Search results for: hybrid cement

Authors: F. F. Howard, I. Yakubu, C. B. Boye, J. S. Y. Kuma

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Natural and human activities, such as mining operations, expose the natural soil to adverse environmental conditions, leading to contamination of soil, groundwater, and surface water, which has negative effects on humans, flora, and fauna. Bare or partly exposed soil is most liable to fluvial erosion. This paper enumerates various methods used to identify, map, and model fluvial erosion in a mining environment. Classical, Artificial Intelligence (AI), and GIS methods have been reviewed. One of the many classical methods used to estimate river erosion is the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE model is easy to use. Its reliance on empirical relationships that may not always be applicable to specific circumstances or locations is a flaw. Other classical models for estimating fluvial erosion are the Soil and Water Assessment Tool (SWAT) and the Universal Soil Loss Equation (USLE). These models offer a more complete understanding of the underlying physical processes and encompass a wider range of situations. Although more difficult to utilise, they depend on the availability and dependability of input data for correctness. AI can help deal with multivariate and complex difficulties and predict soil loss with higher accuracy than traditional methods, and also be used to build unique models for identifying degraded areas. AI techniques have become popular as an alternative predictor for degraded environments. However, this research proposed a hybrid of classical, AI, and GIS methods for efficient and effective modelling of fluvial erosion.

Keywords: Fluvial erosion, classical methods, Artificial Intelligence, Geographic Information System.

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Authors: A. Abbas Khalaf, L. Issazadeh, Z. Arif Abdullah, J. Hassanpour

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In order to evaluate the growth and yield properties of two Sorghum-Sudangrass hybrids under different irrigation levels, an investigation was done in the experiment site of Collage of Agriculture, University of Duhok, Kurdistan region of Iraq (36°5´38^⸗ N, 42°52´02^⸗ E) in the years 2015-16. The experiment was conducted under Randomized Complete Block Design (RCBD) with three replications, which main factor was irrigation treatments (I₁₀₀, I₇₅ and I₅₀) according to evaporation pan class A and type of Sorghum-Sudangrass hybrids (KH12SU9001, G₁) and (KH12SU9002, G₂) were factors of subplots. The parameters studied were: plant height (cm), number of green leaves per plant; leaf area (m²/m²), stem thickness (mm), percent of protein, fresh and dry biomass (ton.ha^-1) and also crop water productivity. The results of variance analysis showed that KH12SU9001 variety had more amount of leaf area, percent of protein, fresh and dry biomass yield in comparison to KH12SU9002 variety. By comparing effects of irrigation levels on vegetative growth and yield properties, results showed that amount of plant height, fresh and dry biomass weight was decreased by decreasing irrigation level from full irrigation regime to 5 _o% of irrigation level. Also, results of crop water productivity (CWP) indicated that improvement in quantity of irrigation would impact fresh and dry biomass yield significantly. Full irrigation regime was recorded the highest level of CWP (1.28-1.29 kg.m^-3).

Keywords: Deficit irrigation, growth, Sorghum-Sudangrass hybrid, yield.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the elearning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery.

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Authors: C. Alexandridou, G. N. Angelopoulos, F. A. Coutelieris

