Search results for: target product profile

Authors: Shoumodip Roy, Ankit Singhania, K. R. K. Rao, Ravi Shankar, M. K. Agarwal, R. V. Ramna, Uttam Singh

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The productivity of a blast furnace and the quality of the hot metal produced are significantly dependent on the smoothness and stability of furnace operation. The permeability of the furnace bed, as well as the gas flow pattern, influences the steady control of process parameters. The softening – melting zone that is formed inside the furnace contributes largely in distribution of the gas flow and the bed permeability. A better shape of softening-melting zone enhances the performance of blast furnace, thereby reducing the fuel rates and improving furnace life. Therefore, predictive model of the softening- melting zone profile can be utilized to control and improve the furnace operation. The shape of softening-melting zone depends upon the physical and chemical properties of the agglomerates and iron ore charged in the furnace. The variations in the agglomerate proportion in the burden at G Blast furnace disturbed the furnace stability. During such circumstances, it was analyzed that a w-shape softening-melting zone profile was formed inside the furnace. The formation of w-shape zone resulted in poor bed permeability and non-uniform gas flow. There was a significant increase in the heat loss at the lower zone of the furnace. The fuel demand increased, and the huge production loss was incurred. Therefore, visibility of softening-melting zone profile was necessary in order to pro-actively optimize the process parameters and thereby to operate the furnace smoothly. Using stave temperatures, a model was developed that predicted the shape of the softening-melting zone inside the furnace. It was observed that furnace operated smoothly during inverse V-shape of the zone and vice-versa during w-shape. This model helped to control the heat loss, optimize the burden distribution and lower the fuel rate at G Blast Furnace, TSL Jamshedpur. As a result of furnace stabilization productivity increased by 10% and fuel rate reduced by 80 kg/thm. Details of the process have been discussed in this paper.

Keywords: agglomerate, blast furnace, permeability, softening-melting

Procedia PDF Downloads 247

Authors: Archana Thangavelu, Han-Ik Park, Young-Chul Park, Joon-Hong Park

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In this numerical study, we have proposed a method for evaluation of backward extrusion process of pressure vessel made up of steel. Demand for lighter and stiffer products have been increasing in the last years especially in automobile engineering. Through detailed finite element analysis, effective stress, strain and velocity profile have been obtained with optimal range. The process design of a forward and backward extrusion axe-symmetric part has been studied. Forging is mainly carried out because forged products are highly reliable and possess superior mechanical properties when compared to normal products. Performing computational simulations of 3D hot forging with various dimensions of billet and optimization of weight is carried out using Taguchi Orthogonal Array (OA) Optimization technique. The technique used in this study can be used for newly developed materials to investigate its forgeability for much complicated shapes in closed hot die forging process.

Keywords: backward extrusion, hot forging, optimization, finite element analysis, Taguchi method

Procedia PDF Downloads 302

Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Michael N. O'Sullivan, Con Sheahan

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Researchers have spent decades developing tools and techniques to aid teams in the new product development (NPD) process. Despite this, it is evident that there is a huge gap between their academic prevalence and their industry adoption. For the fuzzy front-end, in particular, there is a wide range of tools to choose from, including the Kano Model, the House of Quality, and many others. In fact, there are so many tools that it can often be difficult for teams to know which ones to use and how they interact with one another. Moreover, while the benefits of using these tools are obvious to industrialists, they are rarely used as they carry a learning curve that is too steep and they become too complex to manage over time. In essence, it is commonly believed that they are simply not worth the effort required to learn and use them. This research explores a streamlined process for the fuzzy front-end, assembling the most effective tools and making them accessible to everyone. The process was developed iteratively over the course of 3 years, following over 80 final year NPD teams from engineering, design, technology, and construction as they carried a product from concept through to production specification. Questionnaires, focus groups, and observations were used to understand the usability issues with the tools involved, and a human-centred design approach was adopted to produce a solution to these issues. The solution takes the form of physical toolkit, similar to a board game, which allows the team to play through an example of a new product development in order to understand the process and the tools, before using it for their own product development efforts. A complimentary website is used to enhance the physical toolkit, and it provides more examples of the tools being used, as well as deeper discussions on each of the topics, allowing teams to adapt the process to their skills, preferences and product type. Teams found the solution very useful and intuitive and experienced significantly less confusion and mistakes with the process than teams who did not use it. Those with a design background found it especially useful for the engineering principles like Quality Function Deployment, while those with an engineering or technology background found it especially useful for design and customer requirements acquisition principles, like Voice of the Customer. Products developed using the toolkit are added to the website as more examples of how it can be used, creating a loop which helps future teams understand how the toolkit can be adapted to their project, whether it be a small consumer product or a large B2B service. The toolkit unlocks the potential of these beneficial tools to those in industry, both for large, experienced teams and for inexperienced start-ups. It allows users to assess the market potential of their product concept faster and more effectively, arriving at the product design stage with technical requirements prioritized according to their customers’ needs and wants.

