Search results for: hierarchical linear modeling

Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

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Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

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This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Yanisa Chaiya, Jintana Sanwong

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Let V be a vector space over a field and W a subspace of V. Let Fix(V,W) denote the set of all linear transformations on V with fix all elements in W. In this paper, we show that Fix(V,W) is a semigroup under the composition of maps and describe Green’s relations on this semigroup in terms of images, kernels and the dimensions of subspaces of the quotient space V/W where V/W = {v+W : v is an element in V} with v+W = {v+w : w is an element in W}. Let dim(U) denote the dimension of a vector space U and Vα = {vα : v is an element in V} where vα is an image of v under a linear transformation α. For any cardinal number a let a'= min{b : b > a}. We also show that the ideals of Fix(V,W) are precisely the sets. Fix(r) ={α ∊ Fix(V,W) : dim(Vα/W) < r} where 1 ≤ r ≤ a' and a = dim(V/W). Moreover, we prove that if V is a finite-dimensional vector space, then every ideal of Fix(V,W) is principle.

Keywords: Green’s relations, ideals, linear transformation semi-groups, principle ideals

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Authors: Saeed Otarod

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In a different simple and straight forward analysis a closed-form integral solution is found for nonhomogeneous second order linear ordinary differential equations, in terms of a particular solution of their corresponding homogeneous part. To find the particular solution of the homogeneous part, the equation is transformed into a simple Riccati equation from which the general solution of non-homogeneouecond order differential equation, in the form of a closed integral equation is inferred. The method works well in manyimportant cases, such as Schrödinger equation for hydrogen-like atoms. A non-homogenous second order linear differential equation has been solved as an extra example

Keywords: explicit, linear, differential, closed form

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: M. C. Padma, R. J. Prathibha

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Parts of speech tagging is the process of assigning appropriate parts of speech tags to the words in a given text. The critical or crucial information needed for tagging a word come from its internal structure rather from its neighboring words. The internal structure of a word comprises of its morphological features and grammatical information. This paper presents a morpheme based parts of speech tagger for Kannada language. This proposed work uses hierarchical tag set for assigning tags. The system is tested on some Kannada words taken from EMILLE corpus. Experimental result shows that the performance of the proposed system is above 90%.

Keywords: hierarchical tag set, morphological analyzer, natural language processing, paradigms, parts of speech

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Authors: F. A. Al-Awadhi, D. Al-Hulail

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In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.

Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode

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Authors: Li Zhu, Binghua Wang, Yong Sun

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China is experiencing the rural development process, with the agritourism complex becoming one of the significant modes. Therefore, it is imperative to understand the energy performance of agritourism complex. This study focuses on a typical case of the agritourism complex and simulates the energy consumption performance on condition of the regular energy system. It was found that HVAC took 90% of the whole energy demand range. In order to optimize the energy supply structure, the hierarchical analysis was carried out on the level of architecture with three main factors such as construction situation, building types and energy demand types. Finally, the energy planning suggestion of the agritourism complex was put forward and the relevant results were obtained.

Keywords: agritourism complex, energy planning, energy demand simulation, hierarchical structure model

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Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean

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In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.

Keywords: asymptotic relative efficiency, non-linear rank-based, rank estimates, variogram

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Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

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Authors: Ahmet Parlak, Celalettin Bilgen

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In order to create an effective early warning system, Identification of the risks, preparation and carrying out risk modeling of risk scenarios, taking into account the shortcomings of the old disaster scenarios should be used to improve the system. In the light of this, the importance of risk modeling in creating an effective early warning system is understood. In the scope of TAFRISK project risk modeling trend analysis report on risk modeling developed and a demonstration was conducted for Risk Modeling for flood and mass movements. For risk modeling R&D, studies have been conducted to determine the information, and source of the information, to be gathered, to develop algorithms and to adapt the current algorithms to Turkey’s conditions for determining the risk score in the high disaster risk areas. For each type of the disaster; Disaster Deficit Index (DDI), Local Disaster Index (LDI), Prevalent Vulnerability Index (PVI), Risk Management Index (RMI) have been developed as disaster indices taking danger, sensitivity, fragility, and vulnerability, the physical and economic damage into account in the appropriate scale of the respective type.