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Construction industry in Greece consumes annually more than 25 million tons of natural aggregates originating mainly from quarries. At the same time, more than 2 million tons of construction and demolition waste are deposited every year, usually without control, therefore increasing the environmental impact of this sector. A potential alternative for saving natural resources and minimize landfilling, could be the recycling and re-use of Concrete and Demolition Waste (CDW) in concrete production. Moreover, in order to conform to the European legislation, Greece is obliged to recycle non-hazardous construction and demolition waste to a minimum of 70% by 2020. In this paper characterization of recycled materials - commercially and laboratory produced, coarse and fine, Recycled Concrete Aggregates (RCA) - has been performed. Namely, X-Ray Fluorescence and X-ray diffraction (XRD) analysis were used for chemical and mineralogical analysis respectively. Physical properties such as particle density, water absorption, sand equivalent and resistance to fragmentation were also determined. This study, first time made in Greece, aims at outlining the differences between RCA and natural aggregates and evaluating their possible influence in concrete performance. Results indicate that RCA’s chemical composition is enriched in Si, Al, and alkali oxides compared to natural aggregates. X-ray diffraction (XRD) analyses results indicated the presence of calcite, quartz and minor peaks of mica and feldspars. From all the evaluated physical properties of coarse RCA, only water absorption and resistance to fragmentation seem to have a direct influence on the properties of concrete. Low Sand Equivalent and significantly high water absorption values indicate that fine fractions of RCA cannot be used for concrete production unless further processed. Chemical properties of RCA in terms of water soluble ions are similar to those of natural aggregates. Four different concrete mixtures were produced and examined, replacing natural coarse aggregates with RCA by a ratio of 0%, 25%, 50% and 75% respectively. Results indicate that concrete mixtures containing recycled concrete aggregates have a minor deterioration of their properties (3-9% lower compression strength at 28 days) compared to conventional concrete containing the same cement quantity.

Keywords: Chemical and physical characterization, compressive strength, mineralogical analysis, recycled concrete aggregates, waste management.

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.

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Authors: Khaled Elbehiery, Hussam Elbehiery

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The success of education is dependent on evolution and adaptation, while the traditional system has worked before, one type of education evolved with the digital age is virtual education that has influenced efficiency in today’s learning environments. Virtual learning has indeed proved its efficiency to overcome the drawbacks of the physical environment such as time, facilities, location, etc., but despite what it had accomplished, the educational system over all is not adequate for being a productive system yet. Earning a degree is not anymore enough to obtain a career job; it is simply missing the skills and creativity. There are always two sides of a coin; a college degree or a specialized certificate, each has its own merits, but having both can put you on a successful IT career path. For many of job-seeking individuals across world to have a clear meaningful goal for work and education and positively contribute the community, a productive correlation and cooperation among employers, universities alongside with the individual technical skills is a must for generations to come. Fortunately, the proposed research “Entrepreneur Universal Education System” is an evolution to meet the needs of both employers and students, in addition to gaining vital and real-world experience in the chosen fields is easier than ever. The new vision is to empower the education to improve organizations’ needs which means improving the world as its primary goal, adopting universal skills of effective thinking, effective action, effective relationships, preparing the students through real-world accomplishment and encouraging them to better serve their organization and their communities faster and more efficiently.

Keywords: Virtual education, academic degree, certificates, internship, amazon web services, Microsoft Azure, Google cloud platform, hybrid models.

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Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

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Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: Additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability.

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Authors: P. Luangpaiboon, P. Aungkulanon

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This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.

Keywords: Aggregate Production Planning, Desirability Function Approach, Improved Harmony Search Algorithm, Hunting Search Algorithm and Firefly Algorithm.

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Authors: Tharwat N. Hijjawi

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Learning oral skills in an Arabic speaking environment is challenging. A blended course (material, activities, and individual/ group work tasks …) was implemented in a module of level B1 for undergraduate students of French as a foreign language in order to increase their opportunities to practice listening and speaking skills. This research investigates the influence of this modality on enhancing active learning and examines the effectiveness of provided strategies. Moreover, it aims at discovering how it allows teacher to flip the traditional classroom and create a learner-centered framework. Which approaches were integrated to motivate students and urge them to search, analyze, criticize, create and accomplish projects? What was the perception of students? This paper is based on the qualitative findings of a questionnaire and a focus group interview with learners. Despite the doubled time and effort both “teacher” and “student” needed, results revealed that the NTIC allowed a shift into a learning paradigm where learners were the “chiefs” of the process. Tasks and collaborative projects required higher intellectual capacities from them. Learners appreciated this experience and developed new life-long learning competencies at many levels: social, affective, ethical and cognitive. To conclude, they defined themselves as motivated young researchers, motivators and critical thinkers.

Keywords: Active learning, critical thinking, inverted classroom, learning paradigm, problem-based.

