Search results for: size driven MPB
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7278

Search results for: size driven MPB

6768 Porous Titanium Scaffolds Fabricated by Metal Injection Moulding Using Potassium-Chloride and Space Holder

Authors: Ali Dehghan Manshadi, David H. StJohn, Matthew S. Dargusch, M. Qian

Abstract:

Biocompatible, highly porous titanium scaffolds were manufactured by metal injection moulding of spherical titanium powder (powder size: -45 µm) with potassium chloride (powder size: -250 µm) as a space holder. Property evaluation of scaffolds confirmed a high level of compatibility between their mechanical properties and those of human cortical bone. The optimum sintering temperature was found to be 1250°C producing scaffolds with more than 90% interconnected pores in the size range of 200-250 µm, yield stress of 220 MPa and Young’s modulus of 7.80 GPa, all of which are suitable for bone tissue engineering. Increasing the sintering temperature to 1300°C increased the Young’s modulus to 22.0 GPa while reducing the temperature to 1150°C reduced the yield stress to 120 MPa due to incomplete sintering. The residual potassium chloride was determined vs. sintering temperature. A comparison was also made between the porous titanium scaffolds fabricated in this study and the additively manufactured titanium lattices of similar porosity reported in the literature.

Keywords: titanium, metal injection moulding, mechanical properties, scaffolds

Procedia PDF Downloads 206
6767 Development of Methods for Plastic Injection Mold Weight Reduction

Authors: Bita Mohajernia, R. J. Urbanic

Abstract:

Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

Procedia PDF Downloads 289
6766 Development of Basic Patternmaking Using Parametric Modelling and AutoLISP

Authors: Haziyah Hussin, Syazwan Abdul Samad, Rosnani Jusoh

Abstract:

This study is aimed towards the automisation of basic patternmaking for traditional clothes for the purpose of mass production using AutoCAD to apply AutoLISP feature under software Hazi Attire. A standard dress form (industrial form) with the size of small (S), medium (M) and large (L) size is measured using full body scanning machine. Later, the pattern for the clothes is designed parametrically based on the measured dress form. Hazi Attire program is used within the framework of AutoCAD to generate the basic pattern of front bodice, back bodice, front skirt, back skirt and sleeve block (sloper). The generation of pattern is based on the parameters inputted by user, whereby in this study, the parameters were determined based on the measured size of dress form. The finalized pattern parameter shows that the pattern fit perfectly on the dress form. Since the pattern is generated almost instantly, these proved that using the AutoLISP programming, the manufacturing lead time for the mass production of the traditional clothes can be decreased.

Keywords: apparel, AutoLISP, Malay traditional clothes, pattern ganeration

Procedia PDF Downloads 256
6765 Analysis of Organizational Factors Effect on Performing Electronic Commerce Strategy: A Case Study of the Namakin Food Industry

Authors: Seyed Hamidreza Hejazi Dehghani, Neda Khounsari

Abstract:

Quick growth of electronic commerce in developed countries means that developing nations must change in their commerce strategies fundamentally. Most organizations are aware of the impact of the Internet and e-Commerce on the future of their firm, and thus, they have to focus on organizational factors that have an effect on the deployment of an e-Commerce strategy. In this situation, it is essential to identify organizational factors such as the organizational culture, human resources, size, structure and product/service that impact an e-commerce strategy. Accordingly, this research specifies the effects of organizational factors on applying an e-commerce strategy in the Namakin food industry. The statistical population of this research is 95 managers and employees. Cochran's formula is used for determination of the sample size that is 77 of the statistical population. Also, SPSS and Smart PLS software were utilized for analyzing the collected data. The results of hypothesis testing show that organizational factors have positive and significant effects of applying an e-Commerce strategy. On the other hand, sub-hypothesizes show that effectiveness of the organizational culture and size criteria were rejected and other sub-hypothesis were accepted.