Keywords: disaster, hazard, risk modeling, sensor

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Authors: Mihai Caramihai, Dan Vasilescu

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The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo

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Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.

Keywords: cementitious materials, deformation, failure, material chemistry modeling

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Authors: Xiaobao Han, Huacong Li, Jia Li

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For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

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Authors: Rik van Leeuwen, Ger Koole

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Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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Authors: Ksenija Dumičić, Anita Čeh Časni, Irena Palić

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This paper examines economic and Information and Communication Technology (ICT) development influence on recently increasing Internet purchases by individuals for European Union member states. After a growing trend for Internet purchases in EU27 was noticed, all possible regression analysis was applied using nine independent variables in 2011. Finally, two linear regression models were studied in detail. Conducted simple linear regression analysis confirmed the research hypothesis that the Internet purchases in analysed EU countries is positively correlated with statistically significant variable Gross Domestic Product per capita (GDPpc). Also, analysed multiple linear regression model with four regressors, showing ICT development level, indicates that ICT development is crucial for explaining the Internet purchases by individuals, confirming the research hypothesis.

Keywords: European union, Internet purchases, multiple linear regression model, outlier

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Authors: Yiyan Wu

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In the past several decades, the market transition in China has brought in not only more opportunities for women in the labor market but also more attention to gender inequality in workplace. Although some pieces of literature have mentioned gender inequality and segregation at workplace in China, the paper looks into the variations of gender inequality and segregation: working women have little feeling about 'hierarchical inequalities', which define the status and position of women at the workplace. However, at the same time, they unconsciously reinforced 'horizontal inequalities', which creates gender segregation across occupations and job titles. Using qualitative interviews with women employers and employees of various occupations and job titles in Eastern and Southern China, this paper finds evidence that working women's understandings of the division of labor based on the characteristics and expectations of women and men are not as a result of rationality and efficiency, but instead, are the products of gendered stereotypes and traditions. However, holding positive views of gender equality at workplace, working women are not aware of the existence and influence of such gendered stereotypes and traditions. By distinguishing the concepts of 'horizontal inequality' and 'hierarchical inequality' with a cultural sociological approach, this paper contributes to the understanding of gender inequality and segregation in contemporary Chinese society. Moreover, this paper explains the logic behind the paradox in which gender inequality and segregation at workplace persist while women are feeling equal.

Keywords: gender equality, segregation, hierarchical inequality, horizontal inequality, China

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Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

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Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: routing protocol, optimization, clustering, WSN

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Authors: Sahar Dehghan, Yeganeh Mousavi Jahromi, Ghahraman Abdoli

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Since tax revenues are one of the most important sources of government revenue, it is essential to consider increasing taxpayers' compliance. One of the factors that can affect the taxpayers' compliance is the structure of the crimes and incentives envisaged in the tax law. In this research, by using the 'prospect theory', the effects of changes in the rate of crimes and the tax incentive in the direct tax law on the taxpayer’s compliance behavior have been investigated. To determine the preferences and preferences of taxpayer’s in the business sector and their degree of sensitivity to fines and incentives, a questionnaire with mixed gamble structure is designed. Estimated results using the Hierarchical Bayesian method indicate that the taxpayer’s that have been tested in this study are more sensitive to the incentives in the direct tax law, and the tax administration can use this to increase the level of collected tax and increase the level of compliance.

Keywords: tax compliance, prospect theory, value function, mixed gamble

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Authors: Vikram Saini, Lillie Dewan

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This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: C. Patrascioiu

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The paper describes the modeling and simulation of the heat pumps domain processes. The main objective of the study is the use of the heat pump in propene–propane distillation processes. The modeling and simulation instrument is the Unisim^® Design simulator. The paper is structured in three parts: An overview of the compressing gases, the modeling and simulation of the freezing systems, and the modeling and simulation of the heat pumps. For each of these systems, there are presented the Unisim^® Design simulation diagrams, the input–output system structure and the numerical results. Future studies will consider modeling and simulation of the propene–propane distillation process with heat pump.

