Search results for: market and product values

Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

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Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Yusuf Dawa Sidi, Abdulrahman Bulama Bizi

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The most dependable and precise source of climate data is often gauge observation. However, long-term records of gauge observations, on the other hand, are unavailable in many regions around the world. In recent years, a number of gridded climate datasets with high spatial and temporal resolutions have emerged as viable alternatives to gauge-based measurements. However, it is crucial to thoroughly evaluate their performance prior to utilising them in hydroclimatic applications. Therefore, this study aims to assess the effectiveness of NASA Prediction of Worldwide Energy Resources (NASA POWER) and Climate Research Unit (CRU) datasets in accurately estimating precipitation and temperature patterns within the dry region of Nigeria from 1990 to 2020. The study employs widely used statistical metrics and the Standardised Precipitation Index (SPI) to effectively capture the monthly variability of precipitation and temperature and inter-annual anomalies in rainfall. The findings suggest that CRU exhibited superior performance compared to NASA POWER in terms of monthly precipitation and minimum and maximum temperatures, demonstrating a high correlation and much lower error values for both RMSE and MAE. Nevertheless, NASA POWER has exhibited a moderate agreement with gauge observations in accurately replicating monthly precipitation. The analysis of the SPI reveals that the CRU product exhibits superior performance compared to NASA POWER in accurately reflecting inter-annual variations in rainfall anomalies. The findings of this study indicate that the CRU gridded product is often regarded as the most favourable gridded precipitation product.

Keywords: CRU, climate change, precipitation, SPI, temperature

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Authors: Rudi Hartono, Bambang Purwanto

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The translation quality of food and drink labels from Indonesian into English is poor because the translation is not accurate, less natural, and difficult to read. The label translation can be found in some cans packages of food and drink products produced and marketed by several companies in Indonesia. If this problem is left unchecked, it will lead to a misunderstanding on the translation results and make consumers confused. This study was conducted to analyze the translation errors on food and drink products labels and formulate the solution for the better translation quality. The research design was the evaluation research with a holistic criticism approach. The data used were words, phrases, and sentences translated from Indonesian to English language printed on food and drink product labels. The data were processed by using Interactive Model Analysis that carried out three main steps: collecting, classifying, and verifying data. Furthermore, the data were analyzed by using content analysis to view the accuracy, naturalness, and readability of translation. The results showed that the translation quality of food and drink product labels from Indonesian to English has the level of accuracy (60%), level of naturalness (50%), and level readability (60%). This fact needs a help to create an effective strategy for translating food and drink product labels later.

Keywords: translation quality, food and drink product labels, a holistic criticism approach, interactive model, content analysis

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Lucia Steenkamp, Chris V. D. Westhuyzen, Kgama Mathiba

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Ambergris, and more specifically its oxidation product (–)-ambrafuran, is a scarce, valuable, and sought-after perfumery ingredient. The material is used as a fixative agent to stabilise perfumes in formulations by reducing the evaporation rate of volatile substances. Ambergris is a metabolic product of the sperm whale (Physeter macrocephatus L.), resulting from intestinal irritation. Chemically, (–)-ambrafuran is produced from the natural product sclareol in eight synthetic steps – in the process using harsh and often toxic chemicals to do so. An overall yield of no more than 76% can be achieved in some routes, but generally, this is lower. A new 'green' route has been developed in our laboratory in which sclareol, extracted from the Clary sage plant, is converted to (–)-ambrafuran in two steps with an overall yield in excess of 80%. The first step uses a microorganism, Hyphozyma roseoniger, to bioconvert sclareol to an intermediate diol using substrate concentrations up to 50g/L. The yield varies between 90 and 67% depending on the substrate concentration used. The purity of the diol product is 95%, and the diol is used without further purification in the next step. The intermediate diol is then cyclodehydrated to the final product (–)-ambrafuran using a zeolite, which is not harmful to the environment and is readily recycled. The yield of the product is 96%, and following a single recrystallization, the purity of the product is > 99.5%. A preliminary LC-MS study of the bioconversion identified several intermediates produced in the fermentation broth under oxygen-restricted conditions. Initially, a short-lived ketone is produced in equilibrium with a more stable pyranol, a key intermediate in the process. The latter is oxidised under Norrish type I cleavage conditions to yield an acetate, which is hydrolysed either chemically or under lipase action to afford the primary fermentation product, an intermediate diol. All the intermediates identified point to the likely CYP450 action as the key enzyme(s) in the mechanism. This invention is an exceptional example of how the power of biocatalysis, combined with a mild, benign chemical step, can be deployed to replace a total chemical synthesis of a specific chiral antipode of a commercially relevant material.

