Search results for: business data processing

Authors: Kanamon Suwantada

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The purpose of this research is to understand customer’s expectations towards homestays and to establish the precise strategies to increase numbers of tourists for homestay business in Amphawa district, Samutsongkram, Thailand. The researcher aims to ensure that each host provides experiences to travelers who are looking for and determining new targets for homestay business in Amphawa as well as creating sustainable homestay using marketing strategies to increase customers. The methods allow interview and questionnaire to gain both overview data from the tourists and qualitative data from the homestay owner’s perspective to create a GAP analysis. The data was collected from 200 tourists, during 15th May - 30th July, 2011 from homestay in Amphawa Community. The questionnaires were divided into three sections: the demographic profile, customer information and influencing on purchasing position, and customer expectation towards homestay. The analysis, in fact, will be divided into two methods which are percentage and correlation analyses. The result of this research revealed that homestay had already provided customers with reasonable prices in good locations. Antithetically, activities that they offered still could not have met the customer’s requirements. Homestay providers should prepare additional activities such as village tour, local attraction tour, village daily life experiences, local ceremony participation, and interactive conversation with local people. Moreover, the results indicated that a price was the most important factor for choosing homestay.

Keywords: ecotourism, homestay, marketing, sufficiency economic philosophy

Procedia PDF Downloads 310

Authors: M. Gil, R. Montalvo

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Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

Procedia PDF Downloads 123

Authors: Lasha Kamashidze

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COVID19 has already become one of the biggest challenges in the modern world. The virus has also had a significant impact on the world economy, which has faced a major crisis. Each crisis and challenge creates new opportunities. Changes in the world have allowed us to see business in a new light. The aim of the article is to explore new opportunities in the business that have arisen as a result of the Corona virus. Now, organizations with a service profile are working to meet the rapidly changing needs of their staff and customers. Due to the situation created by the pandemic, it became necessary to make some changes in people's daily lives. It became necessary to adapt to the new reality. The changes caused by Coronavirus require in-depth research and analysis in the world economy, as the current situation is not ruled out to be repeated in the future. Many companies have resorted to remote work methods, which require organizational changes. The form of remote work is not new to the Georgian reality. In Georgia, as well as in the rest of the world, the business sector has undergone changes. It will be beneficial for many Georgian companies to make organizational changes that will allow them to work remotely. The current situation has shown the managers of both Georgian and other companies to have "weak points" in organizing modern business. A survey was conducted (online survey), as a result of which it received important information about the problems of remote work in Georgia.

Keywords: organizational change, coronomics, remote work, management

Procedia PDF Downloads 89

Authors: Hamed Saremi, Shahla Saremi

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In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: marketing strategy, business strategy, strategy alignment, house of quality deployment, production strategy

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Authors: Cai-Wan Chang-Jian, Han-Ting Tsai

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In the processing industry of metal forming, rolling is the most used method of processing. In a cold rolling factory of stainless steel, there occurs a product defect on temper rolling process within cold rolling. It is called 'roll marks', which is a phenomenon of undesirable flatness problem. In this research, we performed a series of experimental measurements on the roll marks, and we used optical sensors to measure it and compared the vibration frequency of roll marks with the vibration frequency of key components in the skin pass mill. We found there is less correlation between the above mentioned data. Finally, we took measurement on the motor driver in rolling mill. We found that the undulation frequency of motor could match with the frequency of roll marks, and then we have confirmed that the motor’s undulation caused roll marks.

Keywords: roll mark, plane strain, rolling mill, stainless steel

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Authors: David Muyise

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Mixed Integer Programming (MIP) is an approach that involves the optimization of a range of decision variables in order to minimize or maximize a particular objective function. The main objective of this study was to apply the MIP approach to optimize the deployment of waste plastic to fuel oil processing plants in Uganda. The processing plants are meant to reduce plastic pollution by pyrolyzing the waste plastic into a cleaner fuel that can be used to power diesel/paraffin engines, so as (1) to reduce the negative environmental impacts associated with plastic pollution and also (2) to curb down the energy gap by utilizing the fuel oil. A programming model was established and tested in two case study applications that are, small-scale applications in rural towns and large-scale deployment across major cities in the country. In order to design the supply chain, optimal decisions on the types of waste plastic to be processed, size, location and number of plants, and downstream fuel applications were concurrently made based on the payback period, investor requirements for capital cost and production cost of fuel and electricity. The model comprises qualitative data gathered from waste plastic pickers at landfills and potential investors, and quantitative data obtained from primary research. It was found out from the study that a distributed system is suitable for small rural towns, whereas a decentralized system is only suitable for big cities. Small towns of Kalagi, Mukono, Ishaka, and Jinja were found to be the ideal locations for the deployment of distributed processing systems, whereas Kampala, Mbarara, and Gulu cities were found to be the ideal locations initially utilize the decentralized pyrolysis technology system. We conclude that the model findings will be most important to investors, engineers, plant developers, and municipalities interested in waste plastic to fuel processing in Uganda and elsewhere in developing economy.

