Search results for: complex polynomials

Authors: Akhilesh G. Naik, Dipankar Pal

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In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba, Looped Karatsuba.

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Authors: Pi-Chung Hsu

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Super-quadrics can represent a set of implicit surfaces, which can be used furthermore as primitive surfaces to construct a complex object via Boolean set operations in implicit surface modeling. In fact, super-quadrics were developed to create a parametric surface by performing spherical product on two parametric curves and some of the resulting parametric surfaces were also represented as implicit surfaces. However, because not every parametric curve can be redefined implicitly, this causes only implicit super-elliptic and super-hyperbolic curves are applied to perform spherical product and so only implicit super-ellipsoids and hyperboloids are developed in super-quadrics. To create implicit surfaces with more diverse shapes than super-quadrics, this paper proposes an implicit representation of spherical product, which performs spherical product on two implicit curves like super-quadrics do. By means of the implicit representation, many new implicit curves such as polygonal, star-shaped and rose-shaped curves can be used to develop new implicit surfaces with a greater variety of shapes than super-quadrics, such as polyhedrons, hyper-ellipsoids, superhyperboloids and hyper-toroids containing star-shaped and roseshaped major and minor circles. Besides, the newly developed implicit surfaces can also be used to define new primitive implicit surfaces for constructing a more complex implicit surface in implicit surface modeling.

Keywords: Implicit surfaces, Soft objects, Super-quadrics.

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Authors: Ahmed Mansouri, Naoji Matsumoto

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This research is a comparative study of complexity, as a multidimensional concept, in the context of streetscape composition in Algeria and Japan. 80 streetscapes visual arrays have been collected and then presented to 20 participants, with different cultural backgrounds, in order to be categorized and classified according to their degrees of complexity. Three analysis methods have been used in this research: cluster analysis, ranking method and Hayashi Quantification method (Method III). The results showed that complexity, disorder, irregularity and disorganization are often conflicting concepts in the urban context. Algerian daytime streetscapes seem to be balanced, ordered and regular, and Japanese daytime streetscapes seem to be unbalanced, regular and vivid. Variety, richness and irregularity with some aspects of order and organization seem to characterize Algerian night streetscapes. Japanese night streetscapes seem to be more related to balance, regularity, order and organization with some aspects of confusion and ambiguity. Complexity characterized mainly Algerian avenues with green infrastructure. Therefore, for Japanese participants, Japanese traditional night streetscapes were complex. And for foreigners, Algerian and Japanese avenues nightscapes were the most complex visual arrays.

Keywords: Streetscape, Nightscape, Complexity, Visual Array, Affordance, Cluster Analysis, Hayashi Quantification Method.

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Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: Toolpath, part program, optimization, pocket.

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Authors: Chongyang Ye, Rong Liu

Abstract:

Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: Elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis.

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

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This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Markus Kaiser, Johannes Buchmann

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In this article we explore the application of a formal proof system to verification problems in cryptography. Cryptographic properties concerning correctness or security of some cryptographic algorithms are of great interest. Beside some basic lemmata, we explore an implementation of a complex function that is used in cryptography. More precisely, we describe formal properties of this implementation that we computer prove. We describe formalized probability distributions (σ-algebras, probability spaces and conditional probabilities). These are given in the formal language of the formal proof system Isabelle/HOL. Moreover, we computer prove Bayes- Formula. Besides, we describe an application of the presented formalized probability distributions to cryptography. Furthermore, this article shows that computer proofs of complex cryptographic functions are possible by presenting an implementation of the Miller- Rabin primality test that admits formal verification. Our achievements are a step towards computer verification of cryptographic primitives. They describe a basis for computer verification in cryptography. Computer verification can be applied to further problems in cryptographic research, if the corresponding basic mathematical knowledge is available in a database.

Keywords: prime numbers, primality tests, (conditional) probabilitydistributions, formal proof system, higher-order logic, formalverification, Bayes' Formula, Miller-Rabin primality test.