Keywords: ambrafuran, biocatalysis, fragrance, microorganism

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Authors: Firsan Nova

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The average Indonesian watches 5.5 hours of TV a day. With a population of 242 million people and a Free-to-Air (FTA) TV penetration rate of 56%, that equates to 745 million hours of television watched each day. With such potential, it is no wonder that many companies are now attempting to get into the Pay TV market. Research firm Media Partner Asia has forecast in its study that the number of Indonesian pay-television subscribers will climb from 2.4 million in 2012 to 8.7 million by 2020, with penetration scaling up from 7 percent to 21 percent. Key drivers of market growth, the study says, include macro trends built around higher disposable income and a rising middle class, with leading players continuing to invest significantly in sales, distribution and content. New entrants, in the meantime, will boost overall prospects. This study aims to examine and analyze the effect of Market Attractiveness and the Core Competence on Value Creation and Competitive Advantage and its impact to Business Performance in the pay TV industry in Indonesia. The study using strategic management science approach with the census method in which all members of the population are as sample. Verification method is used to examine the relationship between variables. The unit of analysis in this research is all Indonesian Pay TV business units totaling 19 business units. The unit of observation is the director and managers of each business unit. Hypothesis testing is performed by using statistical Partial Least Square (PLS). The conclusion of the study shows that the market attractiveness affects business performance through value creation and competitive advantage. The appropriate value creation comes from the company ability to optimize its core competence and exploit market attractiveness. Value creation affects competitive advantage. The competitive advantage can be determined based on the company's ability to create value for customers and the competitive advantage has an impact on business performance.

Keywords: market attractiveness, core competence, value creation, competitive advantage, business performance

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Authors: Petra Dilling

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This study examines the market reaction to the publication of integrated reports for a sample of 316 global companies for the reporting year 2018. Applying event study methodology, we find significant cumulative average abnormal returns (CAARs) after the publication date. To ensure robust estimation resultsthe three-factor model, according to Fama and French, is used as well as a market-adjusted model, a CAPM and a Frama-French model taking GARCH effects into account. We find a significant positive CAAR after the publication day of the integrated report. Our results suggest that investors react to information provided in the integrated report and that they react differently to the annual financial report. Furthermore, our cross-sectional analysis confirms that companies with a significant positive cumulative average abnormal show certain characteristic. It was found that European companies have a higher likelihood to experience a stronger significant positive market reaction to their integrated report publication.

Keywords: integrated report, event methodology, cumulative abnormal return, sustainability, CAPM

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Authors: C. F. Jones Couto

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The implementation of quality Physical Education (PE) inspires and instils lasting healthy behavioural patterns, hence have the potential as an educational tool to teach values in today’s society. The goal of PE should be to contribute to the acceptance of the infinite qualities of South Africa’s (RSA) diversity and to claim RSA’s diversity as a source of strength that forms a universal bond of a common set of values. There is a global change in the interaction of children with their environment; their lives are shaped by forces that do not necessarily assist them in learning and applying values. In most countries today, the responsibility for developing values is assigned to schools in formal teaching settings. Values-based education offers an investment in individual and societal improvement through attendance to a values framework. The aim of this qualitative research is to develop a PE programme aligned with the current South African curriculum, enriched with values of Olympism and Ubuntuism, and to present PE teacher training workshops (TTW). Participatory action research will be used as the basis of how data will be collected, analysed, and presented on an ongoing, cyclical basis. PE teachers from different schools in the Tshwane District of RSA will participate as they can best inform the research questions and enhance the understanding of the phenomenon under study. The outcomes of using PE as a tool to teach values can propose recommendations to the Department of Basic Education of RSA to improve and implement a quality PE curriculum that is applicable to practice and that will optimize the chances of meeting the South African National Curriculum Statement standards. A PE programme with the aim of holistic development, based on the values of Olympism and Ubuntuism, can strive to ensure that the values set out in RSA’s constitution are part of PE organization, planning, and teaching at each South African school.