Keywords: electronic commerce, organizational factors, attitude of managers, organizational readiness

Procedia PDF Downloads 280
6764 Shear Strength Characteristics of Sand Mixed with Particulate Rubber

Authors: Firas Daghistani, Hossam Abuel Naga

Abstract:

Waste tyres is a global problem that has a negative effect on the environment, where there are approximately one billion waste tyres discarded worldwide yearly. Waste tyres are discarded in stockpiles, where they provide harm to the environment in many ways. Finding applications to these materials can help in reducing this global problem. One of these applications is recycling these waste materials and using them in geotechnical engineering. Recycled waste tyre particulates can be mixed with sand to form a lightweight material with varying shear strength characteristics. Contradicting results were found in the literature on the inclusion of particulate rubber to sand, where some experiments found that the inclusion of particulate rubber can increase the shear strength of the mixture, while other experiments stated that the addition of particulate rubber decreases the shear strength of the mixture. This research further investigates the inclusion of particulate rubber to sand and whether it can increase or decrease the shear strength characteristics of the mixture. For the experiment, a series of direct shear tests were performed on a poorly graded sand with a mean particle size of 0.32 mm mixed with recycled poorly graded particulate rubber with a mean particle size of 0.51 mm. The shear tests were performedon four normal stresses 30, 55, 105, 200 kPa at a shear rate of 1 mm/minute. Different percentages ofparticulate rubber content were used in the mixture i.e., 10%, 20%, 30% and 50% of sand dry weight at three density states, namely loose, slight dense, and dense state. The size ratio of the mixture,which is the mean particle size of the particulate rubber divided by the mean particle size of the sand, was 1.59. The results identified multiple parameters that can influence the shear strength of the mixture. The parameters were: normal stress, particulate rubber content, mixture gradation, mixture size ratio, and the mixture’s density. The inclusion of particulate rubber tosand showed a decrease to the internal friction angle and an increase to the apparent cohesion. Overall, the inclusion of particulate rubber did not have a significant influenceon the shear strength of the mixture. For all the dense states at the low normal stresses 33 and 55 kPa, the inclusion of particulate rubber showed aslight increase in the shear strength where the peak was at 20% rubber content of the sand’s dry weight. On the other hand, at the high normal stresses 105, and 200 kPa, there was a slight decrease in the shear strength.

Keywords: shear strength, direct shear, sand-rubber mixture, waste material, granular material

Procedia PDF Downloads 132
6763 Big Data in Telecom Industry: Effective Predictive Techniques on Call Detail Records

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 139
6762 Coulomb-Explosion Driven Proton Focusing in an Arched CH Target

Authors: W. Q. Wang, Y. Yin, D. B. Zou, T. P. Yu, J. M. Ouyang, F. Q. Shao

Abstract:

High-energy-density state, i.e., matter and radiation at energy densities in excess of 10^11 J/m^3, is related to material, nuclear physics, astrophysics, and geophysics. Laser-driven particle beams are better suited to heat the matter as a trigger due to their unique properties of ultrashort duration and low emittance. Compared to X-ray and electron sources, it is easier to generate uniformly heated large-volume material for the proton and ion beams because of highly localized energy deposition. With the construction of state-of-art high power laser facilities, creating of extremely conditions of high-temperature and high-density in laboratories becomes possible. It has been demonstrated that on a picosecond time scale the solid density material can be isochorically heated to over 20 eV by the ultrafast proton beam generated from spherically shaped targets. For the above-mentioned technique, the proton energy density plays a crucial role in the formation of warm dense matter states. Recently, several methods have devoted to realize the focusing of the accelerated protons, involving externally exerted static-fields or specially designed targets interacting with a single or multi-pile laser pulses. In previous works, two co-propagating or opposite direction laser pulses are employed to strike a submicron plasma-shell. However, ultra-high pulse intensities, accurately temporal synchronization and undesirable transverse instabilities for a long time are still intractable for currently experimental implementations. A mechanism of the focusing of laser-driven proton beams from two-ion-species arched targets is investigated by multi-dimensional particle-in-cell simulations. When an intense linearly-polarized laser pulse impinges on the thin arched target, all electrons are completely evacuated, leading to a Coulomb-explosive electric-field mostly originated from the heavier carbon ions. The lighter protons in the moving reference frame by the ionic sound speed will be accelerated and effectively focused because of this radially isotropic field. At a 2.42×10^21 W/cm^2 laser intensity, a ballistic proton bunch with its energy-density as high as 2.15×10^17 J/m^3 is produced, and the highest proton energy and the focusing position agree well with that from the theory.

