Search results for: brand machines

Authors: Petra Gergelova, Sofia Ioannidou, Davide Arcella, Alexandra Tard, Polly E. Boon, Oliver Lindtner, Christina Tlustos, Jean-Charles Leblanc

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Objectives: To assess chronic dietary exposure to food additives in different European countries and population groups. Method and Design: The European Food Safety Authority’s (EFSA) Panel on Food Additives and Nutrient Sources added to Food (ANS) estimates chronic dietary exposure to food additives with the purpose of re-evaluating food additives that were previously authorized in Europe. For this, EFSA uses concentration values (usage and/or analytical occurrence data) reported through regular public calls for data by food industry and European countries. These are combined, at individual level, with national food consumption data from the EFSA Comprehensive European Food Consumption Database including data from 33 dietary surveys from 19 European countries and considering six different population groups (infants, toddlers, children, adolescents, adults and the elderly). EFSA ANS Panel estimates dietary exposure for each individual in the EFSA Comprehensive Database by combining the occurrence levels per food group with their corresponding consumption amount per kg body weight. An individual average exposure per day is calculated, resulting in distributions of individual exposures per survey and population group. Based on these distributions, the average and 95th percentile of exposure is calculated per survey and per population group. Dietary exposure is assessed based on two different sets of data: (a) Maximum permitted levels (MPLs) of use set down in the EU legislation (defined as regulatory maximum level exposure assessment scenario) and (b) usage levels and/or analytical occurrence data (defined as refined exposure assessment scenario). The refined exposure assessment scenario is sub-divided into the brand-loyal consumer scenario and the non-brand-loyal consumer scenario. For the brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the highest reported usage/analytical level for one food group, and at the mean level for the remaining food groups. For the non-brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the mean reported usage/analytical level for all food groups. An additional exposure from sources other than direct addition of food additives (i.e. natural presence, contaminants, and carriers of food additives) is also estimated, as appropriate. Results: Since 2014, this methodology has been applied in about 30 food additive exposure assessments conducted as part of scientific opinions of the EFSA ANS Panel. For example, under the non-brand-loyal scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 5.9 and 8.7 mg/kg body weight/day, respectively. The same estimates under the brand-loyal scenario in toddlers resulted in exposures of 8.1 and 20.7 mg/kg body weight/day, respectively. For the regulatory maximum level exposure assessment scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 11.9 and 30.3 mg/kg body weight/day, respectively. Conclusions: Detailed and up-to-date information on food additive concentration values (usage and/or analytical occurrence data) and food consumption data enable the assessment of chronic dietary exposure to food additives to more realistic levels.

Keywords: α-tocopherol, ammonium phosphatides, dietary exposure assessment, European Food Safety Authority, food additives, food consumption data

Procedia PDF Downloads 291

Authors: S. Meguenni, A. Djahbar, K. Tounsi

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Electric railway traction systems are complex; they have electrical couplings, magnetic and solid mechanics. These couplings impose several constraints that complicate the modeling and analysis of these systems. An example of drive systems, which combine the advantages of the use of multiphase machines, power electronics and computing means, is mono convert isseur multi-machine system which can control a fully decoupled so many machines whose electric windings are connected in series. In this approach, our attention especially on modeling and independent control of two five phase synchronous machine with permanent magnet connected in series and fed by a matrix converter application to the rail traction (bogie of a locomotive BB 36000).

Keywords: synchronous machine, vector control Multi-machine/ Multi-inverter, matrix inverter, Railway traction

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Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

