Search results for: Butcher's fifth order Runge-Kutta approach

Authors: Ananya Sharma

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International Relations is a discipline of paradoxes. The State is the dominant political institution, with mainstream analysis theorizing the State, but theory remains at best a reactionary monolith. Critical Theorists have been pushing the envelope and to that extent, there has been a clear shift in the dominant discourse away from State-centrism to individuals and group-level behaviour. This paradigm shift has been accompanied with more nuanced conceptualizations of other variables at play–power, security, and trust, to name a few. Yet, the ambit of “what is discussed” remains primarily embedded in realist conceptualizations. With this background in mind, this paper will attempt to understand, juxtapose and evaluate how “order” has been conceptualized in International Relations theory. This paper is a tentative attempt to present a “state of the art” and in the process, set the stage for a deeper study to draw attention to what the author feels is a gaping lacuna in IR theory. The paper looks at how different branches of international relations theory envisage world order and the silences embedded therein. Further, by locating order and disorder inhabiting the same reality along a continuum, alternative readings of world orders are drawn from the critical theoretical traditions, in which various articulations of justice impart the key normative pillar to the world order.

Keywords: global justice, international relations theory, legitimacy, world order

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Authors: B. SahaRoy, T. Medhi, S. C. Saha

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To understand the friction stir welding process, it is very important to know the nature of the material flow in and around the tool. The process is a combination of both thermal as well as mechanical work i.e it is a coupled thermo-mechanical process. Numerical simulations are very much essential in order to obtain a complete knowledge of the process as well as the physics underlying it. In the present work a model based approach is adopted in order to study material flow. A thermo-mechanical based CFD model is developed using a Finite Element package, Comsol Multiphysics. The fluid flow analysis is done. The model simultaneously predicts shear strain fields, shear strain rates and shear stress over the entire workpiece for the given conditions. The flow fields generated by the streamline plot give an idea of the material flow. The variation of dynamic viscosity, velocity field and shear strain fields with various welding parameters is studied. Finally the result obtained from the above mentioned conditions is discussed elaborately and concluded.

Keywords: AA6061-T6, CFD modelling, friction stir welding, material flow

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

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In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Radhwane Boudjelthia

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The most recent earthquakes that occurred in the world and particularly in Algeria, have killed thousands of people and severe damage. The example that is etched in our memory is the last earthquake in the regions of Boumerdes and Algiers (Boumerdes earthquake of May 21, 2003). For all the actors involved in the building process, the earthquake is the litmus test for construction. The goal we set ourselves is to contribute to the implementation of a thoughtful approach to the seismic protection of structures. For many engineers, the most conventional approach protection works (buildings and bridges) the effects of earthquakes is to increase rigidity. This approach is not always effective, especially when there is a context that favors the phenomenon of resonance and amplification of seismic forces. Therefore, the field of earthquake engineering has made significant inroads among others catalyzed by the development of computational techniques in computer form and the use of powerful test facilities. This has led to the emergence of several innovative technologies, such as the introduction of special devices insulation between infrastructure and superstructure. This approach, commonly known as "seismic isolation" to absorb the significant efforts without the structure is damaged and thus ensuring the protection of lives and property. In addition, the restraints to the construction by the ground shaking are located mainly at the supports. With these moves, the natural period of construction is increasing, and seismic loads are reduced. Thus, there is an attenuation of the seismic movement. Likewise, the insulation of the base mechanism may be used in combination with earthquake dampers in order to control the deformation of the insulation system and the absolute displacement of the superstructure located above the isolation interface. On the other hand, only can use these earthquake dampers to reduce the oscillation amplitudes and thus reduce seismic loads. The use of damping devices represents an effective solution for the rehabilitation of existing structures. Given all these acceleration reducing means considered passive, much research has been conducted for several years to develop an active control system of the response of buildings to earthquakes.

Keywords: earthquake, building, seismic forces, displacement, resonance, response

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Nilesh Pancholi, Mangal Bhatt

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This paper highlights comparative results of traditional FMECA and multi-factor decision-making approach based on “Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)” for aluminum wire rolling mill plant. The suggested study is carried out to overcome the limitations of FMECA by assigning the scores against each failure modes in crisp values to evaluate the criticalities of the failure modes without uncertainty. The primary findings of the paper are that sudden impact on the rolls seems to be most critical failure cause and high contact stresses due to rolling & sliding action of mesh to be least critical failure cause. It is suggested to modify the current control practices with proper maintenance strategy based on achieved maintainability criticality index (MCI). The outcome of the study will be helpful in deriving optimized maintenance plan to maximize the performance of continuous process industry.