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Authors: J. Prakash, K. Rajesh

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In this paper, we introduce a new method for elliptical object identification. The proposed method adopts a hybrid scheme which consists of Eigen values of covariance matrices, Circular Hough transform and Bresenham-s raster scan algorithms. In this approach we use the fact that the large Eigen values and small Eigen values of covariance matrices are associated with the major and minor axial lengths of the ellipse. The centre location of the ellipse can be identified using circular Hough transform (CHT). Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of circumference pixels is identified using raster scan algorithm which uses the geometrical symmetry property. This method does not require the evaluation of tangents or curvature of edge contours, which are generally very sensitive to noise working conditions. The proposed method has the advantages of small storage, high speed and accuracy in identifying the feature. The new method has been tested on both synthetic and real images. Several experiments have been conducted on various images with considerable background noise to reveal the efficacy and robustness. Experimental results about the accuracy of the proposed method, comparisons with Hough transform and its variants and other tangential based methods are reported.

Keywords: Circular Hough transform, covariance matrix, Eigen values, ellipse detection, raster scan algorithm.

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems do not scale well on cluster containing multiple Central Processing Units (multi-CPUs cluster) or cluster containing multiple Graphics Processing Units (multi-GPUs cluster). For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration, instead of two for standard CG (Conjugate Gradient). The standard and pipelined CG methods need the vector entries generated by current GPU and other GPUs for matrix-vector product. So the communication between GPUs becomes a major performance bottleneck on miltiGPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: Conjugate Gradient, GPU, parallel programming, pipelined algorithm.

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: Data mining, ensemble, radial basis function, support vector machine, accuracy.

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: Distributed energy resources, network energy system, optimization, microgeneration system.

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Authors: A. Udayakumar, M. Rizvan Basha, M. Stalin, V.V Bhanu Prasad

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Three dimensional non-Interlaced carbon fibre reinforced silicon carbide (3-D-Cf/SiC) composites with pyrocarbon interphase were fabricated using isothermal chemical vapor infiltration (ICVI) combined with polymer impregnation pyrolysis (PIP) process. Polysilazane (PSZ) is used as a preceramic polymer to obtain silicon carbide matrix. Thermo gravimetric analysis (TGA), Infrared spectroscopic analysis (IR) and X-ray diffraction (XRD) analysis were carried out on PSZ pyrolysed at different temperatures to understand the pyrolysis and obtaining the optimum pyrolysing condition to yield β-SiC phase. The density of the composites was 1.94 g cm-3 after the 3-D carbon preform was SiC infiltrated for 280 h with one intermediate polysilazane pre-ceramic PIP process. Mechanical properties of the composite materials were investigated under tensile, flexural, shear and impact loading. The values of tensile strength were 200 MPa at room temperature (RT) and 195 MPa at 500°C in air. The average RT flexural strength was 243 MPa. The lower flexural strength of these composites is because of the porosity. The fracture toughness obtained from single edge notched beam (SENB) technique was 39 MPa.m1/2. The work of fracture obtained from the load-displacement curve of SENB test was 22.8 kJ.m-2. The composites exhibited excellent impact resistance and the dynamic fracture toughness of 44.8 kJ.m-2 is achieved as determined from instrumented Charpy impact test. The shear strength of the composite was 93 MPa, which is significantly higher compared 2-D Cf/SiC composites. Microstructure evaluation of fracture surfaces revealed the signatures of fracture processes and showed good support for the higher toughness obtained.

Keywords: 3-D-Cf/SiC, charpy impact test, composites, dynamic fracture toughness, polysilazane, pyrocarbon, Interphase.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: P. C. Boisteanu, M. G. Usturoi, Roxana Lazar, B. V. Avarvarei