Procedia PDF Downloads 567

Authors: Chi-Ying Yu

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Fashion design is, in fact, an aesthetic inquiry of fabric, style and human body. In recent years, close cooperation between the artistic circles and the fashion world has even brought fashion into the arena of contemporary art. This study offers a case study on the avant-garde fashion designer Alexander McQueen, investigating how he and his brand translate fashion into contemporary art at various levels. Firstly, in terms of his designs themselves, McQueen demonstrates through fashions his declarations on political and gender issues, demonstrating his unique barbarian aesthetics and creating an enchanting sublimity. Secondly, McQueen extends his fashion aesthetics into a cross-disciplinary performing method, and raises catwalk shows to the level of complete artistic experience. Finally, and also most importantly, the brand has been producing fashion movies for its seasonal design series. By means of an abstract, non-narrative visual language, these films essentially transform people’s experience of clothing – from the senses to the pure visual. This is not simply a cross-media artistic practice, but much more fundamentally a discourse on contemporary perceptual experience. From the case of Alexander McQueen, it can be argued that avant-garde fashion has broken through the boundary between design and art, issuing its own art manifesto through the field of art or non-art.

Keywords: Alexander McQueen, avant-garde fashion, contemporary art, fashion film

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Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

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Authors: Sylvia Chan-Olmsted, Lisa-Charlotte Wolter

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With the continuous proliferation of media platforms, there have been tremendous changes in media consumption behaviors. From the perspective of sports sponsorship, while there is now a multitude of platforms to create brand associations, the changing media landscape and shift of message control also mean that sports sponsors will have to take into account the nature of and consumer responses toward these emerging digital media to devise effective marketing strategies. Utilizing the personal interview methodology, this study is qualitative and exploratory in nature. A total of 18 experts from European and American academics, sports marketing industry, and sports leagues/teams were interviewed to address three main research questions: 1) What are the major changes in digital technologies that are relevant to sports sponsorship; 2) How have digital media influenced the channels and platforms of sports sponsorship; and 3) How have these technologies affected the goals, strategies, and measurement of sports sponsorship. The study found that sports sponsorship has moved from consumer engagement, engagement measurement, and consequences of engagement on brand behaviors to micro-targeting one on one, engagement by context, time, and space, and activation and leveraging based on tracking and databases. From the perspective of platforms and channels, the use of mobile devices is prominent during sports content consumption. Increasing multiscreen media consumption means that sports sponsors need to optimize their investment decisions in leagues, teams, or game-related content sources, as they need to go where the fans are most engaged in. The study observed an imbalanced strategic leveraging of technology and digital infrastructure. While sports leagues have had less emphasis on brand value management via technology, sports sponsors have been much more active in utilizing technologies like mobile/LBS tools, big data/user info, real-time marketing and programmatic, and social media activation. Regardless of the new media/platforms, the study found that integration and contextualization are the two essential means of improving sports sponsorship effectiveness through technology. That is, how sponsors effectively integrate social media/mobile/second screen into their existing legacy media sponsorship plan so technology works for the experience/message instead of distracting fans. Additionally, technological advancement and attention economy amplify the importance of consumer data gathering, but sports consumer data does not mean loyalty or engagement. This study also affirms the benefit of digital media as they offer viral and pre-event activations through storytelling way before the actual event, which is critical for leveraging brand association before and after. That is, sponsors now have multiple opportunities and platforms to tell stories about their brands for longer time period. In summary, digital media facilitate fan experience, access to the brand message, multiplatform/channel presentations, storytelling, and content sharing. Nevertheless, rather than focusing on technology and media, today’s sponsors need to define what they want to focus on in terms of content themes that connect with their brands and then identify the channels/platforms. The big challenge for sponsors is to play to the venues/media’s specificity and its fit with the target audience and not uniformly deliver the same message in the same format on different platforms/channels.

Keywords: digital media, mobile media, social media, technology, sports sponsorship

