Search results for: semantic computing

Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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Authors: Burak Bal, Demircan Canadinc

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Dynamic strain aging (DSA), resulting from the reorientation of C-Mn clusters in the core of dislocations, can provide a strain hardening mechanism. In addition, in Hadfield steel, negative strain rate sensitivity is observed due to the DSA. In our study, we incorporated dynamic strain aging onto crystal plasticity computations to predict the local instabilities and corresponding negative strain rate sensitivity. Specifically, the material response of Hadfield steel was obtained from monotonic and strain-rate jump experiments under tensile loading. The strain rate range was adjusted from 10⁻⁴ to 10⁻¹s ⁻¹. The crystal plasticity modeling of the material response was carried out based on Voce-type hardening law and corresponding Voce hardening parameters were determined. The solute pinning effect of carbon atom was incorporated to crystal plasticity simulations at microscale level by computing the shear stress contribution imposed on an arrested dislocation by carbon atom. After crystal plasticity simulations with modifying hardening rule, which takes into account the contribution of DSA, it was seen that the model successfully predicts both the role of DSA and corresponding strain rate sensitivity.

Keywords: crystal plasticity, dynamic strain aging, Hadfield steel, negative strain rate sensitivity

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Authors: Ghazal Faraj, Andras Micsik

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The CIDOC Conceptual Reference Model (CRM) is an extensible ontology that provides integrated access to heterogeneous and digital datasets. The CIDOC-CRM offers a “semantic glue” intended to promote accessibility to several diverse and dispersed sources of cultural heritage data. That is achieved by providing a formal structure for the implicit and explicit concepts and their relationships in the cultural heritage field. The COURAGE (“Cultural Opposition – Understanding the CultuRal HeritAGE of Dissent in the Former Socialist Countries”) project aimed to explore methods about socialist-era cultural resistance during 1950-1990 and planned to serve as a basis for further narratives and digital humanities (DH) research. This project highlights the diversity of flourished alternative cultural scenes in Eastern Europe before 1989. Moreover, the dataset of COURAGE is an online RDF-based registry that consists of historical people, organizations, collections, and featured items. For increasing the inter-links between different datasets and retrieving more relevant data from various data silos, a shared federated ontology for reconciled data is needed. As a first step towards these goals, a full understanding of the CIDOC CRM ontology (target ontology), as well as the COURAGE dataset, was required to start the work. Subsequently, the queries toward the ontology were determined, and a table of equivalent properties from COURAGE and CIDOC CRM was created. The structural diagrams that clarify the mapping process and construct queries are on progress to map person, organization, and collection entities to the ontology. Through mapping the COURAGE dataset to CIDOC-CRM ontology, the dataset will have a common ontological foundation with several other datasets. Therefore, the expected results are: 1) retrieving more detailed data about existing entities, 2) retrieving new entities’ data, 3) aligning COURAGE dataset to a standard vocabulary, 4) running distributed SPARQL queries over several CIDOC-CRM datasets and testing the potentials of distributed query answering using SPARQL. The next plan is to map CIDOC-CRM to other upper-level ontologies or large datasets (e.g., DBpedia, Wikidata), and address similar questions on a wide variety of knowledge bases.

Keywords: CIDOC CRM, cultural heritage data, COURAGE dataset, ontology alignment

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

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There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: Ren Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

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Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption

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Authors: Esraa Moustafa, Gaetan Rey, Stephane Lavirotte, Jean-Yves Tigli

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With the development of Internet of Things and Web of Things, computing becomes more pervasive, invisible and present everywhere. In fact, in our environment, we are surrounded by multiple devices that deliver (web) services that meet the needs of the users. However, the mobility of these devices as the users has important repercussions that challenge software design of these applications because the variability of the environment cannot be anticipated at the design time. Thus, it will be interesting to dynamically discover the environment and adapt the application during its execution to the new contextual conditions. We, therefore, propose a model of a context-aware middleware that can address this issue through a monitoring service that is capable of reasoning and observation channels capable of calculating the context during the runtime. The monitoring service evaluates the pre-defined X-Query predicates in the context manager and uses Prolog to deduce the services needed to respond back. An independent Observation Channel for each different predicate is then dynamically generated by the monitoring service depending on the current state of the environment. Each channel sends its result directly to the context manager which consequently calculates the context based on all the predicates’ results while preserving the reactivity of the self-adaptive system.

