: City centers, revitalization, urban development, vitality and viability.

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Authors: Erna T. Herdiani, Maman A. Djauhari

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In recent years, the use of vector variance as a measure of multivariate variability has received much attention in wide range of statistics. This paper deals with a more economic measure of multivariate variability, defined as vector variance minus all duplication elements. For high dimensional data, this will increase the computational efficiency almost 50 % compared to the original vector variance. Its sampling distribution will be investigated to make its applications possible.

Keywords: Asymptotic distribution, covariance matrix, likelihood ratio test, vector variance.

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Authors: Narasimham Challa, Jayaram Pradhan

Abstract:

Cryptographic algorithms play a crucial role in the information society by providing protection from unauthorized access to sensitive data. It is clear that information technology will become increasingly pervasive, Hence we can expect the emergence of ubiquitous or pervasive computing, ambient intelligence. These new environments and applications will present new security challenges, and there is no doubt that cryptographic algorithms and protocols will form a part of the solution. The efficiency of a public key cryptosystem is mainly measured in computational overheads, key size and bandwidth. In particular the RSA algorithm is used in many applications for providing the security. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The fact that most chips on smart cards can-t process key extending 1024 bit shows that there is need for alternative. NTRU is such an alternative and it is a collection of mathematical algorithm based on manipulating lists of very small integers and polynomials. This allows NTRU to high speeds with the use of minimal computing power. NTRU (Nth degree Truncated Polynomial Ring Unit) is the first secure public key cryptosystem not based on factorization or discrete logarithm problem. This means that given sufficient computational resources and time, an adversary, should not be able to break the key. The multi-party communication and requirement of optimal resource utilization necessitated the need for the present day demand of applications that need security enforcement technique .and can be enhanced with high-end computing. This has promoted us to develop high-performance NTRU schemes using approaches such as the use of high-end computing hardware. Peer-to-peer (P2P) or enterprise grids are proven as one of the approaches for developing high-end computing systems. By utilizing them one can improve the performance of NTRU through parallel execution. In this paper we propose and develop an application for NTRU using enterprise grid middleware called Alchemi. An analysis and comparison of its performance for various text files is presented.

Keywords: Alchemi, GridNtru, Ntru, PKCS.

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Authors: J. R. C. Kuntz, Katharina Näswall, Frances Walls

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This study sought to uncover the complex role of stress in the workplace by investigating both positive (eustress) and negative (distress) stress responses. In particular, the study tested a mediation model in which organisational stressors (person-job fit and role overload) influence employee affective wellbeing, both directly and indirectly through stress responses. Participants were recruited from retail and finance organisations in Australia and New Zealand, and asked to complete an anonymous online questionnaire. A total of 140 individuals returned completed questionnaires. The results show that person-job fit influenced eustress, which in turn had a positive effect on employee affective wellbeing; and role overload impacted distress, which in turn held a negative influence on affective wellbeing. These findings indicate that different organisational stressors have unique relationships with eustress and distress responses. Limitations and implications of the study are discussed.

Keywords: Distress, Eustress, Role Overload, Wellbeing.

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Authors: Sharfi Dirar, Shihab Elhaj, Ahmed El Fatih

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Computational fluid dynamics were used to simulate and study the heated water boiler tube for both normal and rifled tube with a refinement of the mesh to check the convergence. The operation condition was taken from GARRI power station and used in a boundary condition accordingly. The result indicates the rifled tube has higher heat transfer efficiency than the normal tube.

Keywords: Boiler tube, Convergence Check, Normal Tube, Rifled Tube.

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Authors: Y. N. Phang, E. F. Loh

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The zero inflated models are usually used in modeling count data with excess zeros where the existence of the excess zeros could be structural zeros or zeros which occur by chance. These type of data are commonly found in various disciplines such as finance, insurance, biomedical, econometrical, ecology, and health sciences which involve sex and health dental epidemiology. The most popular zero inflated models used by many researchers are zero inflated Poisson and zero inflated negative binomial models. In addition, zero inflated generalized Poisson and zero inflated double Poisson models are also discussed and found in some literature. Recently zero inflated inverse trinomial model and zero inflated strict arcsine models are advocated and proven to serve as alternative models in modeling overdispersed count data caused by excessive zeros and unobserved heterogeneity. The purpose of this paper is to review some related literature and provide a variety of examples from different disciplines in the application of zero inflated models. Different model selection methods used in model comparison are discussed.

Keywords: Overdispersed count data, model selection methods, likelihood ratio, AIC, BIC.

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Authors: Francois T. Pronk, Steven J. Hulshoff

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A study of various turbulent inflow generation methods was performed to compare their relative effectiveness for LES computations of turbulent boundary layers. This study confirmed the quality of the turbulent information produced by the family of recycling and rescaling methods which take information from within the computational domain. Furthermore, more general inflow methods also proved applicable to such simulations, with a precursor-like inflow and a random inflow augmented with forcing planes showing promising results.

Keywords: Boundary layer, Flat plate, Inflow modeling, LES

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Authors: Lenka Krulikovská, Jaroslav Polec, Tomáš Hirner

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In this paper we present a novel method, which reduces the computational complexity of abrupt cut detection. We have proposed fast algorithm, where the similarity of frames within defined step is evaluated instead of comparing successive frames. Based on the results of simulation on large video collection, the proposed fast algorithm is able to achieve 80% reduction of needed frames comparisons compared to actually used methods without the shot cut detection accuracy degradation.

Keywords: Abrupt cut, fast algorithm, shot cut detection, Pearson correlation coefficient.

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Authors: Corneliu Sofronie, Roxana Zubcov

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Cognitive Science appeared about 40 years ago, subsequent to the challenge of the Artificial Intelligence, as common territory for several scientific disciplines such as: IT, mathematics, psychology, neurology, philosophy, sociology, and linguistics. The new born science was justified by the complexity of the problems related to the human knowledge on one hand, and on the other by the fact that none of the above mentioned sciences could explain alone the mental phenomena. Based on the data supplied by the experimental sciences such as psychology or neurology, models of the human mind operation are built in the cognition science. These models are implemented in computer programs and/or electronic circuits (specific to the artificial intelligence) – cognitive systems – whose competences and performances are compared to the human ones, leading to the psychology and neurology data reinterpretation, respectively to the construction of new models. During these processes if psychology provides the experimental basis, philosophy and mathematics provides the abstraction level utterly necessary for the intermission of the mentioned sciences. The ongoing general problematic of the cognitive approach provides two important types of approach: the computational one, starting from the idea that the mental phenomenon can be reduced to 1 and 0 type calculus operations, and the connection one that considers the thinking products as being a result of the interaction between all the composing (included) systems. In the field of psychology measurements in the computational register use classical inquiries and psychometrical tests, generally based on calculus methods. Deeming things from both sides that are representing the cognitive science, we can notice a gap in psychological product measurement possibilities, regarded from the connectionist perspective, that requires the unitary understanding of the quality – quantity whole. In such approach measurement by calculus proves to be inefficient. Our researches, deployed for longer than 20 years, lead to the conclusion that measuring by forms properly fits to the connectionism laws and principles.

Keywords: complementary methodology, connection approach, networks without scaling, quantum psychology.

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