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Satya Girish Goparaju

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It is said that the pyramid of Needs is not an invention by Maslow but only a graphical representation of his theory. It is also interesting to note how business management schools have adopted this interpreted theory to organizational behavior and marketing subjects. Against this background, this article attempts to raise the point that the hierarchy of needs proposed by Abraham Maslow need not necessarily be represented in a pyramid, but a linear model would be more eligible in the present times. To propose this point, this article presents needs a comparative study of ‘self-actualization’ (the apex of the pyramid) in organizational behavior and branding contexts, respectively. This article tries to shed light on the original theory proposed by Maslow, which stated that self-actualization is attained through living one’s life completely and not by satisfying individual needs. Therefore, in an organizational behavior perspective, it can be understood that self-actualization is irrelevant as an employee’s life is not the work and the satisfied needs in a workplace will only make the employee perform better. In the same way, a brand does not sell products to satisfy all needs of a consumer and does not have a role directly in attaining self-actualization. For the purpose of this study, select employees of a branding agency will participate in responding to a questionnaire to answer both as employees of an organization and also as consumers of a global smartphone brand. This study aims to deconstruct the interpretations that have been widely accepted by both organizational behavior and branding professionals.

Keywords: branding, marketing, needs, organizational behavior, psychology

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Authors: Z. Q. Zhang, Y. Zhang, D. L. Li

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To overcome the some shortcomings associated with traditional flotation machines and columns in collophanite flotation, a flotation device was designed and fabricated in the laboratory. A multi-impeller pump with same function as a mechanical cell was used instead of the injection sparger and circulation pump in column flotation unit. The influence of main operational parameters of the device like feed flow rate, air flow rate and impellers’ speed on collophanite flotation was analyzed. Experiment results indicate that the influence of the operational parameters were significant on flotation recovery and grade of phosphate concentrate. The best operating conditions of the device were: feed flow rate 0.62 L/min, air flow rate 6.67 L/min and impellers speed 900 rpm. At these conditions, a phosphate concentrate assaying about 30.5% P₂O₅ and 1% MgO with a P₂O₅ recovery of about 81% was obtained from a Yuan'an phosphate ore sample containing about 22.30% P₂O₅ and 3.2% MgO.

Keywords: collophanite flotation, flotation columns, flotation machines, multi-impeller pump

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Authors: O. Starineca

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Some organizations as employers have difficulties to attract job seekers and retain their employees. Strategic planning of Human Resources (HR) presumes broad analysis of perspectives including analysis of potential job seekers in the field. Human Resources Recruitment (HRR) influences employer brand of an organization and peculiarities of both external organizational factors and stakeholders. Defining peculiarities of the future job seekers, who could potentially become the employees of the organization, could help to adjust HRR tools and methods adapt to the youngest generation employees’ preferences and be more successful in selecting the best candidates, who are likely to be loyal to the employer. The aim of the empirical study is definition of some students’ as job seekers peculiarities and their requirements to their potential employer. The survey in Latvia, Lithuania and Spain. Respondents were students from these countries’ tertiary education institutions Public Administration (PA) or relevant study programs. All three countries students’ peculiarities have just a slight difference. Overall, they all wish to work for a socially responsible employer that is able to provide positive working environment and possibilities for professional development and learning. However, respondents from each country have own peculiarities. The study might have a practical application. PA of the examined countries might use the results developing employer brand and creating job advertisements focusing on recent graduates’ recruitment.

Keywords: generation Y, human resources recruitment, job seekers, public administration

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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With the evolution of the productive processes, demonstrated mainly by the presence every time larger of the irrigation and to crescent it disputes for water, accompanied by your shortage (distances every time larger), there is need to project facilities that can provide supply of water with larger speed and efficiency. Being like this, the presence of hydraulic pumps in an irrigation project or water supply for small communities, is of highest importance, and the knowledge of the fundamental parts to your good operation it deserves the due attention and care. Hydraulic pumps are machines of flow, whose function is to supply energy for the water, in order to press down her, through the conversion of mechanical energy of your originating from rotor a motor the combustion or of an electric motor. This way, the hydraulic pumps are had as generating hydraulic machines. The objective of this work was to project and to build a radial centrifugal pump for agricultural application in small communities.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigation

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Authors: J. BalaRaju, M. Govinda Raj, C. S. N. Murthy

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Every organization in the competitive world tends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production, and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). This is used as loading and hauling purpose in underground mines. In view of the aforementioned facts, this paper delves into identification of the key influencing factors such as LHDs maintenance effectiveness, vehicle condition, operator skill and utilization of the machines on performance of LHDs. An attempt has been made for improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). Two different approaches for evaluation of OEE have been adopted and compared under various operating conditions. The use of OEE calculation in terms of percentage availability, performance and quality and the hitherto existing situation of the underground mine production is evaluated. Necessary recommendations are suggested to mining industry on the basis of OEE.