Keywords: Coulomb explosion, focusing, high-energy-density, ion acceleration

Procedia PDF Downloads 344
6761 Investigating the Effect of Different Design Factors on the Required Length of the Ambient Air Vaporizer

Authors: F. S. Alavi

Abstract:

In this study, MATLAB engineering software was used in order to model an industrial Ambient Air Vaporizer (AAV), considering combined convection and conduction heat transfers from the fins and the tube. The developed theoretical model was then used to investigate the effects of various design factors such as gas flow rate, ambient air temperature, fin thickness and etc. on total vaporizer ‘s length required. Cryogenic liquid nitrogen was selected as an input fluid, in all cases. According to the results, increasing the inlet fluid flow rate has direct linear effect on the total required length of vaporizer. Vaporizer’s required length decreases by increasing the size of fin radius or size of fin thickness. The dependency of vaporizer’s length on fin thickness’ size reduces at higher values of thickness and gradually converge to zero. For low flow rates, internal convection heat transfer coefficient depends directly on gas flow rate but it becomes constant, independent on flow rate after a specific value. As the ambient air temperature increases, the external heat transfer coefficient also increases and the total required length of vaporizer decreases.

Keywords: heat exchanger, modeling, heat transfer, design

Procedia PDF Downloads 115
6760 Success Factors for Innovations in SME Networks

Authors: J. Gochermann

Abstract:

Due to complex markets and products, and increasing need to innovate, cooperation between small and medium size enterprises arose during the last decades, which are not prior driven by process optimization or sales enhancement. Especially small and medium sized enterprises (SME) collaborate increasingly in innovation and knowledge networks to enhance their knowledge and innovation potential, and to find strategic partners for product and market development. These networks are characterized by dual objectives, the superordinate goal of the total network, and the specific objectives of the network members, which can cause target conflicts. Moreover, most SMEs do not have structured innovation processes and they are not accustomed to collaborate in complex innovation projects in an open network structure. On the other hand, SMEs have suitable characteristics for promising networking. They are flexible and spontaneous, they have flat hierarchies, and the acting people are not anonymous. These characteristics indeed distinguish them from bigger concerns. Investigation of German SME networks have been done to identify success factors for SME innovation networks. The fundamental network principles, donation-return and confidence, could be confirmed and identified as basic success factors. Further factors are voluntariness, adequate number of network members, quality of communication, neutrality and competence of the network management, as well as reliability and obligingness of the network services. Innovation and knowledge networks with an appreciable number of members from science and technology institutions need also active sense-making to bring different disciplines into successful collaboration. It has also been investigated, whether and how the involvement in an innovation network impacts the innovation structure and culture inside the member companies. The degree of reaction grows with time and intensity of commitment.

Keywords: innovation and knowledge networks, SME, success factors, innovation structure and culture

Procedia PDF Downloads 283
6759 Research on Innovation Service based on Science and Technology Resources in Beijing-Tianjin-Hebei

Authors: Runlian Miao, Wei Xie, Hong Zhang

Abstract:

In China, Beijing-Tianjin-Hebei is regarded as a strategically important region because itenjoys highest development in economic development, opening up, innovative capacity and andpopulation. Integrated development of Beijing-Tianjin-Hebei region is increasingly emphasized by the government recently years. In 2014, it has ascended to one of the national great development strategies by Chinese central government. In 2015, Coordinated Development Planning Compendium for Beijing-Tianjin-Hebei Region was approved. Such decisions signify Beijing-Tianjin-Hebei region would lead innovation-driven economic development in China. As an essential factor to achieve national innovation-driven development and significant part of regional industry chain, the optimization of science and technology resources allocation will exert great influence to regional economic transformation and upgrading and innovation-driven development. However, unbalanced distribution, poor sharing of resources and existence of information isolated islands have contributed to different interior innovation capability, vitality and efficiency, which impeded innovation and growth of the whole region. Under such a background, to integrate and vitalize regional science and technology resources and then establish high-end, fast-responding and precise innovation service system basing on regional resources, would be of great significance for integrated development of Beijing-Tianjin-Hebei region and even handling of unbalanced and insufficient development problem in China. This research uses the method of literature review and field investigation and applies related theories prevailing home and abroad, centering service path of science and technology resources for innovation. Based on the status quo and problems of regional development of Beijing-Tianjin-Hebei, theoretically, the author proposed to combine regional economics and new economic geography to explore solution to problem of low resource allocation efficiency. Further, the author puts forward to applying digital map into resource management and building a platform for information co-building and sharing. At last, the author presents the thought to establish a specific service mode of ‘science and technology plus digital map plus intelligence research plus platform service’ and suggestion on co-building and sharing mechanism of 3 (Beijing, Tianjin and Hebei ) plus 11 (important cities in Hebei Province).

Keywords: Beijing-Tianjin-Hebei, science and technology resources, innovation service, digital platform

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6758 Design of a Rectifier with Enhanced Efficiency and a High-gain Antenna for Integrated and Compact-size Rectenna Circuit

Authors: Rawaa Maher, Ahmed Allam, Haruichi Kanaya, Adel B. Abdelrahman

Abstract:

In this paper, a compact, high-efficiency integrated rectenna is presented to operate in the 2.45 GHz band. A comparison between two rectifier topologies is performed to verify the benefits of removing the matching network from the rectifier. A rectifier high conversion efficiency of 74.1% is achieved. To complete the rectenna system, a novel omnidirectional antenna with high gain (3.72 dB) and compact size (25 mm * 29 mm) is designed and fabricated. The same antenna is used with a reflector for raising the gain to nearly 8.3 dB. The simulation and measurement results of the antenna are in good agreement.

Keywords: internet of things, integrated rectenna, rectenna, RF energy harvesting, wireless sensor networks(WSN)

Procedia PDF Downloads 182
6757 Preparation of Nano-Sized Samarium-Doped Yttrium Aluminum Garnet

Authors: M. Tabatabaee, N. Binavayan, M. R. Nateghi

Abstract:

In this research nano-size of yttrium aluminum garnet (YAG) containing lanthanide metals was synthesized by the sol-gel method in presente citric acid as a complexing agent. Samarium (III) was used to synthesis of YAG:M3+. The prepared powders were characterized by powder X-ray diffraction (PXRD). The size distribution and morphology of the samples were analyzed by scanning electron microscopy (SEM). XRD results show that Sm, La, and ce doped YAG crystallizes in the cubic system and additional peaks compared to pure YAG can be assigned to the presence of Sm in the synthesize YAG. The SEM images show possess spherical nano-sized particle with average 50 nm in diameter.

Keywords: citric acid, nano particle, samarium, yttrium aluminum garnet

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6756 Synthesis of Nano Iron Copper Core-Shell by Using K-M Reactor

Authors: Mohamed Ahmed AbdelKawy, A. H. El-Shazly

Abstract:

In this study, Nano iron-copper core-shell was synthesized by using Kinetic energy micro reactor ( K-M reactor). The reaction between nano-pure iron with copper sulphate pentahydrate (CuSO4.5H2O) beside NaCMC as a stabilizer at K-M reactor gives many advantages in comparison with the traditional chemical method for production of nano iron-Copper core-shell in batch reactor. Many factors were investigated for its effect on the process performance such as initial concentrations of nano iron and copper sulphate pentahydrate solution. Different techniques were used for investigation and characterization of the produced nano iron particles such as SEM, XRD, UV-Vis, XPS, TEM and PSD. The produced Nano iron-copper core-shell particle using micro mixer showed better characteristics than those produced using batch reactor in different aspects such as homogeneity of the produced particles, particle size distribution and size, as core diameter 10nm particle size were obtained. The results showed that 10 nm core diameter were obtained using Micro mixer as compared to 80 nm core diameter in one-fourth the time required by using traditional batch reactor and high thickness of copper shell and good stability.