Keywords: olympism, physical education, teacher training, ubuntuism, values-based education

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Authors: Cinzia Colapinto, Davide La Torre

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Goal Programming (GP) and its variants were applied to marketing and specific marketing issues, such as media scheduling problems in the last decades. The concept of satisfaction functions has been widely utilized in the GP model to explicitly integrate the Decision-Maker’s preferences. These preferences can be guided by the available information regarding the decision-making situation. A GP model with satisfaction functions for media planning decisions is proposed and then illustrated through a case study related to a marketing/media campaign in the Italian market.

Keywords: goal programming, satisfaction functions, media planning, tourism management

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Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Seyed Salahedin Naghshbandi, Mahnaz Ahmadikhatir, Siavash Hamidzadeh

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The purpose of this study was to investigate the relationship between organizational political behavior and ethical values with the job enthusiasm of the sport personnel of the National Iranian Gas Company. The population of this research included all personnel of the National Iranian Gas Company's sports personnel (150 people). For collecting information, library resources and three questionnaires, organizational political behavior by Kaspar and Carlsen (1997), Lewall's moral values questionnaire (1986) and job enthusiasm questionnaire Schaufeli & Bekker (2003) have been used. Validity of the questionnaires was confirmed by university professors. Using Cronbach alpha correlation coefficient, the reliability of the organizational political behavior questionnaire was 0.92, the moral values questionnaire was 0.86 and the Schaufeli & Baker job enthusiasm questionnaire was 0.91-0.96. The results of this research show a significant, direct and positive relationship between the components of job aspiration with political behavior and ethical values. Therefore, managers of organizations should, as far as possible, remove political behaviors from the organization and be able to institutionalize ethical values in their organization so that they can increase employee eagerness.

Keywords: political behavior, ethical values, job enthusiasm, staff, national Iranian gas company

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Authors: Montserrat Guillen, Stephania Mosquera-Lopez, Jorge Uribe

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An empirical study of market risk transmission between electricity prices in the Nord Pool interconnected market is done. Crucially, it is differentiated between risk propagation in the two tails of the price variation distribution. Thus, the downside risk from upside risk spillovers is distinguished. The results found document an asymmetric nature of risk and risk propagation in the two tails of the electricity price log variations. Risk spillovers following price increments in the market are transmitted to a larger extent than those after price reductions. Also, asymmetries related to both, the size of the transaction area and related to whether a given area behaves as a net-exporter or net-importer of electricity, are documented. For instance, on the one hand, the bigger the area of the transaction, the smaller the size of the volatility shocks that it receives. On the other hand, exporters of electricity, alongside countries with a significant dependence on renewable sources, tend to be net-transmitters of volatility to the rest of the system. Additionally, insights on the predictive power of positive and negative semivariances for future market volatility are provided. It is shown that depending on the forecasting horizon, downside and upside shocks to the market are featured by a distinctive persistence, and that upside volatility impacts more on net-importers of electricity, while the opposite holds for net-exporters.

Keywords: electricity prices, realized volatility, semivariances, volatility spillovers

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Authors: Priti Bajpai, Mohammed Shibil

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This paper utilizes a comparative case study design to examine a regional onion market. The particular case of onion markets is used to understand perishable product supply chains. The site for the study is Dubai, United Arab Emirates. Results from a six-month field study are outlined. In particular, the findings suggest that firms should examine adding additional destinations to their supply chain. Further, we argue that utilizing Dubai as a supply chain hub is in certain cases counterproductive. Implications for food supply chains and regional trade are discussed.