Keywords: new product development, fuzzy front-end, usability, Kano model, quality function deployment, voice of customer

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Authors: Shasline Gedeon, Tiffany W. Ardley, Ying Wang, Nathan J. Gesmundo, Katarina A. Sarris, Ana L. Aguirre

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Drug discovery and delivery involve drug targeting, an approach that helps find a drug against a chosen target through high throughput screening and other methods by way of identifying the physical properties of the potential lead compound. Physical properties of potential drug candidates have been an imperative focus since the unveiling of Lipinski's Rule of 5 for oral drugs. Throughout a compound's journey from discovery, clinical phase trials, then becoming a classified drug on the market, the desirable properties are optimized while minimizing/eliminating toxicity and undesirable properties. In the pharmaceutical industry, the ability to generate molecules in parallel with maximum efficiency is a substantial factor achieved through sp²-sp² carbon coupling reactions, e.g., Suzuki Coupling reactions. These reaction types allow for the increase of aromatic fragments onto a compound. More recent literature has found benefits to decreasing aromaticity, calling for more sp³-sp² carbon coupling reactions instead. The objective of this project is to provide a comparison between various sp³-sp² carbon coupling methods and reaction conditions, collecting data on production of the desired product. There were four different coupling methods being tested amongst three cores and 4-5 installation groups per method; each method ran under three distinct reaction conditions. The tested methods include the Photoredox Decarboxylative Coupling, the Photoredox Potassium Alkyl Trifluoroborate (BF3K) Coupling, the Photoredox Cross-Electrophile (PCE) Coupling, and the Weix Cross-Electrophile (WCE) Coupling. The results concluded that the Decarboxylative method was very difficult in yielding product despite the several literature conditions chosen. The BF3K and PCE methods produced competitive results. Amongst the two Cross-Electrophile coupling methods, the Photoredox method surpassed the Weix method on numerous accounts. The results will be used to build future libraries.

Keywords: drug discovery, high throughput chemistry, photoredox chemistry, sp³-sp² carbon coupling methods

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Authors: Yinwei Lin, Cha'o-Kuang Chen

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In this article, the Laplace Adomian transform method (LADM) and double decomposition method (DDM) are used to solve the annular hyperbolic profile fins with variable thermal conductivity. As the thermal conductivity parameter ε is relatively large, the numerical solution using DDM become incorrect. Moreover, when the terms of DDM are more than seven, the numerical solution using DDM is very complicated. However, the present method can be easily calculated as terms are over seven and has more precisely numerical solutions. As the thermal conductivity parameter ε is relatively large, LADM also has better accuracy than DDM.

Keywords: fins, thermal conductivity, Laplace transform, Adomian, nonlinear

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Authors: Elsheikh Asser

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Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multi-objective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: genetic algorithms, time-cost trade-off, multi-objective model, project scheduling

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Authors: Z. Y. Jiang, H. B. Tibar, A. Aljabri

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Optimisation of the physical and mechanical properties of cold rolled thin strips is achieved by controlling the rolling parameters. In this paper, the factors affecting the asymmetrical cold rolling of thin low carbon steel strip have been studied at a speed ratio of 1.1 without lubricant applied. The effect of rolling parameters on the resulting microstructure was also investigated. It was found that under dry condition, work roll shifting and work roll cross angle can improve the strip profile, and the result is more significant with an increase of work roll cross angle rather than that of work roll shifting. However, there was no obvious change in microstructure. In addition, effects of rolling parameters on strip profile and microstructure have also been discussed.