Keywords: auto-adaptation, context-awareness, middleware, reasoning engine

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Authors: Bahareh Yousefian, Laurel Smith Stvan

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Linguistic structures have two facades: form and meaning. These structures could have either literal meaning or figurative meaning (although it could also depend on the context in which that structure appears). The literal meaning is understandable more easily, but for the figurative meaning, a word or concept is understood from a different word or concept. In linguistic structures with a figurative meaning, it’s more difficult to relate their forms to the meanings than structures with literal meaning. In these cases, the relationship between form and figurative meaning could be studied from different perspectives. Various linguists have been curious about what happens in someone’s mind to understand figurative meaning through the forms; they have used different perspectives and theories to explain this process. It has been studied through cognitive linguistics as well, in which mind and mental activities are really important. In this viewpoint, meaning (in other words, conceptualization) is considered a mental process. In this descriptive-analytic study, 20 Persian compound nouns with figurative meanings have been collected from the Persian-language Moeen Encyclopedic Dictionary and other sources. Examples include [“Sofreh Xaneh”] (traditional restaurant) and [“Dast Yar”] (Assistant). These were studied in a cognitive semantics framework using “Conceptual Blending Theory” which hasn’t been tested on Persian compound nouns before. It was noted that “Conceptual Blending Theory” could lead to the process of understanding the figurative meanings of Persian compound nouns. Many cognitive linguists believe that “Conceptual Blending” is not only a linguistic theory but it’s also a basic human cognitive ability that plays important roles in thought, imagination, and even everyday life as well (though unconsciously). The ability to use mental spaces and conceptual blending (which is exclusive to humankind) is such a basic but unconscious ability that we are unaware of its existence and importance. What differentiates Conceptual Blending Theory from other ways of understanding figurative meaning, are arising new semantic aspects (emergent structure) that lead to a more comprehensive and precise meaning. In this study, it was found that Conceptual Blending Theory could explain reaching the figurative meanings of Persian compound nouns from their forms, such as [talkative for compound word of “Bolbol + Zabani” (nightingale + tongue)] and [wage for compound word of “Dast + Ranj” (hand + suffering)].

Keywords: cognitive linguistics, conceptual blending, figurative meaning, Persian compound nouns

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Authors: S. Shamohammadi, L. Razavi

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This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.

Keywords: model, mathematical, retention, watershed, SCS

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Chukwuma Mgboji

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Since the advent of Artificial Intelligence, robots have become a major stay in developing societies. Robots are deployed in Education, Health, Food and in other spheres of life. Nigeria a country in West Africa has a very low profile in the advancement of Artificial Intelligence especially in the grass roots. The benefits of Artificial intelligence are not fully maximised and harnessed. Advances in artificial intelligence are perceived as impossible or observed as irrelevant. This study seeks to ascertain the needed skills for the development of artificialintelligence amongst secondary schools in Nigeria. The study focused on South East Nigeria with Five states namely Imo, Abia, Ebonyi, Anambra and Enugu. The sample size is 1000 students drawn from Five Government owned Universities offering Computer Science, Computer Education, Electronics Engineering across the Five South East states. Survey method was used to solicit responses from respondents. The findings from the study identified mathematical skills, analytical skills, problem solving skills, computing skills, programming skills, algorithm skills amongst others. The result of this study to the best of the author’s knowledge will be highly beneficial to all stakeholders involved in the advancements and development of artificial intelligence.

Keywords: artificial intelligence, secondary school, robotics, skills

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Philipp Galkin

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Government policy is a critical factor in the understanding of energy markets. Regardless, it is rarely approached systematically from a research perspective. Gaining a precise understanding of what policies exist, their intended outcomes, geographical extent, duration, evolution, etc. would enable the research community to answer a variety of questions that, for now, are either oversimplified or ignored. Policy, on its surface, also seems a rather unstructured and qualitative undertaking. There may be quantitative components, but incorporating the concept of policy analysis into quantitative analysis remains a challenge. The KAPSARC Energy Policy Database (KEPD) is intended to address these two energy policy research limitations. Our approach is to represent policies within a quantitative library of the specific policy measures contained within a set of legal documents. Each of these measures is recorded into the database as a single entry characterized by a set of qualitative and quantitative attributes. Initially, we have focused on the major laws at the national level that regulate coal in China. However, KAPSARC is engaged in various efforts to apply this methodology to other energy policy domains. To ensure scalability and sustainability of our project, we are exploring semantic processing using automated computer algorithms. Automated coding can provide a more convenient input data for human coders and serve as a quality control option. Our initial findings suggest that the methodology utilized in KEPD could be applied to any set of energy policies. It also provides a convenient tool to facilitate understanding in the energy policy realm enabling the researcher to quickly identify, summarize, and digest policy documents and specific policy measures. The KEPD captures a wide range of information about each individual policy contained within a single policy document. This enables a variety of analyses, such as structural comparison of policy documents, tracing policy evolution, stakeholder analysis, and exploring interdependencies of policies and their attributes with exogenous datasets using statistical tools. The usability and broad range of research implications suggest a need for the continued expansion of the KEPD to encompass a larger scope of policy documents across geographies and energy sectors.