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Authors: P. D. Pastuszak

Abstract:

The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: Active thermography, finite element analysis, composite, curved structures, defects.

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Authors: M. Watanabe, T. Yamaguchi, M. Sasajima, Y. Kurosawa, Y. Koike

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Headphones and earphones have many extremely small holes or narrow slits; they use sound-absorbing or porous material (i.e., dampers) to suppress vibratory system resonance. The air viscosity in these acoustic paths greatly affects the acoustic properties. Simulation analyses such as the finite element method (FEM) therefore require knowledge of the material properties of sound-absorbing or porous materials, such as the characteristic impedance and propagation constant. The transfer function method using acoustic tubes is a widely known measuring method, but there is no literature on taking measurements up to the audible range. To measure the acoustic properties at high-range frequencies, the acoustic tubes that form the measuring device need to be narrowed, and the distance between the two microphones needs to be reduced. However, when the tubes are narrowed, the characteristic impedance drops below the air impedance. In this study, we considered the effect of air viscosity in an acoustical tube, introduced a theoretical formula for this effect in the form of complex density and complex sonic velocity, and verified the theoretical formula. We also conducted an experiment and observed the effect from air viscosity in the actual measurements.

Keywords: acoustic tube, air viscosity, earphones, FEM, porous material, sound-absorbing material, transfer function method

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Authors: A. K. Aswathy, Asha Manoharan, Arya Manoharan

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The purpose of this study are to define the nature of oral sensory issues in children with autism spectrum disorder (ASD), identify important components of the assessment and treatment of this issues specific to this population, and delineate specific therapeutic techniques designed to improve assessment and treatment within therapeutic settings. Literature review and case example is used to define the predominant nature of the oral sensory issues that are experienced by some children on the autism spectrum. Characteristics of this complex disorder that can have an impact on feeding skill and behavior are also identified. These factors are then integrated to create assessment and intervention techniques that can be used in conjunction with traditional feeding approaches to facilitate improvements in eating as well as reducing oral apraxic component in this unique population. The complex nature of ASD and its many influences on feeding skills and behavior create the need for modification to both assessment and treatment approaches. Additional research is needed to create therapeutic protocols that can be used by speech-language pathologists to effectively assess and treat feeding and oro motor apraxic difficulties that are commonly encountered in children with ASD.

Keywords: Autism, feeding, intervention, oral sensory issues, oral apraxia.

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Authors: Markus Kaiser, Johannes Buchmann

Abstract:

In this paper we explore the application of a formal proof system to verification problems in cryptography. Cryptographic properties concerning correctness or security of some cryptographic algorithms are of great interest. Beside some basic lemmata, we explore an implementation of a complex function that is used in cryptography. More precisely, we describe formal properties of this implementation that we computer prove. We describe formalized probability distributions (o--algebras, probability spaces and condi¬tional probabilities). These are given in the formal language of the formal proof system Isabelle/HOL. Moreover, we computer prove Bayes' Formula. Besides we describe an application of the presented formalized probability distributions to cryptography. Furthermore, this paper shows that computer proofs of complex cryptographic functions are possible by presenting an implementation of the Miller- Rabin primality test that admits formal verification. Our achievements are a step towards computer verification of cryptographic primitives. They describe a basis for computer verification in cryptography. Computer verification can be applied to further problems in crypto-graphic research, if the corresponding basic mathematical knowledge is available in a database.

Keywords: prime numbers, primality tests, (conditional) proba¬bility distributions, formal proof system, higher-order logic, formal verification, Bayes' Formula, Miller-Rabin primality test.