Keywords: rolling speed ratio, microstructure, work roll cross angle, work roll shifting

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Authors: Rupamoni Thakur, Madhusmita Dehingia, Narayan C. Talukdar, Mojibur R. Khan

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The human gut is an extremely active fermentation site and is inhabited by diverse bacterial species. Consumption of alcoholic beverages has been shown to substantially modulate the human gut bacterial profile (GBP) of an individual. Assam, a major north-eastern state of India, is home to a number of tribal populations of which the tea-tribes form a major community. These tea-tribal communities are known to prepare and consume a locally-prepared alcoholic beverage from fermented jaggery, whose chemical composition is unknown. In this study, we demonstrate the effect of daily intake of the locally-prepared alcoholic beverage on the GBP of the tea-tribal communities and correlate it with the changes in the biochemical biomarkers of the population. The fecal bacterial diversity of 40 drinkers and 35 non-drinking healthy individuals were analyzed by polymerase chain reaction (PCR)–denaturing gradient gel electrophoresis (DGGE). The results suggested that the GBP was significantly modulated in the fermented-beverage consuming subjects. Significant difference was also observed in the serum biochemical parameters such as triglyceride, total cholesterol and the liver marker enzymes (ASAT/ALAT and GGT). Further studies to identify the GBP of drinkers vs non-drinkers through Next-generation Sequencing (NGS) analysis and to correlate the changes with the biochemical biomarkers of the population is underway.

Keywords: alcoholic beverage, gut bacterial profile, PCR-DGGE analysis, tea-tribes of India

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Authors: Esra Zengin, Sinan Akkar

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Reliable and accurate prediction of nonlinear structural response requires specification of appropriate earthquake ground motions to be used in nonlinear time history analysis. The current research has mainly focused on selection and manipulation of real earthquake records that can be seen as the most critical step in the performance based seismic design and assessment of the structures. Utilizing amplitude scaled ground motions that matches with the target spectra is commonly used technique for the estimation of nonlinear structural response. Representative ground motion ensembles are selected to match target spectrum such as scenario-based spectrum derived from ground motion prediction equations, Uniform Hazard Spectrum (UHS), Conditional Mean Spectrum (CMS) or Conditional Spectrum (CS). Different sets of criteria exist among those developed methodologies to select and scale ground motions with the objective of obtaining robust estimation of the structural performance. This study presents ground motion selection and scaling procedure that considers the spectral variability at target demand with the level of ground motion dispersion. The proposed methodology provides a set of ground motions whose response spectra match target median and corresponding variance within a specified period interval. The efficient and simple algorithm is used to assemble the ground motion sets. The scaling stage is based on the minimization of the error between scaled median and the target spectra where the dispersion of the earthquake shaking is preserved along the period interval. The impact of the spectral variability on nonlinear response distribution is investigated at the level of inelastic single degree of freedom systems. In order to see the effect of different selection and scaling methodologies on fragility curve estimations, results are compared with those obtained by CMS-based scaling methodology. The variability in fragility curves due to the consideration of dispersion in ground motion selection process is also examined.

Keywords: ground motion selection, scaling, uncertainty, fragility curve

Procedia PDF Downloads 581

Authors: Chayaporn Kaensar

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Recently, Job Recommender Systems have gained much attention in industries since they solve the problem of information overload on the recruiting website. Therefore, we proposed Extended Personalized Job System that has the capability of providing the appropriate jobs for job seeker and recommending some suitable information for them using Data Mining Techniques and Dynamic User Profile. On the other hands, company can also interact to the system for publishing and updating job information. This system have emerged and supported various platforms such as web application and android mobile application. In this paper, User profiles, Implicit User Action, User Feedback, and Clustering Techniques in WEKA libraries have gained attention and implemented for this application. In additions, open source tools like Yii Web Application Framework, Bootstrap Front End Framework and Android Mobile Technology were also applied.