Keywords: supply chains, food markets, onion trade, field study

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Authors: Sabine Ambros, Ulrich Kulozik

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Berries such as blue- and raspberries belong to the most valuable fruits. To preserve the characteristic flavor and the high contents of vitamins and anthocyanins, the very sensitive berries are usually dried by lyophilization. As this method is very time- and energy-consuming, the dried fruit is extremely expensive. However, healthy snack foods are growing in popularity. Especially dried fruit free of any additives or additional sugar are more and more asked for. To make these products affordable, the fruits have to be dried by a method that is more energy-efficient than freeze drying but reveals the same high product quality. The additional insertion of microwaves to a freeze drying process was examined in this work to overcome the inconveniences of freeze drying. As microwaves penetrate the product volumetrically, sublimation takes place simultaneously all over the product and leads to a many times shorter process duration. A range of microwave and pressure settings was applied to find the optimum drying condition. The influence of the process parameters microwave power and chamber pressure on drying kinetics, product temperature and product quality was investigated to find the best condition for an energy-efficient process with high product quality. The product quality was evaluated by rehydration capacitiy, crispiness, shrinkage, color, vitamin C content and antioxidative capacity. The conclusion could be drawn that microwave freeze dried berries were almost equal to freeze dried fruit in all measured quality parameters or even could overcome it. Additionally, sensory evaluations could confirm the analytical studies. Drying time could be reduced by more than 75% at much lower energy consumption rates. Thus, an energy-efficient and cost saving method compared to the conventional freeze drying technique for the gentle production of tasty fruit or vegetable snacks has been found. This technique will make dried high-quality snacks available for many of consumers.

Keywords: blueberries, freeze drying, microwave freeze drying, process parameters, product quality

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Authors: G. Götz, P. Stich, J. Backhaus, G. Reinhart

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The rising demand for format-flexible packaging machines is caused by current market changes. Increasing the formatflexibility is a new goal for the packaging machine manufacturers’ product development process. There are no methodical or designorientated tools for a comprehensive consideration of this target. This paper defines the term format-flexibility in the context of packaging machines and shows the state-of-the-art for improving the changeover of production machines. The requirements for a new approach and the concept itself will be introduced, and the method elements will be explained. Finally, the use of the concept and the result of the development of a format-flexible packaging machine will be shown.

Keywords: packaging machine, format-flexibility, changeover, design method

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Saeidreza Radpour, Md. Alam Mondal, Amit Kumar

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Market penetration of high energy efficiency technologies has key impacts on energy consumption and GHG mitigation. Also, it will be useful to manage the policies formulated by public or private organizations to achieve energy or environmental targets. Energy intensity in residential sector of Alberta was 148.8 GJ per household in 2012 which is 39% more than the average of Canada 106.6 GJ, it was the highest amount among the provinces on per household energy consumption. Energy intensity by appliances of Alberta was 15.3 GJ per household in 2012 which is 14% higher than average value of other provinces and territories in energy demand intensity by appliances in Canada. In this research, a framework has been developed to analyze the market penetration and market share of high energy efficiency technologies in residential sector. The overall methodology was based on development of data-intensive models’ estimation of the market penetration of the appliances in the residential sector over a time period. The developed models were a function of a number of macroeconomic and technical parameters. Developed mathematical equations were developed based on twenty-two years of historical data (1990-2011). The models were analyzed through a series of statistical tests. The market shares of high efficiency appliances were estimated based on the related variables such as capital and operating costs, discount rate, appliance’s life time, annual interest rate, incentives and maximum achievable efficiency in the period of 2015 to 2050. Results show that the market penetration of refrigerators is higher than that of other appliances. The stocks of refrigerators per household are anticipated to increase from 1.28 in 2012 to 1.314 and 1.328 in 2030 and 2050, respectively. Modelling results show that the market penetration rate of stand-alone freezers will decrease between 2012 and 2050. Freezer stock per household will decline from 0.634 in 2012 to 0.556 and 0.515 in 2030 and 2050, respectively. The stock of dishwashers per household is expected to increase from 0.761 in 2012 to 0.865 and 0.960 in 2030 and 2050, respectively. The increase in the market penetration rate of clothes washers and clothes dryers is nearly parallel. The stock of clothes washers and clothes dryers per household is expected to rise from 0.893 and 0.979 in 2012 to 0.960 and 1.0 in 2050, respectively. This proposed presentation will include detailed discussion on the modelling methodology and results.