Keywords: nano iron, core-shell, reduction reaction, K-M reactor

Procedia PDF Downloads 309
6755 Analysis Influence Variation Frequency on Characterization of Nano-Particles in Preteatment Bioetanol Oil Palm Stem (Elaeis guineensis JACQ) Use Sonication Method with Alkaline Peroxide Activators on Improvement of Celullose

Authors: Luristya Nur Mahfut, Nada Mawarda Rilek, Ameiga Cautsarina Putri, Mujaroh Khotimah

Abstract:

The use of bioetanol from lignocellulosic material has begone to be developed. In Indonesia the most abundant lignocellulosic material is stem of palm which contain 32.22% of cellulose. Indonesia produces approximatelly 300.375.000 tons of stem of palm each year. To produce bioetanol from lignocellulosic material, the first process is pretreatment. But, until now the method of lignocellulosic pretretament is uneffective. This is related to the particle size and the method of pretreatment of less than optimal so that led to an overhaul of the lignin insufficient, consequently increased levels of cellulose was not significant resulting in low yield of bioetanol. To solve the problem, this research was implemented by using the process of pretreatment method ultasonifikasi in order to produce higher pulp with nano-sized particles that will obtain higher of yield ethanol from stem of palm. Research methods used in this research is the RAK that is composed of one factor which is the frequency ultrasonic waves with three varians, they are 30 kHz, 40 kHz, 50 kHz, and use constant variable is concentration of NaOH. The analysis conducted in this research is the influence of the frequency of the wave to increase levels of cellulose and change size on the scale of nanometers on pretreatment process by using the PSA methods (Particle Size Analyzer), and a Cheason. For the analysis of the results, data, and best treatment using ANOVA and test BNT with confidence interval 5%. The best treatment was obtained by combination X3 (frequency of sonication 50 kHz) and lignin (19,6%) cellulose (59,49%) and hemicellulose (11,8%) with particle size 385,2nm (18,8%).

Keywords: bioethanol, pretreatment, stem of palm, cellulosa

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6754 A Novel Bio-ceramic Using Hyperthermia for Bone Cancer Therapy, Ferro-substituted Silicate Calcium Materials

Authors: hassan gheisari

Abstract:

Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder, as prepared, is annealed at three different temperatures (900 ºC, 1000 ºC, and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks, and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic, which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic; magnetic materials; sol– gel, silicate calcium

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6753 Ferro-Substituted Silicate Calcium Materials, a Novel Bio-Ceramic Using Hyperthermia for Bone Cancer Therapy

Authors: Hassan Gheisari

Abstract:

Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder as prepared is annealed at three different temperatures (900 ºC, 1000 ºC and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic, magnetic materials, sol– gel, silicate calcium

Procedia PDF Downloads 308
6752 FPGA Implementation of RSA Encryption Algorithm for E-Passport Application

Authors: Khaled Shehata, Hanady Hussien, Sara Yehia

Abstract:

Securing the data stored on E-passport is a very important issue. RSA encryption algorithm is suitable for such application with low data size. In this paper the design and implementation of 1024 bit-key RSA encryption and decryption module on an FPGA is presented. The module is verified through comparing the result with that obtained from MATLAB tools. The design runs at a frequency of 36.3 MHz on Virtex-5 Xilinx FPGA. The key size is designed to be 1024-bit to achieve high security for the passport information. The whole design is achieved through VHDL design entry which makes it a portable design and can be directed to any hardware platform.