Keywords: reliability, maintenance, FMECA, TOPSIS, process industry

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Authors: Guang Zou, Kian Banisoleiman, Arturo González

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Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally, there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach.

Keywords: crack initiation, fatigue reliability, inspection planning, welded joints

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Wagner Pereira, Alphonse Kelecom

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Mining can impact the environment, and the major impact of some mining activities is the radiological impact. In human populations, such impact is well studied and regulated. For biota, this assessment always had as focus the protection of human food chain. The protection of biota itself is a new approach, still developing. In order to contribute to this new approach, fish collecting was carried out in areas of naturally occurring radioactive materials (NORM), where a uranium mine is in decommissioning phase. The activity concentrations were analyzed, in Bq/kg wet weight, for Uranium (Unat), Th-232 and Ra-226 in the lambari fish Astyanax bimaculatus L. (omnivorous fish) and in the traíra fish Hoplias malabaricus Bloch, 1794 (carnivorous fish). Seven composite samples (that is: a sufficient number of individuals to reach at least 2 kg of fresh weight) were collected every six months between 2013 and 2015. The mean activity concentrations (AC) for uranium ranged from 1.12 (lambari) to 0.60 (lungfish). For Th, variations ranged from 0.30 to 0.05 (lambari and traíra, respectively). Finally, the Ra-226 means ranged between 0.08 and 0.03. No temporal trends of accumulation could be identified. Systematically, the AC values of radionuclides were higher in omnivorous fish when compared to the carnivore ones.

Keywords: biota dose, NORM, fish, environmental protection

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Authors: Matthias Steffan, Franz Haas

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The production process grinding is one of the latest steps in a value-added manufacturing chain. Within this step, workpiece geometry and surface roughness are determined. Up to this process stage, considerable costs and energy have already been spent on components. According to the current state of the art, therefore, large safety reserves are calculated in order to guarantee a process capability. Especially for non-circular grinding, this fact leads to considerable losses of process efficiency. With present technology, various non-circular geometries on a workpiece must be grinded subsequently in an oscillating process where X- and Q-axis of the machine are coupled. With the approach of RPM-Synchronous Noncircular Grinding, such workpieces can be machined in an ordinary plung grinding process. Therefore, the workpieces and the grinding wheels revolutionary rate are in a fixed ratio. A non-circular grinding wheel is used to transfer its geometry onto the workpiece. The authors use a worldwide unique machine tool that was especially designed for this technology. Highest revolution rates on the workpiece spindle (up to 4500 rpm) are mandatory for the success of this grinding process. This grinding approach is performed in a two-step process. For roughing, a highly porous vitrified bonded grinding wheel with medium grain size is used. It ensures high specific material removal rates for efficiently producing the non-circular geometry on the workpiece. This process step is adapted by a force control algorithm, which uses acquired data from a three-component force sensor located in the dead centre of the tailstock. For finishing, a grinding wheel with a fine grain size is used. Roughing and finishing are performed consecutively among the same clamping of the workpiece with two locally separated grinding spindles. The approach of RPM-Synchronous Noncircular Grinding shows great efficiency enhancement in non-circular grinding. For the first time, three-dimensional non-circular shapes can be grinded that opens up various fields of application. Especially automotive industries show big interest in the emerging trend in finishing machining.

Keywords: efficiency enhancement, finishing machining, non-circular grinding, rpm-synchronous grinding

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Authors: Guillermo Manuel Flores Figueroa, Juan Alejandro Vazquez Feijoo, Jose Navarro Antonio

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A continuous nonlinear system response may be obtained by an infinite sum of the so-called Volterra operators. Each operator is obtained from multidimensional convolution of nth-order between the nth-order Volterra kernel and the system input. These operators can also be obtained from the Associated Linear Equations (ALEs) that are linear models of subsystems which inputs and outputs are of the same nth-order. Each ALEs produces a particular nth-Volterra operator. As linear models a unitary impulse response can be obtained from them. This work shows the relationship between this unitary impulse responses and the corresponding order Volterra kernel.

Keywords: Volterra series, frequency response functions FRF, associated linear equations ALEs, unitary response function, Voterra kernel

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Authors: Akintunde O. Osibamowo, Abdulrasaq O. Olusanya

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The present study was designed to examine the effect of problem-solving approach as a medium of instruction in teaching and learning of mathematics to improve the achievement of the student. One Hundred (100) students were randomly chosen from five (5) Junior Secondary School in Ijebu-Ode Local Government Area of Ogun State, Nigeria. The data was collected through Mathematics Achievement Test (MAT) on the two groups (experimental and control group). The study confirmed that there is a significant different in the achievement of students exposed to problem-solving approach than those not exposed. The result also indicated that male students, however, had a greater mean-score than the female with no significant difference in their achievement. The result of the study supports the use of problem-solving approach in the teaching and learning of mathematics in secondary schools.