Keywords: appliances efficiency improvement, energy star, market penetration, residential sector

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Authors: Fumihiko Isada, Yuriko Isada

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The aim of this research is to clarify the difference by industry segment or product characteristics as regards organisation management for an open innovation to raise R&D performance. In particular, the trait of the pharmaceutical industry is defined in comparison with IT component industry segment. In considering open innovation, both inter-organisational relation and the management in an organisation are important issues. As methodology, a questionnaire was conducted. In conclusion, suitable organisation management according to the difference in industry segment or product characteristics became clear.

Keywords: empirical study, industry segment, open innovation, product-development organisation pattern

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, solder joint reliability, NUDD, connectivity issues, qualifications, characterization and control

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Authors: Tim Giesen, Raphael Adamietz, Pablo Mayer, Philipp Stiefel, Patrick Alle, Dirk Schlenker

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The competitiveness and success of new electrical energy storages such as battery cells are significantly dependent on a short time-to-market. Producers who decide to supply new battery cells to the market need to be easily adaptable in manufacturing with respect to the early customers’ needs in terms of cell size, materials, delivery time and quantity. In the initial state, the required output rates do not yet allow the producers to have a fully automated manufacturing line nor to supply handmade battery cells. Yet there was no solution for manufacturing battery cells in low to medium volumes in a reproducible way. Thus, in terms of cell format and output quantity, a concept for the flexible assembly of battery cells was developed by the Fraunhofer-Institute for Manufacturing Engineering and Automation. Based on clustered processes, the modular system platform can be modified, enlarged or retrofitted in a short time frame according to the ordered product. The paper shows the analysis of the production steps from a conventional battery cell assembly line. Process solutions were found by using I/O-analysis, functional structures, and morphological boxes. The identified elementary functions were subsequently clustered by functional coherences for automation solutions and thus the single process cluster was generated. The result presented in this paper enables to manufacture different cell products on the same production system using seven process clusters. The paper shows the solution for a batch-wise flexible battery cell production using advanced process control. Further, the performed tests and benefits by using the process clusters as cyber-physical systems for an integrated production and value chain are discussed. The solution lowers the hurdles for SMEs to launch innovative cell products on the global market.

Keywords: automation, battery production, carrier, advanced process control, cyber-physical system

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Authors: Cintia Midori Kaminishikawahara, Fernanda Jéssica Mendonça, Moisés Grespan, Elza Iouko Ida, Massami Shimokomaki, Adriana Lourenço Soares

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The quality of broiler breast meat is changing as a result of continuing emphasis on genetically bird’s selection for efficiently higher meat production. The consumer is experiencing a cooked product that is drier and less juicy when consumed. Breast meat has been classified as PSE (pale, soft, exudative), DFD (dark, firm, dry) and normal color meat. However, recently variations of this color have been observed and they are not in line with the specificity of the meat functional properties. Thus, the objective of this work was to report the finding of a new pale meat color group characterized as Pale, Firm and Non-exudative (PFN) based on its pH, color, meat functional properties and micro structural evaluation. Breast meat fillets samples (n=1045) from commercial line were classified into PSE (pH ≤5.8, L* ≥ 53.0), PFN (pH > 5.8 and L* ≥ 53.0) and Normal (pH >5.8 and L* < 53.0), based on pH and L* values. In sequence, a total of 30 samples of each group were analyzed for the water holding capacity (WHC) and shear force (SF). The incidence was 9.1% for PSE meat, 85.7% for PFN and 5.2% for Normal meat. The PSE meat presented lower values of WHC (P ≤ 0.05) followed in sequence by PFN and Normal samples and also the SF values of fresh PFN was higher than PSE meat (P ≤ 0.05) and similar to Normal samples. Under optical microscopy, the cell diameter was 10% higher for PFN in relation to PSE meat and similar to Normal meat. These preliminary results indicate an emerging group of breast meat and it should be considered that the Pale, Firm and Non-exudative should be considered as an ideal broiler breast meat quality.