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The paper is included within the framework of a complex research program, which was initiated from the hypothesis arguing on the existence of a correlation between pineal indolic and peptide hormones and the somatic development rhythm, including thus the epithalamium-epiphysis complex involvement. At birds, pineal gland contains a circadian oscillator, playing a main role in the temporal organization of the cerebral functions. The secretion of pineal indolic hormones is characterized by a high endogenous rhythmic alternation, modulated by the light/darkness (L/D) succession and by temperature as well. The research has been carried out using 100 chicken broilers - “Ross" commercial hybrid, randomly allocated in two experimental batches: Lc batch, reared under a 12L/12D lighting schedule and Lexp batch, which was photic pinealectomised through continuous exposition to light (150 lux, 24 hours, 56 days). Chemical and physical features of the meat issued from breast fillet and thighs muscles have been studied, determining the dry matter, proteins, fat, collagen, salt content and pH value, as well. Besides the variations of meat chemical composition in relation with lighting schedule, other parameters have been studied: live weight dynamics, feed intake and somatic development degree. The achieved results became significant since chickens have 7 days of age, some variations of the studied parameters being registered, revealing that the pineal gland physiologic activity, in relation with the lighting schedule, could be interpreted through the monitoring of the somatic development technological parameters, usually studied within the chicken broilers rearing aviculture practice.

Keywords: lighting schedule, physic-chemical characteristics ofmeat, pineal gland at birds.

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries.

In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530.

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Authors: J. Szolomicki, H. Golasz-Szolomicka

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The architectural and structural analysis of selected high-rise buildings in Tokyo is presented in this paper. The capital of Japan is the most densely populated city in the world and moreover is located in one of the most active seismic zones. The combination of these factors has resulted in the creation of sophisticated designs and innovative engineering solutions, especially in the field of design and construction of high-rise buildings. The foreign architectural studios (as, for Jean Nouvel, Kohn Pedesen Associates, Skidmore, Owings & Merill) which specialize in the designing of skyscrapers, played a major role in the development of technological ideas and architectural forms for such extraordinary engineering structures. Among the projects completed by them, there are examples of high-rise buildings that set precedents for future development. An essential aspect which influences the design of high-rise buildings is the necessity to take into consideration their dynamic reaction to earthquakes and counteracting wind vortices. The need to control motions of these buildings, induced by the force coming from earthquakes and wind, led to the development of various methods and devices for dissipating energy which occur during such phenomena. Currently, Japan is a global leader in seismic technologies which safeguard seismic influence on high-rise structures. Due to these achievements the most modern skyscrapers in Tokyo are able to withstand earthquakes with a magnitude of over seven degrees at the Richter scale. Damping devices applied are of a passive, which do not require additional power supply or active one which suppresses the reaction with the input of extra energy. In recent years also hybrid dampers were used, with an additional active element to improve the efficiency of passive damping.

Keywords: Core structure, damping systems, high-rise buildings.

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two hybrid price prediction models using artificial neural network and long short-term memory (ANN-LSTM), by Python, that can forecast the average monthly copper prices, traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022 and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices, and economic indicators of the three major exporting countries of copper depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation, and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-month prediction model is better than the 1-month prediction model; but still, both models can act as predicting tools for diverse economic situations.

Keywords: Copper prices, prediction model, neural network, time series forecasting.

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Authors: Kazunori Nomura, Hiromichi Ogi, Masaumi Nakahara, Sou Watanabe, Atsuhiro Shibata

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Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.

Keywords: Chemical Processing Facility, medium- and long-term management plan of JAEA Facilities, STRAD project, treatment of radioactive waste.

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Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

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In the modern manufacturing systems, the use of thermal cutting techniques using oxyfuel, plasma and laser have become indispensable for the shape forming of high quality complex components; however, the conventional chip removal production techniques still have its widespread space in the manufacturing industry. Both these types of machining operations require the positioning of end effector tool at the edge where the cutting process commences. This repositioning of the cutting tool in every machining operation is repeated several times and is termed as non-productive time or airtime motion. Minimization of this non-productive machining time plays an important role in mass production with high speed machining. As, the tool moves from one region to the other by rapid movement and visits a meticulous region once in the whole operation, hence the non-productive time can be minimized by synchronizing the tool movements. In this work, this problem is being formulated as a general travelling salesman problem (TSP) and a genetic algorithm approach has been applied to solve the same. For improving the efficiency of the algorithm, the GA has been hybridized with a noble special heuristic and simulating annealing (SA). In the present work a novel heuristic in the combination of GA has been developed for synchronization of toolpath movements during repositioning of the tool. A comparative analysis of new Meta heuristic techniques with simple genetic algorithm has been performed. The proposed metaheuristic approach shows better performance than simple genetic algorithm for minimization of nonproductive toolpath length. Also, the results obtained with the help of hybrid simulated annealing genetic algorithm (HSAGA) are also found better than the results using simple genetic algorithm only.