Keywords: distillation, heat pump, simulation, unisim design

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Authors: Eusebio Jr. Lina, Ederlina Nocon

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Cyclic codes are a fundamental subclass of linear codes that enjoy a very interesting algebraic structure. The class of skew cyclic codes (or θ-cyclic codes) is a generalization of the notion of cyclic codes. This a very large class of linear codes which can be used to systematically search for codes with good properties. A linear code with complementary dual (LCD code) is a linear code C satisfying C ∩ C^⊥ = {0}. This subclass of linear codes provides an optimum linear coding solution for a two-user binary adder channel and plays an important role in countermeasures to passive and active side-channel analyses on embedded cryptosystems. This paper aims to identify LCD codes from the class of skew cyclic codes. Let F_q be a finite field of order q, and θ be an automorphism of F_q. Some conditions for a skew cyclic code to be LCD were given. To this end, the properties of a noncommutative skew polynomial ring F_q[x, θ] of automorphism type were revisited, and the algebraic structure of skew cyclic code using its skew polynomial representation was examined. Using the result that skew cyclic codes are left ideals of the ring F_q[x, θ]/〈x^n-1〉, a characterization of a skew cyclic LCD code of length n was derived. A necessary condition for a skew cyclic code to be LCD was also given.

Keywords: LCD cyclic codes, skew cyclic LCD codes, skew cyclic complementary dual codes, theta-cyclic codes with complementary duals

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram, Wenli Hu, Yang Yung

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In 3D video games, the dominance of production is unceasingly growing with a protruding level of affordability in terms of budget. Afterward, the automation of speech-lip synchronization technique is customarily onerous and has advanced a critical research subject in virtual reality based 3D video games. This paper presents one of these automatic tools, precisely riveted on the synchronization of the speech and the lip movement of the game characters. A robust and precise speech recognition segment that systematized with Algebraic Code Excited Linear Prediction method is developed which unconventionally delivers lip sync results. The Algebraic Code Excited Linear Prediction algorithm is constructed on that used in code-excited linear prediction, but Algebraic Code Excited Linear Prediction codebooks have an explicit algebraic structure levied upon them. This affords a quicker substitute to the software enactments of lip sync algorithms and thus advances the superiority of service factors abridged production cost.

Keywords: algebraic code excited linear prediction, speech-lip synchronization, video games, virtual reality

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Authors: Nadine Yehya, Chantal Maatouk

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Low energy buildings have been developed to achieve global climate commitments in reducing energy consumption. They comprise energy efficient buildings, zero energy buildings, positive buildings and passive house buildings. The reduced energy demands in Low Energy buildings call for advanced building energy modeling that focuses on studying active building systems such as heating, cooling and ventilation, improvement of systems performances, and development of control systems. Modeling and building simulation have expanded to cover different modeling approach i.e.: detailed physical model, dynamic empirical models, and hybrid approaches, which are adopted by various simulation tools. This paper uses DesignBuilder with EnergyPlus simulation engine in order to; First, study the impact of efficiency measures on building energy behavior by comparing Low energy residential model to a conventional one in Beirut-Lebanon. Second, choose the appropriate energy systems for the studied case characterized by an important cooling demand. Third, study dynamic modeling of Variable Refrigerant Flow (VRF) system in EnergyPlus that is chosen due to its advantages over other systems and its availability in the Lebanese market. Finally, simulation of different energy systems models with different modeling approaches is necessary to confront the different modeling approaches and to investigate the interaction between energy systems and building envelope that affects the total energy consumption of Low Energy buildings.

Keywords: physical model, variable refrigerant flow heat pump, dynamic modeling, EnergyPlus, the modeling approach

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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