Keywords: RSA, VHDL, FPGA, modular multiplication, modular exponential

Procedia PDF Downloads 389
6751 Particle Swarm Optimization Algorithm vs. Genetic Algorithm for Image Watermarking Based Discrete Wavelet Transform

Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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6750 The Role of Contextual Factors in the Sustainability Reporting of Australian and New Zealand Companies

Authors: Ramona Zharfpeykan

Abstract:

The concept of sustainability is generally considered as a key topic in many countries, and sustainability reporting is becoming an important tool for companies to communicate their sustainability plans and performance to their stakeholders. There have been various studies on factors that may influence sustainability reporting in companies. This study examines the possible effect of some of the organisational factors on corporate sustainability reporting. The organisational factors included in this study are a company’s type (public or private), industry, and size as well as managers’ perception of the level of importance of indicators in reporting these indicators. A survey was conducted from 240 Australian and New Zealand companies in various industries. They were asked about their perception of the importance of sustainability indicators in their performance and if they report these indicators. The GRI indicators used to develop the survey. A multiple regression model was developed using reporting strategy score as dependent and type, size, industry categorisation, and managers’ perception of the level of importance of the GRI indicators as independent factors. The results show that among all the factors included in the model, size of a company and the perception of managers of the level of importance of environmental and labour practice indicators can affect the sustainability scores of these companies.

Keywords: sustainability reporting, global reporting initiative, sustainability reporting strategy, organisational features

Procedia PDF Downloads 158
6749 A Theorem Related to Sample Moments and Two Types of Moment-Based Density Estimates

Authors: Serge B. Provost

Abstract:

Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

Procedia PDF Downloads 165
6748 Factors Influencing Household Expenditure Patterns on Cereal Grains in Nasarawa State, Nigeria

Authors: E. A. Ojoko, G. B. Umbugadu

Abstract:

This study aims at describing the expenditure pattern of households on millet, maize and sorghum across income groups in Nasarawa State. A multi-stage sampling technique was used to select a sample size of 316 respondents for the study. The Almost Ideal Demand System (AIDS) model was adopted in this study. Results from the study shows that the average household size was five persons with dependency ratio of 52 %, which plays an important role on the household’s expenditure pattern by increasing the household budget share. On the average 82 % were male headed households with an average age of 49 years and 13 years of formal education. Results on expenditure share show that maize has the highest expenditure share of 38 % across the three income groups and that most of the price effects are significantly different from zero at 5 % significant level. This shows that the low price of maize increased its demand as compared to other cereals. Household size and age of household members are major factors affecting the demand for cereals in the study. This agrees with the fact that increased household population (size) will bring about increase consumption. The results on factors influencing preferences for cereal grains reveals that cooking quality and appearance (65.7 %) were the most important factors affecting the demand for maize in the study area. This study recommends that cereal crop production should be prioritized in government policies and farming activities that help to boost food security and alleviate poverty should be subsidized.

Keywords: expenditure pattern, AIDS model, budget share, price cereal grains and consumption

Procedia PDF Downloads 195
6747 Coal Preparation Plant:Technology Overview and New Adaptations

Authors: Amit Kumar Sinha

Abstract:

A coal preparation plant typically operates with multiple beneficiation circuits to process individual size fractions of coal obtained from mine so that the targeted overall plant efficiency in terms of yield and ash is achieved. Conventional coal beneficiation plant in India or overseas operates generally in two methods of processing; coarse beneficiation with treatment in dense medium cyclones or in baths and fines beneficiation with treatment in flotation cell. This paper seeks to address the proven application of intermediate circuit along with coarse and fines circuit in Jamadoba New Coal Preparation Plant of capacity 2 Mt/y to treat -0.5 mm+0.25 mm size particles in reflux classifier. Previously this size of particles was treated directly in Flotation cell which had operational and metallurgical limitations which will be discussed in brief in this paper. The paper also details test work results performed on the representative samples of TSL coal washeries to determine the top size of intermediate and fines circuit and discusses about the overlapping process of intermediate circuit and how it is process wise suitable to beneficiate misplaced particles from coarse circuit and fines circuit. This paper also compares the separation efficiency (Ep) of various intermediate circuit process equipment and tries to validate the use of reflux classifier over fine coal DMC or spirals. An overview of Modern coal preparation plant treating Indian coal especially Washery Grade IV coal with reference to Jamadoba New Coal Preparation Plant which was commissioned in 2018 with basis of selection of equipment and plant profile, application of reflux classifier in intermediate circuit and process design criteria is also outlined in this paper.