Keywords: Non-productive time, Airtime, 2.5 D milling, Laser cutting, Metaheuristic, Genetic Algorithm, Simulated Annealing.

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Authors: Sami W. Tabsh

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The strength of reinforced concrete depends on the member dimensions and material properties. The properties of concrete and steel materials are not constant but random variables. The variability of concrete strength is due to batching errors, variations in mixing, cement quality uncertainties, differences in the degree of compaction and disparity in curing. Similarly, the variability of steel strength is attributed to the manufacturing process, rolling conditions, characteristics of base material, uncertainties in chemical composition, and the microstructure-property relationships. To account for such uncertainties, codes of practice for reinforced concrete design impose resistance factors to ensure structural reliability over the useful life of the structure. In this investigation, the effects of reductions in concrete and reinforcing steel strengths from the nominal values, beyond those accounted for in the structural design codes, on the structural reliability are assessed. The considered limit states are flexure, shear and axial compression based on the ACI 318-11 structural concrete building code. Structural safety is measured in terms of a reliability index. Probabilistic resistance and load models are compiled from the available literature. The study showed that there is a wide variation in the reliability index for reinforced concrete members designed for flexure, shear or axial compression, especially when the live-to-dead load ratio is low. Furthermore, variations in concrete strength have minor effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and sever effect on the reliability of columns in axial compression. On the other hand, changes in steel yield strength have great effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and mild effect on the reliability of columns in axial compression. Based on the outcome, it can be concluded that the reliability of beams is sensitive to changes in the yield strength of the steel reinforcement, whereas the reliability of columns is sensitive to variations in the concrete strength. Since the embedded target reliability in structural design codes results in lower structural safety in beams than in columns, large reductions in material strengths compromise the structural safety of beams much more than they affect columns.

Keywords: Code, flexure, limit states, random variables, reinforced concrete, reliability, reliability index, shear, structural safety.

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Authors: Timothy E. Frank, Peter J. Amaddio, Elizabeth D. Decko, Alexis M. Tri, Darcy A. Farrell, Cole M. Landes

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Ultra-high performance concrete (UHPC) is a class of cementitious composites with a relatively large percentage of cement generating high compressive strength. Additionally, UHPC contains disbursed fibers, which control crack width, carry the tensile load across narrow cracks, and limit spalling. These characteristics lend themselves to a wide range of structural applications when UHPC members are reinforced with longitudinal steel. Efficient use of fibers and longitudinal steel is required to keep lifecycle cost competitive in reinforced UHPC members; this requires full utilization of both the compressive and tensile qualities of the reinforced cementitious composite. The objective of this study is to investigate the shear response of steel-reinforced UHPC beams to guide design decisions that keep initial costs reasonable, limit serviceability crack widths, and ensure a ductile structural response and failure path. Five small-scale, reinforced UHPC beams were experimentally tested. Longitudinal steel, transverse steel, and casting direction were varied. Results indicate that an increase in transverse steel in short-spanned reinforced UHPC beams provided additional shear capacity and increased the peak load achieved. Beams with very large longitudinal steel reinforcement ratios did not achieve yield and fully utilized the tension properties of the longitudinal steel. Casting the UHPC beams from the end or from the middle affected load-carrying capacity and ductility, but image analysis determined that the fiber orientation was not significantly different. It is believed that the presence of transverse and longitudinal steel reinforcement minimized the effect of different UHPC casting directions. Results support recent recommendations in the literature suggesting that a 1% fiber volume fraction is sufficient within UHPC to prevent spalling and provide compressive fracture toughness under extreme loading conditions.