Keywords: utilization, maintenance, availability, performance and quality

Procedia PDF Downloads 192

Authors: Galu Papy Yuma

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This paper presents a new dynamic simulation of a power system consisting of four machines equipped with the Generalized Unified Power Flow Controller (GUPFC) to improve power system stability. The dynamic simulation of the GUPFC consists of one shunt converter and two series converters based on voltage source converter, and DC link capacitor installed in the power system. MATLAB/Simulink is used to arrange the dynamic simulation of the GUPFC, where the power system is simulated in order to investigate the impact of the controller on power system oscillation damping and to show the simulation program reliability. The Improved Chaotic- Harmony Search (IC-HS) Algorithm is used to provide the parameter controller in order to lead-lag compensation design. The results obtained by simulation show that the power system with four machines is suitable for stability analysis. The use of GUPFC and IC-HS Algorithm provides the excellent capability in fast damping of power system oscillations and improve greatly the dynamic stability of the power system.

Keywords: GUPFC, IC-HS algorithm, Matlab/Simulink, damping oscillation

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Authors: Sneha Leslie

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The current situation in the cyber world is that crimes performed by Botnets are increasing and the masterminds (botmaster) are not detectable easily. The botmaster in the botnet compromises the legitimate host machines in the network and make them bots or zombies to initiate the cyber-attacks. This paper will focus on the live detection of the botmaster in the network by using the strong framework 'metasploit', when distributed denial of service (DDOS) attack is performed by the botnet. The affected victim machine will be continuously monitoring its incoming packets. Once the victim machine gets to know about the excessive count of packets from any IP, that particular IP is noted and details of the noted systems are gathered. Using the vulnerabilities present in the zombie machines (already compromised by botmaster), the victim machine will compromise them. By gaining access to the compromised systems, applications are run remotely. By analyzing the incoming packets of the zombies, the victim comes to know the address of the botmaster. This is an effective and a simple system where no specific features of communication protocol are considered.

Keywords: bonet, DDoS attack, network security, detection system, metasploit framework

Procedia PDF Downloads 224

Authors: Evans Oteng, Clement Yeboah, Alexander Otechere-Fianko

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In today’s economy, despite achievements and advances in the banking and financial institutions, there are challenges that will require intensive attempts on the portion of the banks in Ghana. The perceived decline in profitability of banks seems to have emanated from ineffective branding. Hence, the purpose of this quantitative descriptive-correlational study was to examine the effects of branding on the profitability of banks in Ghana. The researchers purposively sampled some 116 banks in Ghana. Self-developed Likert scale questionnaires were administered to the finance officers of the financial institutions. The results were found to be statistically significant, F (1, 114) = 4. 50, p = .036. This indicates that those banks in Ghana with good branding practices have strong marketing tools to identify and sell their products and services and, as such, have a big market share. The correlation coefficients indicate that branding has a positive correlation with profitability and are statistically significant (r=.207, p<0.05), which signifies that as branding increases, the return on equity’s profitability indicator improves and vice versa. Future researchers can consider other factors beyond branding, such as online banking. The study has significant implications for the success and competitive advantage of those banks that effective branding allows them to differentiate themselves from their competitors. A strong and unique brand identity can help a bank stand out in a crowded market, attract customers, and build customer loyalty. This can lead to increased market share and profitability. Branding influences customer perception and trust. A well-established and reputable brand can create a positive image in the minds of customers, enhancing their confidence in the bank's products and services. This can result in increased customer acquisition, customer retention and a positive impact on profitability. Banks with strong brands can leverage their reputation and customer trust to cross-sell additional products and services. When customers have confidence in the brand, they are more likely to explore and purchase other offerings from the same institution. Cross-selling can boost revenue streams and profitability. Successful branding can open up opportunities for brand extensions and diversification into new products or markets. Banks can leverage their trusted brand to introduce new financial products or expand their presence into related areas, such as insurance or investment services. This can lead to additional revenue streams and improved profitability. This study can have implications for education. Thus, increased profitability of banks due to effective branding can result in higher financial resources available for corporate social responsibility (CSR) activities. Banks may invest in educational initiatives, such as scholarships, grants, research projects, and sponsorships, to support the education sector in Ghana. Also, this study can have implications for logistics and supply chain management. Thus, strong branding can create trust and credibility among customers, leading to increased customer loyalty. This loyalty can positively impact the bank's relationships with its suppliers and logistics partners. It can result in better negotiation power, improved supplier relationships, and enhanced supply chain coordination, ultimately leading to more efficient and cost-effective logistics operations.