Keywords: recommendation, user profile, data mining, web and mobile technology

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Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

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Authors: Archana Surendran, Kalpana C. A.

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Vitamin D insufficiency is highly prevalent in women. Vitamin D bioavailability could be reduced in obesity due to increased sequestration by white adipose tissue. Increased sun exposure due to more frequent outdoor physical activity as well as a diet rich in vitamin D could be the common cause of both higher levels of 25(OH)D and a more favorable lipid profile. The study was conducted with the aim to assess the obesity status among selected working women in Coimbatore, determine their lifestyle and physical activity pattern, study their dietary intake, estimate the vitamin D and lipid profile of selected women and associate the relationship between Vitamin D and obesity among the selected women. A total of 100 working women (non pregnant, non lactating) working in IT sector, hotels and teaching staff were selected for the study. Anthropometric measurements and dietary recall were conducted for all. The women were further categorized as obese and non-obese based on their BMI. Fifteen obese and 15 non-obese women were selected and their fasting blood glucose level, serum Vitamin D and lipid profile were measured. Association between serum vitamin D, lipid profile, anthropometric measurements, food intake and sun exposure was correlated. Fifty six percent of women in the age group between 25-39 years and 44 percent of women in the age group between 40-45 years were obese. Waist and hip circumference of women in the age group between 40-45 years (89.7 and 107.4 cm) were higher than that of obese women in the age group between 25-39 years (88.6 and 102.8 cm). There were no women with sufficient vitamin D levels. In the age group between 40-45 years (obese women), serum Vitamin D was inversely proportional to waist-hip ratio and LDL cholesterol. There was an inverse relationship between body fat percentage and Total cholesterol with serum vitamin D among the women of the age group between 25-39 years. Consumption of milk and milk products were low among women. Intake of calcium was deficit among the women in both the age groups and showed a negative correlation. Sun exposure was less for all the women. Findings from the study revealed that obese women with a higher consumption of fat and less intake of calcium-rich foods have low serum Vitamin D levels than the non-obese women. Thus, it can be concluded that there is an association between Vitamin D status and obesity among adult women.

Keywords: obesity, sun exposure, vitamin D, women

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Authors: Anjushi Verma, Tirthankar Gayen

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Although, reliability is an important attribute of quality, especially for mission critical systems, yet, there does not exist any versatile model even today for the reliability assessment of component-based software. The existing Black Box models are found to make various assumptions which may not always be realistic and may be quite contrary to the actual behaviour of software. They focus on observing the manner in which the system behaves without considering the structure of the system, the components composing the system, their interconnections, dependencies, usage frequencies, etc.As a result, the entropy (uncertainty) in assessment using these models is much high.Though, there are some models based on operation profile yet sometimes it becomes extremely difficult to obtain the exact operation profile concerned with a given operation. This paper discusses the drawbacks, deficiencies and limitations of Black Box approaches from the perspective of various authors and finally proposes a conceptual model for the reliability assessment of software.

Keywords: black box, faults, failure, software reliability

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Authors: Imran Muhammad

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The main cause of infectious disease in the modern world is Mycobacterium Tuberculosis (MT). To combat tuberculosis, new and efficient drugs are an urgent need in the modern world. Schif bases are potent for their biological pharmacophore activity. Thus we selected different Vanillin-based Schiff bases for their binding activity against target enzymes of Mycobacterium tuberculosis that is (DprE1 (decaprenyl phosphoryl-β-D-ribose 2′-epimerase), and DNA gyrase subunit-A), using molecular docking. We evaluate the inhibition potential, interaction, and binding mode of these compounds with the target enzymes.

Keywords: schiff bases, tuberculosis, DNA gyrase, DprE1, docking

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Authors: Yousif Mohamed Y. Abdallah, Khalid H. Eltom

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This is an experimental study deals with measurement of the periodic physiological organ motion during lung external irradiation in order to reduce the exposure of healthy tissue during radiation treatments. The results showed for left lung displacement reading (4.52+1.99 mm) and right lung is (8.21+3.77 mm) which the radiotherapy physician should take suitable countermeasures in case of significant errors. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, the calculation of tumour mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a high resolution CT scan with a margin of 3-5 mm is appropriate.