Keywords: Fiber orientation, reinforced ultra-high performance concrete beams, shear, transverse steel.

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Authors: Dulal Acharjee, Punyaban Patel

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For collecting data from all sensor nodes, some changes in Dynamic Source Routing (DSR) protocol is proposed. At each hop level, route-ranking technique is used for distributing packets to different selected routes dynamically. For calculating rank of a route, different parameters like: delay, residual energy and probability of packet loss are used. A hybrid topology of DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path Routing) is formed, where braided topology is used in different faulty zones of network. For reducing energy consumption, variant transmission ranges is used instead of fixed transmission range. For reducing number of packet drop, a fuzzy logic inference scheme is used to insert different types of delays dynamically. A rule based system infers membership function strength which is used to calculate the final delay amount to be inserted into each of the node at different clusters. In braided path, a proposed 'Dual Line ACK Link'scheme is proposed for sending ACK signal from a damaged node or link to a parent node to ensure that any error in link or any node-failure message may not be lost anyway. This paper tries to design the theoretical aspects of a model which may be applied for collecting data from any large hanging iron structure with the help of wireless sensor network. But analyzing these data is the subject of material science and civil structural construction technology, that part is out of scope of this paper.

Keywords: Metallic corrosion, Multi Path Routing, DisjointMPR, Meshed MPR, braided path, dual line ACK link, route rankingand Fuzzy Logic.

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: Aerodynamics, flight control, computational fluid dynamics, flapping-wing flight.

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Authors: Hammad T. Janjuhah, Josep Sanjuan, Mohamed K. Salah

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Biological and chemical activities in carbonates are responsible for the complexity of the pore system. Primary porosity is generally of natural origin while secondary porosity is subject to chemical reactivity through diagenetic processes. To understand the integrated part of hydrocarbon exploration, it is necessary to understand the carbonate pore system. However, the current porosity classification scheme is limited to adequately predict the petrophysical properties of different reservoirs having various origins and depositional environments. Rock classification provides a descriptive method for explaining the lithofacies but makes no significant contribution to the application of porosity and permeability (poro-perm) correlation. The Central Luconia carbonate system (Malaysia) represents a good example of pore complexity (in terms of nature and origin) mainly related to diagenetic processes which have altered the original reservoir. For quantitative analysis, 32 high-resolution images of each thin section were taken using transmitted light microscopy. The quantification of grains, matrix, cement, and macroporosity (pore types) was achieved using a petrographic analysis of thin sections and FESEM images. The point counting technique was used to estimate the amount of macroporosity from thin section, which was then subtracted from the total porosity to derive the microporosity. The quantitative observation of thin sections revealed that the mouldic porosity (macroporosity) is the dominant porosity type present, whereas the microporosity seems to correspond to a sum of 40 to 50% of the total porosity. It has been proven that these Miocene carbonates contain a significant amount of microporosity, which significantly complicates the estimation and production of hydrocarbons. Neglecting its impact can increase uncertainty about estimating hydrocarbon reserves. Due to the diversity of geological parameters, the application of existing porosity classifications does not allow a better understanding of the poro-perm relationship. However, the classification can be improved by including the pore types and pore structures where they can be divided into macro- and microporosity. Such studies of microporosity identification/classification represent now a major concern in limestone reservoirs around the world.

Keywords: Carbonate reservoirs, microporosity, overview of porosity classification, reservoir characterization.

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Authors: Reihaneh Montazeri Shatouri, Rosmini Omar, Kunio Igusa

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Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.