Keywords: branding, profitability, competitors, customer loyalty, customer retention, corporate social responsibility, cost-effective, logistics operations

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Authors: Aniruddha Joshi

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This paper discusses a simulation study of automated sand casting production system. Therefore, the first aims of this study is development of automated sand casting process model and analyze this model with a simulation software Witness. Production methodology aims to improve overall productivity through elimination of wastes and that leads to improve quality. Integration of automation with Simulation is beneficial to identify the obstacles in implementation and to take appropriate options to implement successfully. For this integration, there are different Simulation Software’s. To study this integration, with the help of “WITNESS” Simulation Software the model is created. This model is based on literature review. The input parameters are Setup Time, Number of machines, cycle time and output parameter is number of castings, avg, and time and percentage usage of machines. Obtained results are used for Statistical Analysis. This analysis concludes the optimal solution to get maximum output.

Keywords: automated sand casting production system, simulation, WITNESS software, performance evaluation

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Authors: Fahad Y. Al-dawish

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The current trend by a large number of organizations and individuals to use cloud computing. Many consider it a significant shift in the field of computing. Cloud computing are distributed and parallel systems consisting of a collection of interconnected physical and virtual machines. With increasing request and profit of cloud computing infrastructure, diverse computing processes can be executed on cloud environment. Many organizations and individuals around the world depend on the cloud computing environments infrastructure to carry their applications, platform, and infrastructure. One of the major and essential issues in this environment related to allocating incoming tasks to suitable virtual machine (cloud task scheduling). Cloud task scheduling is classified as optimization problem, and there are several meta-heuristic algorithms have been anticipated to solve and optimize this problem. Good task scheduler should execute its scheduling technique on altering environment and the types of incoming task set. In this research project a cloud task scheduling methodology based on ant colony optimization ACO algorithm, we call it ACO-TS Ant Colony Optimization for Task Scheduling has been proposed and compared with different scheduling algorithms (Random, First Come First Serve FCFS, and Fastest Processor to the Largest Task First FPLTF). Ant Colony Optimization (ACO) is random optimization search method that will be used for assigning incoming tasks to available virtual machines VMs. The main role of proposed algorithm is to minimizing the makespan of certain tasks set and maximizing resource utilization by balance the load among virtual machines. The proposed scheduling algorithm was evaluated by using Cloudsim toolkit framework. Finally after analyzing and evaluating the performance of experimental results we find that the proposed algorithm ACO-TS perform better than Random, FCFS, and FPLTF algorithms in each of the makespaan and resource utilization.