Keywords: China, energy policy, policy analysis, policy database

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Authors: Zahira Anane, Abdelhafid Bayadi

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Corona in the HV overhead transmission lines is an important source of attenuation and distortion of overvoltage surges. This phenomenon of distortion, which is superimposed on the distortion by skin effect, is due to the dissipation of energy by injection of space charges around the conductor, this process with place as soon as the instantaneous voltage exceeds the threshold voltage of the corona effect conductors. This paper presents a mathematical model to determine the corona inception voltage, the critical electric field and the corona radius, to predict the capacitive changes at conductor of transmission line due to corona. This model has been incorporated into the Alternative Transients Program version of the Electromagnetic Transients Program (ATP/EMTP) as a user defined component, using the MODELS interface with NORTON TYPE94 of this program and using the foreign subroutine. For obtained the displacement of corona charge hell, dichotomy mathematical method is used for this computation. The present corona model can be used for computing of distortion and attenuation of transient overvoltage waves being propagated in a transmission line of the very high voltage electric power.

Keywords: high voltage, corona, Type94 NORTON, dichotomy, ATP/EMTP, MODELS, distortion, foreign model

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: Yusef Hedjazi, Saeedeh Nazari Nooghabi

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New information and communication technologies (ICT) as one of the main needs of Faculty members in the process of teaching and learning has used in Irans higher education system since 2000.The main purpose of this study is to investigate the role of information and communication technologies (ICT) in teaching performance of Agricultural and Natural Resources Faculties at University of Tehran. The statistical population of the study consisted of all 250 faculties in Agriculture and Natural Resources Colleges and a questionnaire was used to collect data. The reliability of the questionnaire was confirmed by computing of Cronbachs Alpha coefficient at greater than .72. The study showed a significant relationship between agricultural Faculty members teaching performance and competency in using ICT. The results of the regression analysis also explained 51.7% of the variance, teaching performance. The six independent variables that accounted for the explained variance were experience in using educational websites or software, use of educational multimedia (e.g. film and CD, etc), making a presentation using PowerPoint, familiarity with online education websites, using News group to discuss on educational subjects with colleagues and students, and using Electronic communication (messengers) to solve studentsproblems.

Keywords: information and communication technologies, agricultural and natural resources, faculties, teaching performance

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Marlene Weber, Joseph Giacomin, Alessio Malizia, Lee Skrypchuk, Voula Gkatzidou

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Technological and sociological developments in the automotive sector are shifting the focus of design towards developing a better understanding of driver needs, desires and emotions. Human centred design methods are being more frequently applied to automotive research, including the use of systems to detect human emotions in real-time. One method for a non-contact measurement of emotion with low intrusiveness is Facial-Expression Analysis (FEA). This paper describes a research study investigating emotional responses of 22 participants in a naturalistic driving environment by applying a multi-method approach. The research explored the possibility to investigate emotional responses and their frequencies during naturalistic driving through real-time FEA. Observational analysis was conducted to assign causes to the collected emotional responses. In total, 730 emotional responses were measured in the collective study time of 440 minutes. Causes were assigned to 92% of the measured emotional responses. This research establishes and validates a methodology for the study of emotions and their causes in the driving environment through which systems and factors causing positive and negative emotional effects can be identified.

Keywords: affective computing, case study, emotion recognition, human computer interaction

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Authors: Mustafa Elfituri, Jonathan Cook

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Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Onyekachi Onwudike, Russell Lock, Iain Phillips