Keywords: Automotive Industry, Green Technology, Innovation, Strategic Human Resource Management

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Authors: Wei-Hsin Sun, Jr-Ming Miao, Chang-Hsien Tai, Chien-Chun Hung

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The development of biomimetic micro-aerial-vehicles (MAVs) with flapping wings is the future trend in military/domestic field. The successful flight of MAVs is strongly related to the understanding of unsteady aerodynamic performance of low Reynolds number airfoils under dynamic flapping motion. This study explored the effects of flapping frequency, stroke amplitude, and the inclined angle of stroke plane on lift force and thrust force of a bio-inspiration corrugated airfoil with 33 full factorial design of experiment and ANOVA analysis. Unsteady vorticity flows over a corrugated thin airfoil executing flapping motion are computed with time-dependent two-dimensional laminar incompressible Reynolds-averaged Navier-Stokes equations with the conformal hybrid mesh. The tested freestream Reynolds number based on the chord length of airfoil as characteristic length is fixed of 103. The dynamic mesh technique is applied to model the flapping motion of a corrugated airfoil. Instant vorticity contours over a complete flapping cycle clearly reveals the flow mechanisms for lift force generation are dynamic stall, rotational circulation, and wake capture. The thrust force is produced as the leading edge vortex shedding from the trailing edge of airfoil to form a reverse von Karman vortex. Results also indicated that the inclined angle is the most significant factor on both the lift force and thrust force. There are strong interactions between tested factors which mean an optimization study on parameters should be conducted in further runs.

Keywords: biomimetic, MAVs, aerodynamic, ANOVA analysis.

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Authors: Suguru Ochiai, Toru Yabuki, Yoshiki Yamaguchi, Yuetsu Kodama

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In this paper, we propose a Connect6 solver which adopts a hybrid approach based on a tree-search algorithm and image processing techniques. The solver must deal with the complicated computation and provide high performance in order to make real-time decisions. The proposed approach enables the solver to be implemented on a single Spartan-6 XC6SLX45 FPGA produced by XILINX without using any external devices. The compact implementation is achieved through image processing techniques to optimize a tree-search algorithm of the Connect6 game. The tree search is widely used in computer games and the optimal search brings the best move in every turn of a computer game. Thus, many tree-search algorithms such as Minimax algorithm and artificial intelligence approaches have been widely proposed in this field. However, there is one fundamental problem in this area; the computation time increases rapidly in response to the growth of the game tree. It means the larger the game tree is, the bigger the circuit size is because of their highly parallel computation characteristics. Here, this paper aims to reduce the size of a Connect6 game tree using image processing techniques and its position symmetric property. The proposed solver is composed of four computational modules: a two-dimensional checkmate strategy checker, a template matching module, a skilful-line predictor, and a next-move selector. These modules work well together in selecting next moves from some candidates and the total amount of their circuits is small. The details of the hardware design for an FPGA implementation are described and the performance of this design is also shown in this paper.

Keywords: Connect6, pattern matching, game-tree reduction, hardware direct computation

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Authors: Berna Istegun, Erkan Celebi

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The main objective of this experimental study is to assess the shear strength and the crack behavior of the triplets built of perforated brickwork masonry elements. In order to observe the influence of shear resistance and energy dissipating before and after retrofitting applications by using the reinforcing system, static-cyclic shear tests were employed in the structural mechanics laboratory of Sakarya University. The reinforcing system is composed of hybrid multiaxial seismic fabric consisting of alkali resistant glass and polypropylene fibers. The plaster as bonding material used in the specimen’s retrofitting consists of expanded glass granular. In order to acquire exact measuring data about the failure behavior of the two mortar joints under shear stressing, vertical load-controlled cylinder having force capacity of 50 kN and loading rate of 1.5 mm/min. with an internal inductive displacement transducers is carried out perpendicular to the triplet specimens. In this study, a total of six triplet specimens with textile reinforcement were prepared for these shear bond tests. The three of them were produced as single-sided reinforced triplets with seismic fabric, while the others were strengthened on both sides. In addition, three triplet specimens without retrofitting and plaster were also tested as reference samples. The obtained test results were given in the manner of force-displacement relationships, ductility coefficients and shear strength parameters comparatively. It is concluded that two-side seismic textile applications on masonry elements with relevant plaster have considerably increased the sheer force resistance and the ductility capacity.

Keywords: Triplet shears tests, retrofitting, seismic fabric, perforated brickwork, expanded glass granular.

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