Keywords: cloud Task scheduling, ant colony optimization (ACO), cloudsim, cloud computing

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Authors: Chin Pang Lei

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Colonized by the UK, handed over to China, and now as a global financial city, Hong Kong’s history is never easy to write under the dominant discourses of colonialism, nationalism and globalization. In this plight, cinema, regarded as Hong Kong’s most representative cultural form, is used for writing, exploring and questioning the local history of the city. In their writing of the past, Hong Kong directors such as Wong Kar-wai, Stanley Kwan and Tsui Hark have demonstrated alternative ways of historicizing Hong Kong. Despite their interests in different periods of time (Wong is obsessed with the 1960s; Kwan is attracted to the 1930s; Tsui often goes back to the early 20th century), all these directors use genres as their time machines to revisit the past. As a popular cultural form, genres always come with a series of ideologies which define our lives and explain the society. Hence, in a changing society, genres change and complicate themselves with different packages of meanings. Genres function as open-ended and corrigible schemata which can contain multiple themes and various meanings. In Hong Kong, genres, often seen as highly commercial and overly market-oriented, are opportunities for alternative history writing and the exploration of local identities. This paper examines how these Hong Kong directors use the popular forms of genres, such as melodrama, martial art and gangster films, to present the past, and how the stories of the fictional characters, such as prostitutes, martial artists and jobless hooligans mobilize imagination of history. These texts show that genre is a crucial platform for Hong Kong’s post-colonial self-writing. Via genres, history in these films is against official and canonical history as well as grand narrative. Genres as time machines articulate a voice for Hong Kong.

Keywords: Hong Kong cinema, genre, historicizing, local history, Wong Kar-Wai

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Authors: Kefyalew Muleta, Tetemke Mehari

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Background: Human being require metallic elements such as copper and zinc up to certain limits that could cause problems if found in excess. Other metallic elements like cadmium and lead can be harmful to health if foodstuffs containing them are consumed regularly. Canned dry-milk and fish contain these metals in the journey from farm to fork. Objective: This study was designed to determine the concentration of Cd, Cu, Pb, and Zn in four brands of canned dry-milk and fish from supermarkets in Addis Ababa. Methods: Laboratory based cross-sectional study design was used to determine the concentration of the heavy metals in four different brands of canned dry-milk and fish imported from different country from February to March 2013. The foods brands were sampled by simple random sampling method from eight supermarkets in Addis Ababa and coded. Wet oxidation using HNO3 and H2O2 was used to extract the heavy metals from the foods samples and analyzed by Flame Atomic Absorption Spectroscopy. Conclusions: From this study, it can be concluded that the level of Cadmium and Copper residues in canned dry-milk significantly vary among brands; and the levels of copper residue significantly vary among brands of canned fish at 95 % level. The AM milk brand from Ethiopia was safe in cadmium level. The cadmium and lead level in the NF fish brands from Indonesia packed in vegetables oil, and the lead level in DF brand packed in brine are safe.

Keywords: AAS, canned dry milk, canned fish, Cd, Cu, Pb, Zn

Procedia PDF Downloads 391

Authors: Bin Liu

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As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Christopher Benedikt Jakob

Abstract:

In our current society, there is no need to take a look at the wristwatch to know the exact time. Smartphones, the watch in the car or the computer watch, inform us about the time too. Over hundreds of years, luxury watches have held a fascination for human beings. Consumers buy watches that cost thousands of euros, although they could buy much cheaper watches which also fulfill the function to indicate the correct time. This shows that the functional value has got a minor meaning with reference to the buying-reasons as regards luxury watches. For a few years, people have an increased demand to track data like their walking distance per day or to track their sleep for example. Smart watches enable consumers to get information about these data. There exists a trend that people intend to optimise parts of their social life, and thus they get the impression that they are able to optimise themselves as human beings. With the help of smart watches, they are able to optimise parts of their productivity and to realise their targets at the same time. These smart watches are also offered as luxury models, and the question is: how will customers of traditional luxury watches react? Therefore this study has the intention to give answers to the question why people are willing to spend an enormous amount of money on the consumption of luxury watches. The self-expression model, the relationship basis model, the functional benefit representation model and the means-end-theory are chosen as an appropriate methodology to find reasons why human beings purchase specific luxury watches and luxury smart watches. This evaluative approach further discusses these strategies concerning for example if consumers buy luxury watches/smart watches to express the current self or the ideal self and if human beings make decisions on expected results. The research critically evaluates that relationships are compared on the basis of their advantages. Luxury brands offer socio-emotional advantages like social functions of identification and that the strong brand personality of luxury watches and luxury smart watches helps customers to structure and retrieve brand awareness which simplifies the process of decision-making. One of the goals is to identify if customers know why they like specific luxury watches and dislike others although they are produced in the same country and cost comparable prices. It is very obvious that the market for luxury watches especially for luxury smart watches is changing way faster than it has been in the past. Therefore the research examines the market changing parameters in detail.