Keywords: problem, achievement, teaching phases, experimental control

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Authors: K. D. Candido, A. Lissounov, I. Knezevic, N. Knezevic

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Background: The most commonly performed pain procedures in the USA is Lumbar Epidural Steroid Injections (LESI). There are three main types of these procedures: transforaminal (TF), interlaminar (IL) and caudal injections. It is expected for TF injections to have better outcomes than IL injections, based on the recently published systematic review. The studies presented in that review used a midline IL approach, but those with parasagittal IL approach were not taken into consideration. Our aim is to emphasize the efficacy of the lateral parasagittal (paramedian) IL approach in this review. Methods: We included five studies in this systematic review, which compared Parasagittal-IL (PIL) with either Midline-IL (MIL) or TF LESI. Total of 296 patients who had undergone different types of LESI were observed across the five studies, and the average pain and functional improvements were calculated and compared among groups. Results: Pain and function improvements with PIL approach is superior on 12 months follow up to MIL approach (53.4% vs. 14.7%) and (55% vs. 27.7%), respectively. A 12 months follow-up results between PIL and TF shows a near equivalent effectiveness for pain (58.9% vs. 63.2%) and function improvement (47.3% vs. 48.1%). An average follow-up of 17.1 days have shown better short-term pain relief for PIL than TF approach (45.8% vs. 19.2%), respectively. Number of repeated injections is lower for PIL injections than MIL. Number of weeks between 1st and 2nd injections: PIL averaged 15.8 weeks and MIL averaged 9.7 weeks. Third LESI injection is more common in TF group (30%) than PIL group (18.8%). Conclusion: Higher complication rates are associated with TF injections for which FDA7 issued an official warning. We have recorded better outcomes in pain and function improvement of Parasagittal-IL LESI as compared to midline-IL injection, in the presented systematic review. Parasagittal and TF injections have equivalent efficacy in Pain and Function improvements thus we advocate for Parasagittal-IL approach consideration as an alternative for TF injections.

Keywords: parasagital approach, lumbar, back pain, epidural steroid injection

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Authors: Mohammad Alnabhan, Awni Hammouri, Mustafa Hammad, Anas Al-Badareen, Omamah Al-Thnebat

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Software visualization is one of the main techniques used to simplify the presentation of software systems and enhance their understandability. It is used to present the software system in a visual manner using simple, clear and meaningful symbols. This study proposes a new 2D software visualization approach. In this approach, each class is represented by rectangle, the name of the class placed above the rectangle, the size of class (Line of Code) represented by the height of the rectangle. The methods and the attributes are represented by circles and triangles respectively. The relationships among classes correspond to arrows. The proposed visualization approach was evaluated in terms of applicability and efficiency. Results have confirmed successful implementation of the proposed approach, and its ability to provide a simple and effective graphical presentation of extracted software components and properties.

Keywords: software visualization, software metrics, calling relationships, 2D graphs

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Authors: Shruti Soudi, Anushka Nayak

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Altruism is a voluntary helping behavior that is not motivated by rewards. The empathy-altruism hypothesis states that altruistic behavior results from empathy, a constant emotional response between the helper and the individual in need. Individual variances in familiar ways of thinking, feeling, and acting are called personalities. The personality of an individual determines their behavior. More importantly, Adler was among the first psychologists to document the importance of birth order on personality. The present study aims to understand the influence of personality and birth order on altruism. A questionnaire consisting of standardized tools to measure altruism (Hindi Self Report Altruism Scale) and personality (Big Five Personality Inventory) will aid in studying the relationship between these variables among young adults in India. A statistical analysis of the data will be completed using ANOVA and T-Test in the SPSS Software.