Keywords: broiler PSE meat, light microscopy, texture, water holding capacity

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

Abstract:

Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

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Authors: Randy D. Colon

Abstract:

Through a freedom of information request, data pertaining to Housing Choice Voucher (HCV) households has been obtained from the Chicago Housing Authority, including rent price and number of bedrooms per HCV household, community area, and zip code from 2013 to the first quarter of 2018. Similar data pertaining to the private rental market will be obtained through public records found through the United States Department of Housing and Urban Development. The datasets will be analyzed through statistical and mapping software to investigate the potential link between HCV households and distorted rent prices. Quantitative data will be supplemented by qualitative data to investigate the lived experience of Chicago residents. Qualitative data will be collected at community meetings in the Chicago Englewood neighborhood through participation in neighborhood meetings and informal interviews with residents and community leaders. The qualitative data will be used to gain insight on the lived experience of community leaders and residents of the Englewood neighborhood in relation to housing, the rental market, and HCV. While there is an abundance of quantitative data on this subject, this qualitative data is necessary to capture the lived experience of local residents effected by a changing rental market. This topic reflects concerns voiced by members of the Englewood community, and this study aims to keep the community relevant in its findings.

Keywords: Chicago, housing, housing choice voucher program, housing subsidies, rental market

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Authors: Sarah A. Alotaibi, Mohammed A. Almutairi, Abdullah A. Alsayari, Adibah M. Almutairi, Somaiah K. Almubayedh

Abstract:

Concerns over the presence of acrylamide in food date back to 2002, when Swedish scientists stated that, in carbohydrate-rich foods, amounts of acrylamide were formed when cooked at high temperatures. Similar findings were reported by other researchers which, consequently, caused major international efforts to investigate dietary exposure and the subsequent health complications in order to properly manage this issue. Due to this issue, in this work, we aim to determine the acrylamide level in different foods (coffee, potato chips, biscuits, and baby food) commonly consumed by the Saudi population. In a total of forty-three samples, acrylamide was detected in twenty-three samples at levels of 12.3 to 2850 µg/kg. In reference to the food groups, the highest concentration of acrylamide was found in coffee samples (<12.3-2850 μg/kg), followed by potato chips (655-1310 μg/kg), then biscuits (23.5-449 μg/kg), whereas the lowest acrylamide level was observed in baby food (<14.75 – 126 μg/kg). Most coffee, biscuits and potato chips products contain high amount of acrylamide content and also the most commonly consumed product. Saudi adults had a mean exposure of acrylamide for coffee, potato, biscuit, and cereal (0.07439, 0.04794, 0.01125, 0.003371 µg/kg-b.w/day), respectively. On the other hand, exposure to acrylamide in Saudi infants and children to the same types of food was (0.1701, 0.1096, 0.02572, 0.00771 µg/kg-b.w/day), respectively. Most groups have a percentile that exceeds the tolerable daily intake (TDI) cancer value (2.6 µg/kg-b.w/day). Overall, the MOE results show that the Saudi population is at high risk of acrylamide-related disease in all food types, and there is a chance of cancer risk in all age groups (all values ˂10,000). Furthermore, it was found that in non-cancer risks, the acrylamide in all tested foods was within the safe limit (˃125), except for potato chips, in which there is a risk for diseases in the population. With potato and coffee as raw materials, additional studies were conducted to assess different factors, including temperature, cocking time, and additives affecting the acrylamide formation in fried potato and roasted coffee, by systematically varying processing temperatures and time values, a mitigation of acrylamide content was achieved when lowering the temperature and decreasing the cooking time. Furthermore, it was shown that the combination of the addition of chitosan and NaCl had a large impact on the formation.