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The variability that exists across governments, her departments and the provisioning of services has been areas of concern in the E-Government domain. There is a need for reuse and integration across government departments which are accompanied by varying degrees of risks and threats. There is also the need for assessment, prevention, preparation, response and recovery when dealing with these risks or threats. The ability of a government to cope with the emerging changes that occur within it is known as resilience. In order to forge ahead with concerted efforts to manage reuse and integration induced risks or threats to governments, the ambiguities contained within resilience must be addressed. Enhancing resilience in the E-Government domain is synonymous with reducing risks governments face with provisioning of services as well as reuse of components across departments. Therefore, it can be said that resilience is responsible for the reduction in government’s vulnerability to changes. In this paper, we present the use of the ontology to measure the resilience of governments. This ontology is made up of a well-defined construct for the taxonomy of resilience. A specific class known as ‘Resilience Requirements’ is added to the ontology. This class embraces the concept of resilience into the E-Government domain ontology. Considering that the E-Government domain is a highly complex one made up of different departments offering different services, the reliability and resilience of the E-Government domain have become more complex and critical to understand. We present questions that can help a government access how prepared they are in the face of risks and what steps can be taken to recover from them. These questions can be asked with the use of queries. The ontology focuses on developing a case study section that is used to explore ways in which government departments can become resilient to the different kinds of risks and threats they may face. A collection of resilience tools and resources have been developed in our ontology to encourage governments to take steps to prepare for emergencies and risks that a government may face with the integration of departments and reuse of components across government departments. To achieve this, the ontology has been extended by rules. We present two tools for understanding resilience in the E-Government domain as a risk analysis target and the output of these tools when applied to resilience in the E-Government domain. We introduce the classification of resilience using the defined taxonomy and modelling of existent relationships based on the defined taxonomy. The ontology is constructed on formal theory and it provides a semantic reference framework for the concept of resilience. Key terms which fall under the purview of resilience with respect to E-Governments are defined. Terms are made explicit and the relationships that exist between risks and resilience are made explicit. The overall aim of the ontology is to use it within standards that would be followed by all governments for government-based resilience measures.

Keywords: E-Government, Ontology, Relationships, Resilience, Risks, Threats

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Itissam Abuiziah

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In several hydraulic systems, it is necessary to calculate the head losses which depend on the resistance flow friction factor in Darcy equation. Computing the resistance friction is based on implicit Colebrook-White equation which is considered as the standard for the friction calculation, but it needs high computational cost, therefore; several explicit approximation methods are used for solving an implicit equation to overcome this issue. It follows that the relative error is used to determine the most accurate method among the approximated used ones. Steel, cast iron and polyethylene pipe materials investigated with practical diameters ranged from 0.1m to 2.5m and velocities between 0.6m/s to 3m/s. In short, the results obtained show that the suitable method for some cases may not be accurate for other cases. For example, when using steel pipe materials, Zigrang and Silvester's method has revealed as the most precise in terms of low velocities 0.6 m/s to 1.3m/s. Comparatively, Halland method showed a less relative error with the gradual increase in velocity. Accordingly, the simulation results of this study might be employed by the hydraulic engineers, so they can take advantage to decide which is the most applicable method according to their practical pipe system expectations.

Keywords: Colebrook–White, explicit equation, friction factor, hydraulic resistance, implicit equation, Reynolds numbers

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

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Authors: Yoon-Cheol Park

Abstract:

This research focuses on examining the information structures in the old Chinese character-Korean translation of the Vajrachedika-prajna-paramita sutra. The background of this research comes from the fact that there were no previous researches which looked into the information structures in the target text of the Vajrachedika-prajna-paramita sutra by now. The existing researches on the Buddhist scripture translation mainly put weight on message conveyance by literal and semantic translation methods. But the message conveyance from one language to another has a necessity to be delivered with equivalent information structure. Thus, this research is intended to investigate on the flow of old and new information in the target text of Buddhist scripture, compared with source text. The Vajrachedika-prajna-paramita sutra unlike other Buddhist scriptures is composed of conversational structures between Buddha and his disciple, Suboli. This implies that the information flow can be changed by utterance context and some propositions. So, this research tries to analyze the flow of old and new information within the source and target text. As a result of analysis, this research can discover the following facts; firstly, there are the differences of the information flow in the message conveyance between the old Chinese character and Korean by language features. The old Chinese character reveals that old-new information flow is developed, while Korean indicates new-old information flow because of word order. Secondly, the source text of the Vajrachedika-prajna-paramita sutra includes abstruse terminologies, jargon and abstract words. These make influence on the target text and cause the change of the information flow. But the repetitive expressions of these words provide the old information in the target text. Lastly, the Vajrachedika-prajna-paramita sutra offers the expository structure from conversations between Buddha and Suboli. It means that the information flow is developed in the way of explaining specific subjects and of paraphrasing unfamiliar phrases and expressions. From the results of analysis above, this research can verify that the information structures in the target text of the Vajrachedika-prajna-paramita sutra are changed by specific subjects and terminologies, developed with the new-old information flow by repetitive expressions or word order and reveal the information structures familiar to target culture. It also implies that the translation of the Vajrachedika-prajna-paramita sutra as a religious book needs the message conveyance to take into account the information structures of two languages.