Keywords: intermediate circuit, overlapping process, reflux classifier

Procedia PDF Downloads 136
6746 Novel Microstrip MIMO Antenna for 3G/4G Applications

Authors: Sandro Samir Nasief, Hussein Hamed Ghouz, Mohamed Fathy

Abstract:

A compact ultra-wide band micro-strip MIMO antenna is introduced. The antenna consists of two elements each of size 24X24 mm2 (square millimetre) while the total MIMO size is 58X24 mm2 after the spacing between MIMO elements and adding a decouple circuit. The first one covers from 3.29 to 6.9 GHZ using digital ground and the second antenna covers from 8.76 to 13.27 GHZ using defective ground. This type of antenna is used for 3G and 4G applications. The introduction for the antenna structure and the parametric study (reflection coefficients, gain, coupling and decoupling) will be introduced.

Keywords: micro-strip antenna, MIMO, digital ground, defective ground, decouple circuit, bandwidth

Procedia PDF Downloads 365
6745 The Effect of Fuel Type on Synthesis of CeO2-MgO Nano-Powder by Combustion Method

Authors: F. Ghafoori-Najafabadi, R. Sarraf-Mamoory, N. Riahi-Noori

Abstract:

In this study, nanocrystalline CeO2-MgO powders were synthesized by combustion reactions using citric acid, ethylene glycol, and glycine as different fuels and nitrate as an oxidant. The powders obtained with different kinds of fuels are characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD). The size and morphology of the particles and the extent of agglomeration in the powders were studied using SEM analysis. It is observed that the variation of fuel has an intense influence on the particle size and morphology of the resulting powder. X-ray diffraction revealed that any combined phases were observed, and that MgO and CeO2 phases were formed, separately.

Keywords: nanoparticle, combustion synthesis, CeO2-MgO, nano-powder

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6744 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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6743 Study on Hydrophilicity of Anodic Aluminum Oxide Templates with TiO2-NTs

Authors: Yu-Wei Chang, Hsuan-Yu Ku, Jo-Shan Chiu, Shao-Fu Chang, Chien-Chon Chen

Abstract:

This paper aims to discuss the hydrophilicity about the anodic aluminum oxide (AAO) template with titania nanotubes (NTs). The AAO templates with pore size diameters of 20-250 nm were generated by anodizing 6061 aluminum alloy substrates in acid solution of sulfuric acid (H2SO4), oxalic acid (COOH)2, and phosphoric acid (H3PO4), respectively. TiO2-NTs were grown on AAO templates by the sol-gel deposition process successfully. The water contact angle on AAO/TiO2-NTs surface was lower compared to the water contact angle on AAO surface. So, the characteristic of hydrophilicity was significantly associated with the AAO pore size and what kinds of materials were immersed variables.

Keywords: AAO, nanotube, sol-gel, anodization, hydrophilicity

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6742 Non-Melanoma Skin Cancer in Ha’il Region in the Kingdom of Saudi Arabia: A Clinicopathological Study

Authors: Laila Seada, Nouf Al Gharbi, Shaimaa Dawa

Abstract:

Although skin cancers are prevalent worldwide, it is uncommon in Ha’il region in the Kingdom of Saudi Arabia, mostly non-melanoma sub-type. During a 4-year period from 2014 to 2017, out of a total of 120 cases of skin lesions, 29 non-melanoma cancers were retrieved from histopathology files obtained from King Khalid Hospital. As part of the study, all cases of skin cancer diagnosed during 2014 -2017 have been revised and the clinicopathological data recorded. The results show that Basal cell carcinoma (BCC) was the most common neoplasm (36%), followed by cutaneous lymphomas (mostly mycosis fungoides 25%), squamous cell carcinoma (SCC) (21%) and dermatofibrosarcoma protuberans (DFSP) (11%). Only one case of metastatic carcinoma was recorded. BCC nodular type was the most prevalent, with a mean age 57.6 years and mean size 2.73 cm. SCC was mostly grade 2, with mean size 1.9 cm and an older mean age of 72.3 cm. Increased size of lesion positively correlated with older age (p = 0.001). Non-melanoma skin cancer in Ha’il region is not frequently encountered. BCC is the most frequent followed by cutaneous T-cell lymphomas and SCC. The findings in this study were in accordance with other parts of, but much lower than other parts of the world.