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Authors: Yong W. Foo, Lai M. Tang

Abstract:

Artificial Intelligence (AI), particularly the usage of deep neural networks for hierarchical representations from data, has found numerous complex applications across various domains, including computer vision, robotics, autonomous vehicles, and other scientific fields. However, their inherent “black box” nature can sometimes make it challenging for early researchers or school students of various levels to comprehend and trust the results they produce. Consequently, there has been a growing demand for reliable visualization tools in engineering and science education to help learners understand, trust, and explain a deep learning network. This has led to a notable emphasis on the visualization of AI in the research community in recent years. AI visualization tools are increasingly being adopted to significantly improve the comprehension of complex topics in deep learning. This paper presents an approach to empower students to actively explore the inner workings of deep neural networks by integrating the student-centered learning approach of flipped classroom models with the investigative capabilities of AI visualization tools, namely, the TensorFlow Playground, the Local Interpretable Model-agnostic Explanations (LIME), and the SHapley Additive exPlanations (SHAP), for delivering an AI education curriculum. Integrating these two factors is crucial for fostering ownership, responsibility, and critical thinking skills in the age of AI.

Keywords: Deep Learning, Explainable AI, AI Visualization, Representation Learning.

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Authors: Liubov A. Magerramova, Mikhail A. Petrov, Vladimir V. Isakov, Liana A. Shcherbinina, Suren G. Gukasyan, Daniil V. Povalyukhin, Olga G. Klimova-Korsmik, Darya V. Volosevich

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Aircraft engines are developing along the path of increasing resource, strength, reliability, and safety. The building of gas turbine engine body parts is a complex design and technological task. Particularly complex in the design and manufacturing are the casings of the input stages of helicopter gearboxes and central drives of aircraft engines. Traditional technologies, such as precision casting or isothermal forging, are characterized by significant limitations in parts production. For parts like housing, additive technologies guarantee spatial freedom and limitless or flexible design. This article presents the results of computational and experimental studies. These investigations justify the applicability of additive technologies (AT) to reduce the weight of aircraft housing gearbox parts by up to 32%. This is possible due to geometrical optimization compared to the classical, less flexible manufacturing methods and as-casted aircraft parts with over-insured values of safety factors. Using an example of the body of the input stage of an aircraft gearbox, visualization of the layer-by-layer manufacturing of a part based on thermal deformation was demonstrated.

Keywords: Additive technologies, gas turbine engines, geometric optimization, weight reduction.

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Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry 4.0, sensor dashboard design, Cyber-physical production system, Interface designer.

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Authors: Lamia Hammadi, Abdellah Ait Ouhman, Aomar Ibourk

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It is widely assumed that the case of Customs Supply Chain is classified as a complex system, due to not only the variety and large number of actors, but also their complex structural links, and the interactions between these actors, that’s why this system is subject to various types of Risks. The economic, political and social impacts of those risks are highly detrimental to countries, businesses and the public, for this reason, Risk management in the customs supply chain is becoming a crucial issue to ensure the sustainability, security and safety. The main characteristic of customs risk management approach is determining which goods and means of transport should be examined? To what extend? And where future compliance resources should be directed? The purposes of this article are, firstly to deal with the concept of customs supply chain, secondly present our risk management approach based on Cross Activity Based Costing (ABC) Method as an interactive tool to support decision making in customs risk management. Finally, analysis of case study of Moroccan customs to putting theory into practice and will thus draw together the various elements of a structured and efficient risk management approach.

Keywords: Cross ABC Method, Customs Supply Chain, Risk, Risk Management.

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Authors: Juliana Panova

Abstract:

Severe symptoms, such as dissociation, depersonalization, self-mutilation, suicidal ideations and gestures, are the main reasons for a person to be diagnosed with Borderline Personality Disorder (BPD) and admitted to an inpatient Psychiatric Hospital. However, these symptoms are also indicators of a severe traumatic history as indicated by the extensive research on the topic. Unfortunately patients with such clinical presentation often are treated repeatedly only for their symptomatic behavior, while the main cause for their suffering, the trauma itself, is usually left unaddressed therapeutically. All of the highly structured, replicable, and manualized treatments lack the recognition of the uniqueness of the person and fail to respect his/her rights to experience and react in an idiosyncratic manner. Thus the communicative and adaptive meaning of such symptomatic behavior is missed. Only its pathological side is recognized and subjected to correction and stigmatization, and the message that the person is damaged goods that needs fixing is conveyed once again. However, this time the message would be even more convincing for the victim, because it is sent by mental health providers, who have the credibility to make such a judgment. The result is a revolving door of very expensive hospitalizations for only a temporary and patchy fix. In this way the patients, once victims of abuse and hardship are left invalidated and thus their re-victimization is perpetuated in their search for understanding and help. Keywordsborderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

Keywords: borderline personality disorder (BPD), complex PTSD, integrative treatment of trauma, re-victimization of trauma victims.