Keywords: buying-behaviour, brand management, consumer, luxury watch, smart watch

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

Abstract:

The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 583

Authors: Galal Omer, Onisimo Mutanga, Elfatih M. Abdel-Rahman, Elhadi Adam

Abstract:

Threatened tree species (TTS) play a significant role in ecosystem functioning and services, land use dynamics, and other socio-economic aspects. Such aspects include ecological, economic, livelihood, security-based, and well-being benefits. The development of techniques for mapping and monitoring TTS is thus critical for understanding the functioning of ecosystems. The advent of advanced imaging systems and supervised learning algorithms has provided an opportunity to classify TTS over fragmenting landscape. Recently, vegetation maps have been produced using advanced imaging systems such as WorldView-2 (WV-2) and robust classification algorithms such as support vectors machines (SVM) and artificial neural network (ANN). However, delineation of TTS in a fragmenting landscape using high resolution imagery has widely remained elusive due to the complexity of the species structure and their distribution. Therefore, the objective of the current study was to examine the utility of the advanced WV-2 data for mapping TTS in the fragmenting Dukuduku indigenous forest of South Africa using SVM and ANN classification algorithms. The results showed the robustness of the two machine learning algorithms with an overall accuracy (OA) of 77.00% (total disagreement = 23.00%) for SVM and 75.00% (total disagreement = 25.00%) for ANN using all eight bands of WV-2 (8B). This study concludes that SVM and ANN classification algorithms with WV-2 8B have the potential to classify TTS in the Dukuduku indigenous forest. This study offers relatively accurate information that is important for forest managers to make informed decisions regarding management and conservation protocols of TTS.

Keywords: artificial neural network, threatened tree species, indigenous forest, support vector machines

Procedia PDF Downloads 488

Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

Abstract:

This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: capacitated MRP, tabu search, simulated annealing, variable neighborhood search, linear programming, assembly flow shop, application in industry

Procedia PDF Downloads 212

Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

Abstract:

In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

Procedia PDF Downloads 141

Authors: Liaqat Ali, Khalid Farooq, Shafieullah Khan, Nasir Orakzai, Qudratullah

Abstract:

Objectives: To determine the risk factors for high resistance of ciprofloxacin in complicated urinary tract infections. Materials and Methods: It is an analytical study that was conducted in the department of Urology (Team ‘C’) at Institute of Kidney Diseases Hayatabad Peshawar from 1st June 2012 till 31st December 2012. Total numbers of 100 patients with complicated UTI was selected in the study. Multivariate analysis and linear regression were performed for the detection of risk factors. All the data was recorded on structured Proforma and was analyzed on SPSS version 17. Results: The mean age of the patient was 55.6 years (Range 3-82 years). 62 patients were male while 38 patients were female. 66 isolates of E-Coli were found sensitive to ciprofloxacin while 34 isolates were found Resistant for ciprofloxacin. Using multivariate analysis and linear regression, an increasing age above 50 (p=0.002) History of urinary catheterization especially for bladder outflow obstruction (p=0.001) and previous multiple use of ciprofloxacin (p=0.001) and poor brand of ciprofloxacin were found to be independent risk factors for high resistance of ciprofloxacin. Conclusion: UTI is common illness across the globe with increasing trend of antimicrobial resistance for ciprofloxacin against E Coli in complicated UTI. The risk factors for emerging resistance are increasing age, urinary catheterization and multiple use and poor brand of ciprofloxacin.

Keywords: urinary tract infection, ciprofloxacin, urethral catheterization, antimicrobial resistance

Procedia PDF Downloads 302