Keywords: physiological motion, lung, external irradiation, radiation medicine

Procedia PDF Downloads 414

Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu

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In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.

Keywords: space-based detection, aerial targets, detectability analysis, scene environment

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Authors: Regita P. Permata, Ulfa S. Nuraini

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Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

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Authors: Berri A. Wells

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The purpose of this study is to explore the different variables that influence women, specifically Black American or African American women to target and bully other Black American women in the workplace. The Pink Elephant Study seeks to answer the research question, what are some of the factors that prompt Black women to target and harass other Black women in the workplace or other professional settings and organizations? The goal of the study is to enhance the workplace bullying body of knowledge in two specific ways beginning with the inclusion of Black women in the conversation of workplace bullying. A second goal is to hear from and learn from perpetrators of workplace bullying.

Keywords: workplace bullying, incivility at work, women at work, overcoming conflict

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya

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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.

Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation

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Authors: Maziyar Nouraee

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Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

Procedia PDF Downloads 390

Authors: Ankush Agrawal, Nadia Bhuiyan

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The new product development (NPD) literature emphasizes the importance of introducing new products on the market for continuing business success. New products are responsible for employment, economic growth, technological progress, and high standards of living. Therefore, the study of NPD and the processes through which they emerge is important. The goal of our research is to propose a framework of critical success factors, metrics, and tools and techniques for implementing metrics for each stage of the new product development (NPD) process. An extensive literature review was undertaken to investigate decades of studies on NPD success and how it can be achieved. These studies were scanned for common factors for firms that enjoyed success of new products on the market. The paper summarizes NPD success factors, suggests metrics that should be used to measure these factors, and proposes tools and techniques to make use of these metrics. This was done for each stage of the NPD process, and brought together in a framework that the authors propose should be followed for complex NPD projects. While many studies have been conducted on critical success factors for NPD, these studies tend to be fragmented and focus on one or a few phases of the NPD process.

Keywords: new product development, performance, critical success factors, framework

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Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

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This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

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Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

Procedia PDF Downloads 485

Authors: O. Ikpotokin

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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

Procedia PDF Downloads 343

Authors: Wegene Demisie Jima

Abstract:

Leather is a durable and flexible material used for various purposes including clothing, footwear, upholstery and gloves. However, the use of leather for smart product applications is a challenge since it is electrically insulating material. Here, we report a simple method to produce conducting glove leathers using an in-situ polymerization of pyrrole. The concentrations of pyrrole, ferric chloride and anthraquinone-2-sulfonic acid sodium salt monohydrate were optimized to produce maximum conductivity in the treated leathers. The coating of polypyrrole in the treated leathers was probed using FT-IR, X-ray diffraction and electron microscopic analysis. FTIR confirms that the formation of polypyrrole on the leather surface as well as presence of prominent N-C stretching band. X-ray diffraction analysis suggests para-crystallinity in the PPy-treated leathers.We further demonstrate that the treated leathers, with maximum conductivity of 7.4 S/cm, can be used for making conductive gloves for operating touch-screen devices apart from other smart product applications.

Keywords: electrical conductivity, in-situ polymerization, pyrrole, smart product

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Authors: Yafri Hazbi, Zaenal Bachruddin, Nafiatul Umami, Lies Mira Yusiati

Abstract:

The objective of this study was to identify the benefits of total mixture concentrate based on tofu waste silage (TMC-TWS) as ration containing lactic acid bacteria on performance of lambs. Fifteen weaning lambs (2-3 months old) were randomly divided into two treatment groups, treatment group I (TI) was fed with TMC-TWS as ration and treatment group II (TII) was fed with TMC-TWS fresh (without silage fermentation). The performance of lambs was evaluated on day 0, 15, and 30 to have data of body weight per day. Meanwhile, blood sampling and feces were made on the 30th day to get an analysis on the blood profile (erythrocytes (mill/ml), hemoglobin (g/dL), packed cell volume (%), and leukocytes (mill/ml)) and the number of worm eggs in feces. The results of this study showed no significant difference between the effect of different feed on the blood profile (erythrocytes (mill/ml), hemoglobin (g/dL), packed cell volume (%), as well as the number of worm eggs in the feces. However the results showed significant differences if it is low (P<0.05) due to the treatment group based on sex on body weight gain per day, feed conversion rate and the number of erythrocytes.