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studies with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: Building envelope, machine learning, perforated metal, multi-factor optimization, façade.

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Authors: Shameemraj M. Nadaf, Sipra Behera, Hemant K. Rath, Garima Mishra, Raja Mukhopadhyay, Sumanta Patro

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Microservices architecture has been widely embraced for rapid, frequent, and reliable delivery of complex applications. It enables organizations to evolve their technology stack in various domains. Today, the networking domain is flooded with plethora of devices and software solutions which address different functionalities ranging from elementary operations, viz., switching, routing, firewall etc., to complex analytics and insights based intelligent services. In this paper, we attempt to bring in the microservices based approach for agile and adaptive delivery of network services for any underlying networking technology. We discuss the life cycle management of each individual microservice and a distributed control approach with emphasis for dynamic provisioning, management, and orchestration in an automated fashion which can provide seamless operations in large scale networks. We have conducted validations of the system in lab testbed comprising of Traditional/Legacy and Software Defined Wireless Local Area networks.

Keywords: Microservices architecture, software defined wireless networks, traditional wireless networks, automation, orchestration, intelligent networks, network analytics, seamless management, single pane control, fine-grain control.

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Authors: M. Watanabe, T. Yamaguchi, M. Sasajima, Y. Kurosawa, Y. Koike

Abstract:

Earphones and headphones, which are compact electro-acoustic transducers, tend to have a lot of acoustic absorption materials and porous materials known as dampers, which often have a large number of extremely small holes and narrow slits to inhibit the resonance of the vibrating system, because the air viscosity significantly affects the acoustic characteristics in such acoustic paths. In order to perform simulations using the finite element method (FEM), it is necessary to be aware of material characteristics such as the impedance and propagation constants of sound absorbing materials and porous materials. The transfer function is widely known as a measurement method for an acoustic tube with such physical properties, but literature describing the measurements at the upper limits of the audible range is yet to be found. The acoustic tube, which is a measurement instrument, must be made narrow, and the distance between the two sets of microphones must be shortened in order to take measurements of acoustic characteristics at higher frequencies. When such a tube is made narrow, however, the characteristic impedance has been observed to become lower than the impedance of air. This paper considers the cause of this phenomenon to be the effect of the air viscosity and describes an FEM analysis of an acoustic tube considering air viscosity to compare to the theoretical formula by including the effect of air viscosity in the theoretical formula for an acoustic tube.

Keywords: Acoustic tube, air viscosity, earphones, FEM, porous materials, sound absorbing materials, transfer function method.

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Authors: Abimbola M. Enitan, John O. Odiyo, Feroz M. Swalaha

Abstract:

The study of microbial ecology and their function in anaerobic digestion processes are essential to control the biological processes. This is to know the symbiotic relationship between the microorganisms that are involved in the conversion of complex organic matter in the industrial wastewater to simple molecules. In this study, diversity and quantity of bacterial community in the granular sludge taken from the different compartments of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated using polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR). The phylogenetic analysis showed three major eubacteria phyla that belong to Proteobacteria, Firmicutes and Chloroflexi in the full-scale UASB reactor, with different groups populating different compartment. The result of qPCR assay showed high amount of eubacteria with increase in concentration along the reactor’s compartment. This study extends our understanding on the diverse, topological distribution and shifts in concentration of microbial communities in the different compartments of a full-scale UASB reactor treating brewery wastewater. The colonization and the trophic interactions among these microbial populations in reducing and transforming complex organic matter within the UASB reactors were established.