Keywords: altruism, personality, birth order, ANOVA, young adults

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Authors: Y. Fandja, O. Colot, M. Croquet

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Small and medium-sized firms (SMEs) face difficulties in accessing bank credit. Bank credit is actually the main source of external financing for SMEs. In general, SMEs are risky businesses because of the potential opacity maintained by the leader in the management of affairs, the agency conflicts between business owners and third-party funders and the potential opportunism of the leader due to the incompleteness of the contracts. These elements accentuate the problems of information asymmetries between SMEs and bankers leading to capital rationing. Moreover, the last economic crisis reinforced this rationing of capital. However, a long-term relationship between SMEs and their bank would enable the latter to accumulate a set of relevant information allowing the reduction of information asymmetry and, consequently, the reduction of credit rationing. The objective of this research is to investigate the lived experience of SMEs loan officers in their relationships with their clients in order to understand how these relationships can affect the financing structure of these SMEs. To carry out this research, an Interpretative Phenomenological Analysis is implemented. This approach is part of the constructivist paradigm and refers to the subjective narratives of the individual rather than to an objective description of the facts. The role of the researcher is to explore the lived experience of the interviewees and to try to understand the meaning they give to this experience. Currently, several sixty-minute semi-structured interviews with loan officers for SMEs have been conducted. The analysis of the content of these interviews brought out three main themes. First, the relationship between the credit officer and the company manager is complex because the credit officer is not aware of establishing a personal relationship with his client. Second; the emotional involvement in the bank financing decision is present and third, the trust in the relationship between the credit officer and his client is very important. The originality of this research is to use the interpretative phenomenological analysis more specific to psychology and sociology in order to approach in a different way the problem of the financing of SMEs through their particular relations with the bankers.

Keywords: financing structure, interpretative phenomenological analysis, relationship financing, SME

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Authors: Florian Vincent Haase, Adrian Dierl, Anna Henke, Ralf Woll, Ennes Sarradj

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Structured sheet metals and structured sandwich sheet metals are three-dimensional, lightweight structures with increased stiffness which are used in the automotive industry. The impedance, a figure of resistance of a structure to vibrations, will be determined regarding plain sheets, structured sheets, and structured sandwich sheets. The aim of this paper is generating an experimental design in order to minimize costs and duration of experiments. The design of experiments will be used to reduce the large number of single tests required for the determination of correlation between the impedance and its influencing factors. Full and fractional factorials are applied in order to systematize and plan the experiments. Their major advantages are high quality results given the relatively small number of trials and their ability to determine the most important influencing factors including their specific interactions. The developed full factorial experimental design for the study of plain sheets includes three factor levels. In contrast to the study of plain sheets, the respective impedance analysis used on structured sheets and structured sandwich sheets should be split into three phases. The first phase consists of preliminary tests which identify relevant factor levels. These factor levels are subsequently employed in main tests, which have the objective of identifying complex relationships between the parameters and the reference variable. Possible post-tests can follow up in case additional study of factor levels or other factors are necessary. By using full and fractional factorial experimental designs, the required number of tests is reduced by half. In the context of this paper, the benefits from the application of design for experiments are presented. Furthermore, a multistage approach is shown to take into account unrealizable factor combinations and minimize experiments.

Keywords: structured sheet metals, structured sandwich sheet metals, impedance measurement, design of experiment

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Chanon Promsakon, Sayan Panma

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Let S be a finite semigroup, A a subset of S and f an endomorphism on S. The endo-Cayley digraph of a semigroup S corresponding to a connecting set A and an endomorphism f, denoted by endo − Cayf (S, A) is a digraph whose vertex set is S and a vertex u is adjacent to a vertex v if and only if v = f(u)a for some a ∈ A. A digraph D is called undirected if any edge uv in D, there exists an edge vu in D. We consider the undirectedness of an endo-Cayley of a cyclic group of order prime, Zp. In this work, we investigate conditions for connecting sets and endomorphisms to make endo-Cayley digraphs of cyclic groups of order primes be undirected. Moreover, we give some conditions for an undirected endo-Cayley of cycle group of any order.

Keywords: endo-Cayley graph, undirected digraphs, cyclic groups, endomorphism

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Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan

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We analyze stochastic integrals associated with a mutation process. To be specific, we describe the cell population process and derive the differential equations for the joint generating functions for the number of mutants and their integrals in generating functions and their applications. We obtain first-order moments of the processes of the two-way mutation process in first-order moment structure of X (t) and Y (t) and the second-order moments of a one-way mutation process. In this paper, we obtain the limiting behaviour of the integrals in limiting distributions of X (t) and Y (t).

Keywords: stochastic integrals, single–server queue model, catastrophes, busy period

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Haruo Okabayashi

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The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon

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Authors: Jai Prakash Verma, Khushboo Verma

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In the present paper, a pair of Mond-Weir type non-differentiable multiobjective second-order programming problems, involving two kernel functions, where each of the objective functions contains support function, is formulated. We prove weak, strong and converse duality theorem for the second-order symmetric dual programs under η-pseudoinvexity conditions.