Keywords: lambs, total mixture concentrate, silage, acid lactid bacteria, blood profile, eggs worm in feces

Procedia PDF Downloads 173

Authors: Farrukh Jamil, Ala'a H. Al-Muhtaseb, Lamya Al-Haj, Mohab A. Al-Hinai

Abstract:

Date pits are major agricultural waste produced in Oman. Current work was conducted to produce jet fuel and green diesel from hydrodeoxygenation of Date pits oil in the presence of Pd/C catalyst. The hydrodeoxygenation of Date pits oil occurred to be highly efficient at following mild operating conditions such as conditions temperature 300°C pressure 10bar with continuous stirring at 500rpm. Detailed product characterization revealed that large fraction of paraffinic hydrocarbons was found which accounts up to 91.1 % which attributed due to efficient hydrodeoxygenation. Based on the type of components in product oil, it was calculated that the maximum fraction of hydrocarbons formed lies within the range of green diesel 72.0 % then jet fuel 30.4% by using Pd/C catalysts. The densities of product oil were 0.88 kg/m³, the viscosity of products calculated was 3.49 mm²/s. Calorific values for products obtained were 44.11 MJ/kg when Pd/C catalyst was used for hydrodeoxygenation. Based on products analysis it can conclude that Date pits oil could successfully utilize for synthesizing green diesel and jet fuel fraction.

Keywords: biomass, jet fuel, green diesel, catalyst

Procedia PDF Downloads 290

Authors: Maged El-Sayed Mohamed

Abstract:

Plant tissue culture practices are presented nowadays as the most promising substitute to a whole plant in the terms of secondary metabolites production. They offer the advantages of high production, tunability and they have less effect on plant ecosystems. Lantana camara is a weed, which is common all over the world as an ornamental plant. Weeds can adapt to any type of soil and climate due to their rich cellular machinery for secondary metabolites’ production. This characteristic is found in Lantana camara as a plant of very rich diversity of secondary metabolites with no dominant class of compounds. Aim: This trait has encouraged the author to develop tissue culture experiments for Lantana camara to be a platform for production and manipulation of secondary metabolites through biotransformation. Methodology: The plant was collected in its flowering stage in September 2014, from which explants were prepared from shoot tip, auxiliary bud and leaf. Different types of culture media were tried as well as four phytohormones and their combinations; NAA, 2,4-D, BAP and kinetin. Explants were grown in dark or in 12 hours dark and light cycles at 25°C. A metabolic profile for the produced callus was made and then compared to the whole plant profile. The metabolic profile was made using GC-MS for volatile constituents (extracted by n-hexane) and by HPLC-MS and capillary electrophoresis-mass spectrometry (CE-MS) for non-volatile constituents (extracted by ethanol and water). Results: The best conditions for the callus induction was achieved using MS media supplied with 30 gm sucrose and NAA/BAP (1:0.2 mg/L). Initiation of callus was favoured by incubation in dark for 20 day. The callus produced under these conditions showed yellow colour, which changed to brownish after 30 days. The rate of callus growth was high, expressed in the callus diameter, which reached to 1.15±0.2 cm in 30 days; however, the induction of callus delayed for 15 days. The metabolic profile for both volatile and non-volatile constituents of callus showed more simple background metabolites than the whole plant with two new (unresolved) peaks in the callus’ nonvolatile constituents’ chromatogram. Conclusion: Lantana camara callus production can be itself a source of new secondary metabolites and could be used for biotransformation studies due to its simple metabolic background, which allow easy identification of newly formed metabolites. The callus production gathered the simple metabolic background with the rich cellular secondary metabolite machinery of the plant, which could be elicited to produce valuable medicinally active products.

Keywords: capillary electrophoresis-mass spectrometry, gas chromatography, metabolic profile, plant tissue culture

Procedia PDF Downloads 381