Keywords: abstruse terminologies, the information structure, new and old information, old Chinese character-Korean translation

Procedia PDF Downloads 357

Authors: Jui-Hsueh Hu

Abstract:

This study investigated various models of refusal speech acts among three target groups: French learners of Mandarin Chinese (FM), Taiwanese native Mandarin speakers (TM), and native French speakers (NF). The refusal responses were analyzed in terms of their options, frequencies, and sequences and the contents of their semantic formulas. This study also examined differences in refusal strategies, as determined by social status and social distance, among the three groups. The difficulties of refusal speech acts encountered by FM were then generalized. The results indicated that Mandarin instructors of NF should focus on the different reasons for the pragmatic failure of French learners and should assist these learners in mastering refusal speech acts that rely on abundant cultural information. In this study, refusal policies were mainly classified according to the research of Beebe et al. (1990). Discourse completion questionnaires were collected from TM, FM, and NF, and their responses were compared to determine how refusal policies differed among the groups. This study not only emphasized the dissimilarities of refusal strategies between native Mandarin speakers and second-language Mandarin learners but also used NF as a control group. The results of this study demonstrated that regarding overall strategies, FM were biased toward NF in terms of strategy choice, order, and content, resulting in pragmatic transfer under the influence of social factors such as 'social status' and 'social distance,' strategy choices of FM were still closer to those of NF, and the phenomenon of pragmatic transfer of FM was revealed. Regarding the refusal difficulties among the three groups, the F-test in the analysis of variance revealed statistical significance was achieved for Role Playing Items 13 and 14 (P < 0.05). A difference was observed in the average number of refusal difficulties between the participants. However, after multiple comparisons, it was found that item 13 (unrecognized heterosexual junior colleague requesting contacts) was significantly more difficult for NF than for TM and FM; item 14 (contacts requested by an unrecognized classmate of the opposite sex) was significantly more difficult to refuse for NF than for TM. This study summarized the pragmatic language errors that most FM often perform, including the misuse or absence of modal words, hedging expressions, and empty words at the end of sentences, as the reasons for pragmatic failures. The common social pragmatic failures of FM include inaccurately applying the level of directness and formality.

Keywords: French Mandarin, interlanguage refusal, pragmatic transfer, speech acts

Procedia PDF Downloads 242

Authors: A. Grilec, S. Petrak, M. Mahnic Naglic

Abstract:

Technological development and the globalization in production and sales of clothing in the last decade have significantly influenced the changes in consumer relationship with the industrial-fashioned apparel and in the way of clothing purchasing. The Internet sale of clothing is in a constant and significant increase in the global market, but the possibilities offered by modern computing technologies in the customization segment are not yet fully involved, especially according to the individual customer requirements and body sizes. Considering the growing trend of online shopping, the main goal of this paper is to investigate the differences in customer perceptions towards online apparel shopping and particularly to discover the main differences in perceptions between customers regarding three different body sizes. In order to complete the research goal, the quantitative study on the sample of 85 Croatian consumers was conducted in 2017 in Zagreb, Croatia. Respondents were asked to indicate their level of agreement according to a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). To analyze attitudes of respondents, simple and descriptive statistics were used. The main findings highlight the differences in respondent perception of 3D body scanning, using 3D body scanning in Internet shopping, online apparel shopping habits regarding their body sizes.

Keywords: consumer behavior, Internet, 3D body scanning, body types

Procedia PDF Downloads 153

Authors: Mário Ernesto Sitoe, Orlando Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: A. Bayaga

Abstract:

This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

Procedia PDF Downloads 480

Authors: Yoji Yamato

Abstract:

In this paper, we propose an automatic verification technology of software patches for user virtual environments on IaaS Cloud to decrease verification costs of patches. In these days, IaaS services have been spread and many users can customize virtual machines on IaaS Cloud like their own private servers. Regarding to software patches of OS or middleware installed on virtual machines, users need to adopt and verify these patches by themselves. This task increases operation costs of users. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from test case DB, distributes patches to virtual machines on replicated environments and conducts those test cases automatically on replicated environments. We have implemented the proposed method on OpenStack using Jenkins and confirmed the feasibility. Using the implementation, we confirmed the effectiveness of test case creation efforts by our proposed idea of 2-tier abstraction of software functions and test cases. We also evaluated the automatic verification performance of environment replications, test cases extractions and test cases conductions.

Keywords: OpenStack, cloud computing, automatic verification, jenkins

Procedia PDF Downloads 471

Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

Abstract:

Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

Procedia PDF Downloads 431