Keywords: non melanoma skin cancer, Hail Region, histopathology, BCC

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6741 Multi-Scale Modeling of Ti-6Al-4V Mechanical Behavior: Size, Dispersion and Crystallographic Texture of Grains Effects

Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vidal, Farhad Rezai-Aria, Christine Boher

Abstract:

Ti-6Al-4V titanium alloy is one of the most widely used materials in aeronautical and aerospace industries. Because of its high specific strength, good fatigue, and corrosion resistance, this alloy is very suitable for moderate temperature applications. At room temperature, Ti-6Al-4V mechanical behavior is generally controlled by the behavior of alpha phase (beta phase percent is less than 8%). The plastic strain of this phase notably based on crystallographic slip can be hindered by various obstacles and mechanisms (crystal lattice friction, sessile dislocations, strengthening by solute atoms and grain boundaries…). The grains aspect of alpha phase (its morphology and texture) and the nature of its crystallographic lattice (which is hexagonal compact) give to plastic strain heterogeneous, discontinuous and anisotropic characteristics at the local scale. The aim of this work is to develop a multi-scale model for Ti-6Al-4V mechanical behavior using crystal plasticity approach; this multi-scale model is used then to investigate grains size, dispersion of grains size, crystallographic texture and slip systems activation effects on Ti-6Al-4V mechanical behavior under monotone quasi-static loading. Nine representative elementary volume (REV) are built for taking into account the physical elements (grains size, dispersion and crystallographic) mentioned above, then boundary conditions of tension test are applied. Finally, simulation of the mechanical behavior of Ti-6Al-4V and study of slip systems activation in alpha phase is reported. The results show that the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior of Ti-6Al-4V alloy modeled. The grains size influences also on mechanical proprieties of Ti-6Al-4V, especially on the yield stress; by decreasing of the grain size, the yield strength increases. Finally, the grains' distribution which characterizes the morphology aspect (homogeneous or heterogeneous) gives to the deformation fields distribution enough heterogeneity because the crystallographic slip is easier in large grains compared to small grains, which generates a localization of plastic deformation in certain areas and a concentration of stresses in others.

Keywords: multi-scale modeling, Ti-6Al-4V alloy, crystal plasticity, grains size, crystallographic texture

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6740 A Data-Driven Compartmental Model for Dengue Forecasting and Covariate Inference

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

Abstract:

Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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6739 Method to Find a ε-Optimal Control of Stochastic Differential Equation Driven by a Brownian Motion

Authors: Francys Souza, Alberto Ohashi, Dorival Leao

Abstract:

We present a general solution for finding the ε-optimal controls for non-Markovian stochastic systems as stochastic differential equations driven by Brownian motion, which is a problem recognized as a difficult solution. The contribution appears in the development of mathematical tools to deal with modeling and control of non-Markovian systems, whose applicability in different areas is well known. The methodology used consists to discretize the problem through a random discretization. In this way, we transform an infinite dimensional problem in a finite dimensional, thereafter we use measurable selection arguments, to find a control on an explicit form for the discretized problem. Then, we prove the control found for the discretized problem is a ε-optimal control for the original problem. Our theory provides a concrete description of a rather general class, among the principals, we can highlight financial problems such as portfolio control, hedging, super-hedging, pairs-trading and others. Therefore, our main contribution is the development of a tool to explicitly the ε-optimal control for non-Markovian stochastic systems. The pathwise analysis was made through a random discretization jointly with measurable selection arguments, has provided us with a structure to transform an infinite dimensional problem into a finite dimensional. The theory is applied to stochastic control problems based on path-dependent stochastic differential equations, where both drift and diffusion components are controlled. We are able to explicitly show optimal control with our method.

Keywords: dynamic programming equation, optimal control, stochastic control, stochastic differential equation

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