Keywords: risk assessment, dietary exposure, MOA, acrylamide, hazard

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Authors: Chebouti-meziou Nadjiba1, And Chebouti Yahia2:

Abstract:

the cultivation of Pistachios Pistacia vera of rare plants in Algeria and this point to see the lack of knowledge of techniques, which resulted in the proliferation of the tree to obtain a limited benefit does not exceed 0.75 tons / hectare, in addition to the enemy that lead to poor product on the one hand, one of which buds into wood and fruit Chaetoptelius vestitus. Since the tree is the raw sound production, while 25 kg of infected tree produces about 15 kg of any shortage of fact that this insect Chaetoptelius vestitus spend the amount of trouble going in the summer the young twigs of the trees into a sound the product by20% and due to the composition by the problem of spending in the newly formed branches, which lead to this loss in yield

Keywords: chaetoptelius vestitus, pistacia vera, spending, return, poor product.

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Authors: Mesias Alfeus, Kirsty Fitzhenry, Alessia Lederer

Abstract:

The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits a better performance.

Keywords: default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

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Authors: Omar Awad, R. Mamat, F. Yusop, M. M. Noor, I. M. Yusri

Abstract:

Fusel oil is a by-product obtained through the fermentation of some agricultural products. The fusel oil properties are closer to other alternative combustible types and the limited number of studies on the use of fusel oil as an alcohol derivative in SI engines constitutes to the base of this study. This paper experimentally examined the impacts of a by-product of alcohol, which is fusel oil by blending it with gasoline, on engine performance, combustion characteristics, and emissions in a 4-cylinder SI engine. The test was achieved at different engine speeds and a 60 % throttle valve (load). As results, brake power, BTE, and BSFC of F10 are higher at all engine speeds. Maximum engine BTE was 33.9%, at the lowest BSFC with F10. Moreover, it is worth seeing that the F10 under rich air-fuel ratio has less variation of COVIMEP compared to the F20 and gasoline. F10 represents shorter combustion duration, thereby, the engine power increased. NOx emission for F10 at 4500 rpm was lower than gasoline. The highest value of HC emission is obtained with F10 compared to gasoline and F20 with an average increase of 11% over the engine speed range. CO and CO2 emissions increased when using fusel oil blends.

Keywords: fusel oil, spark ignition engine, by-product alcohol, combustion characteristics, engine emissions, alternative fuel

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Authors: Prajwal Eachempati, Laurent Muzellec, Ashish Kumar Jha

Abstract:

We use Facebook as a case study to investigate the complex relationship between the firm’s public discourse (and actions) surrounding data privacy and the performance of a business model based on monetizing user’s data. We do so by looking at the evolution of public discourse over time (2004–2021) and relate topics to revenue and stock market evolution Drawing from archival sources like Zuckerberg We use LDA topic modelling algorithm to reveal 19 topics regrouped in 6 major themes. We first show how, by using persuasive and convincing language that promises better protection of consumer data usage, but also emphasizes greater user control over their own data, the privacy issue is being reframed as one of greater user control and responsibility. Second, we aim to understand and put a value on the extent to which privacy disclosures have a potential impact on the financial performance of social media firms. There we found significant relationship between the topics pertaining to privacy and social media/technology, sentiment score and stock market prices. Revenue is found to be impacted by topics pertaining to politics and new product and service innovations while number of active users is not impacted by the topics unless moderated by external control variables like Return on Assets and Brand Equity.

Keywords: public discourses, data protection, social media, privacy, topic modeling, business models, financial performance

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