Keywords: non-differentiable multiobjective programming, second-order symmetric duality, efficiency, support function, eta-pseudoinvexity

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Authors: Beatrice Wamuyu Muchiri, Monika M. L. Dos Santos

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An increasingly recognised prevention approach for substance use entails reduction in risk factors and enhancement of promotive or protective factors in individuals and the environment surrounding them during their growth and development. However, in order to enhance the effectiveness of this approach, continuous study of risk aspects targeting different cultures, social groups and mixture of society has been recommended. This study evaluated the impact of potential risk and protective factors associated with family management and relations on adolescent substance abuse in South Africa. Exploratory analysis and cumulative odds ordinal logistic regression modelling was performed on the data while controlling for demographic and socio-economic characteristics on adolescent substance use. The most intensely used substances were tobacco, cannabis, cocaine, heroin and alcohol in decreasing order of use intensity. The specific protective or risk impact of family management or relations factors varied from substance to substance. Risk factors associated with demographic and socio-economic factors included being male, younger age, being in lower education grades, coloured ethnicity, adolescents from divorced parents and unemployed or fully employed mothers. Significant family relations risk and protective factors against substance use were classified as either family functioning and conflict or family bonding and support. Several family management factors, categorised as parental monitoring, discipline, behavioural control and rewards, demonstrated either risk or protective effect on adolescent substance use. Some factors had either interactive risk or protective impact on substance use or lost significance when analysed jointly with other factors such as controlled variables. Interaction amongst risk or protective factors as well as the type of substance should be considered when further considering interventions based on these risk or protective factors. Studies in other geographical regions, institutions and with better gender balance are recommended to improve upon the representativeness of the results. Several other considerations to be made when formulating interventions, the shortcomings of this study and possible improvements as well as future studies are also suggested.

Keywords: risk factors, protective factors, substance use, adolescents

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Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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Authors: Jihane Saad, Thomas Lendormi, Caroline Le Marechal, Anne-marie Pourcher, Céline Druilhe, Jean-louis Lanoiselle

Abstract:

Agricultural anaerobic digestion consists in the conversion of animal slurry and manure into biogas and digestate. They need, however, to be treated at 70 ºC during 60 min before anaerobic digestion according to the European regulation (EC n°1069/2009 & EU n°142/2011). The impact of such heat treatment on the outcome of bacteria has been poorly studied up to now. Moreover, a recent study¹ has shown that enterococci and clostridia are still detected despite the application of such thermal treatment, questioning the relevance of this approach for the hygienisation of digestate. The aim of this study is to establish the heat inactivation kinetics of two species of enterococci (Enterococcus faecalis and Enterococcus faecium) and two species of clostridia (Clostridioides difficile and Clostridium novyi as a non-toxic model for Clostridium botulinum of group III). A pure culture of each strain was prepared in a specific sterile medium at concentration of 10⁴ – 10⁷ MPN / mL (Most Probable number), depending on the bacterial species. Bacterial suspensions were then filled in sterilized capillary tubes and placed in a water or oil bath at desired temperature for a specific period of time. Each bacterial suspension was enumerated using a MPN approach, and tests were repeated three times for each temperature/time couple. The inactivation kinetics of the four indicator bacteria is described using the Weibull model and the classical Bigelow model of first-order kinetics. The Weibull model takes biological variation, with respect to thermal inactivation, into account and is basically a statistical model of distribution of inactivation times as the classical first-order approach is a special case of the Weibull model. The heat treatment at 70 ºC / 60 min contributes to a reduction greater than 5 log10 for E. faecium and E. faecalis. However, it results only in a reduction of about 0.7 log10 for C. difficile and an increase of 0.5 log10 for C. novyi. Application of treatments at higher temperatures is required to reach a reduction greater or equal to 3 log10 for C. novyi (such as 30 min / 100 ºC, 13 min / 105 ºC, 3 min / 110 ºC, and 1 min / 115 ºC), raising the question of the relevance of the application of heat treatment at 70 ºC / 60 min for these spore-forming bacteria. To conclude, the heat treatment (70 ºC / 60 min) defined by the European regulation is sufficient to inactivate non-sporulating bacteria. Higher temperatures (> 100 ºC) are required as far as spore-forming bacteria concerns to reach a 3 log10 reduction (sporicidal activity).

Keywords: heat treatment, enterococci, clostridia, inactivation kinetics

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

Abstract:

Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina

Procedia PDF Downloads 130