Keywords: Bacteria, brewery wastewater, real-time quantitative PCR, UASB reactor.

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Authors: Saud A. Taj

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Employer branding is considered as a useful tool for addressing the global-local problem facing complex organisations that have operations scattered across the globe and face challenges of dealing with the local environment alongside. Despite being an established field of study within the Western developed world, there is little empirical evidence concerning the relevance of employer branding to global companies that operate in the under-developed economies. This paper fills this gap by gaining rich insight into the implementation of employer branding programs in a foreign multinational operating in Pakistan dealing with the global-local problem. The study is qualitative in nature and employs semistructured and focus group interviews with senior/middle managers and local frontline employees to deeply examine the phenomenon in case organisation. Findings suggest that authenticity is required in employer brands to enable them to respond to the local needs thereby leading to the resolution of the global-local problem. However, the role of signaling theory is key to the development of authentic employer brands as it stresses on the need to establish an efficient and effective signaling environment where in signals travel in both directions (from signal designers to receivers and backwards) and facilitate firms with the global-local problem. The paper also identifies future avenues of research for the employer branding field.

Keywords: Authenticity, Counter-signals, Employer Branding, Global-Local Problem, Signaling Theory.

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Authors: L. Heidari, M. Jalili Ghazizade

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In recent years, different petrochemical complexes have been established to produce aromatic compounds. Among them, Nouri Petrochemical Complex (NPC) is the largest producer of aromatic raw materials in the world, and is located in south of Iran. Environmental concerns have been raised in this region due to generation of different types of solid waste generated in the process of aromatics production, and subsequently, industrial waste characterization has been thoroughly considered. The aim of this study is qualitative and quantitative characterization of industrial waste generated in the aromatics production process and determination of the best method for industrial waste management. For this purpose, all generated industrial waste during the production process was determined using a checklist. Four main industrial wastes were identified as follows: spent industrial soil, spent catalyst, spent molecular sieves and spent N-formyl morpholine (NFM) solvent. The amount of heavy metals and organic compounds in these wastes were further measured in order to identify the nature and toxicity of such a dangerous compound. Then industrial wastes were classified based on lab analysis results as well as using different international lists of hazardous waste identification such as EPA, UNEP and Basel Convention. Finally, the best method of waste disposal is selected based on environmental, economic and technical aspects. 

Keywords: Spent industrial soil, spent molecular sieve, spent normal ¬formyl -morpholine solvent.

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Authors: J. F. Viljoen, Catherine Foxcroft

Abstract:

Expert sight readers rely on their ability to recognize patterns in scores, their inner hearing and prediction skills in order to perform complex sight reading exercises. They also have the ability to observe deviations from expected patterns in musical scores. This increases the “Eye-hand span” (reading ahead of the point of playing) in order to process the elements in the score. The study aims to investigate the gaze patterns of expert and non-expert sight readers focusing on key and time signatures. 20 musicians were tasked with playing 12 sight reading examples composed for one hand and five examples composed for two hands to be performed on a piano keyboard. These examples were composed in different keys and time signatures and included accidentals and changes of time signature to test this theory. Results showed that the experts fixate more and for longer on key and time signatures as well as deviations in examples for two hands than the non-expert group. The inverse was true for the examples for one hand, where expert sight readers showed fewer and shorter fixations on key and time signatures as well as deviations. This seems to suggest that experts focus more on the key and time signatures as well as deviations in complex scores to facilitate sight reading. The examples written for one appeared to be too easy for the expert sight readers, compromising gaze patterns.

Keywords: Cognition, eye tracking, musical notation, sight reading.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean Functions, Simplification, KarnoughMap, Implementation of Logic Functions, Modular NeuralNetworks.

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Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

Abstract:

With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: Energy-efficient buildings, Hierarchical model predictive control, Microgrid power flow optimization, Price-optimal building climate control.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean functions, simplification, Karnough map, implementation of logic functions, modular neural networks.

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Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

Abstract:

RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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