Keywords: mixed integer programming, fuel oil plants, optimisation of waste plastics, plastic pollution, pyrolyzing

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Claire Norman-Maillet

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Insider fraud, otherwise known as occupational, employee, or internal fraud, is a financial crime threat. Perpetrated by defrauding (or attempting to defraud) one’s current, prospective, or past employer, an ‘employee’ covers anyone employed by the company, including board members and contractors. The Coronavirus pandemic has forced insider fraud into the spotlight, and it isn’t dimming. As the focus of most academics and practitioners has historically been on that of ‘external fraud’, insider fraud is often overlooked or not considered to be a real threat. However, since COVID-19 changed the working world, pushing most of us into remote or hybrid working, employers cannot easily keep an eye on what their staff are doing, which has led to reliance on trust and transparency. This, therefore, brings about an increased risk of insider fraud perpetration. The objective of this paper is to explore why insider fraud is, therefore, now the biggest threat to a business. To achieve the research objective, participating individuals within the financial crime sector (either as a practitioner or consultants) attended semi-structured interviews with the researcher. The principal recruitment strategy for these individuals was via the researcher’s LinkedIn network. The main findings in the research suggest that insider fraud has been ignored and rejected as a threat to a business, owing to a reluctance to admit that a colleague may perpetrate. A positive of the Coronavirus pandemic is that it has forced insider fraud into a more prominent position and giving it more importance on a business’ agenda and risk register. Despite insider fraud always having been a possibility (and therefore a risk) within any business, it is very rare that a business has given it the attention it requires until now, if at all. The research concludes that insider fraud needs to prioritised by all businesses, and even ahead of external fraud. The research also provides advice on how a business can add new or enhance existing controls to mitigate the risk.

Keywords: insider fraud, occupational fraud, COVID-19, COVID, coronavirus, pandemic, internal fraud, financial crime, economic crime

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Eseldin Keleb

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In the pharmaceutical industry particle size distribution is an important parameter for the characterization of pharmaceutical powders. The powder flowability, reactivity and compatibility, which have a decisive impact on the final product, are determined by particle size and size distribution. Therefore, the aim of this study was to evaluate the influence of processing parameters on the particle size distribution measurements. Different Size fractions of α-lactose monohydrate and 5% polyvinylpyrrolidone were prepared by wet granulation and were used for the preparation of samples. The influence of sieve load (50, 100, 150, 200, 250, 300, and 350 g), processing time (5, 10, and 15 min), sample size ratios (high percentage of small and large particles), type of disturbances (vibration and shaking) and process reproducibility have been investigated. Results obtained showed that a sieve load of 50 g produce the best separation, a further increase in sample weight resulted in incomplete separation even after the extension of the processing time for 15 min. Performing sieving using vibration was rapider and more efficient than shaking. Meanwhile between day reproducibility showed that particle size distribution measurements are reproducible. However, for samples containing 70% fines or 70% large particles, which processed at optimized parameters, the incomplete separation was always observed. These results indicated that sieving reliability is highly influenced by the particle size distribution of the sample and care must be taken for samples with particle size distribution skewness.

Keywords: sieving, reliability, particle size distribution, processing parameters

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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: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Hamed Saremi, Suzan Taghavy, Shahla Saremi

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In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: strategy alignment, house of quality deployment, production strategy, marketing strategy, business strategy

Procedia PDF Downloads 435

Authors: Z. Babic, I. Veza, A. Balic, M. Crnjac

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The linear programming model is sometimes difficult to apply in real business situations due to its assumption of proportionality. This paper shows an example of how to use De Novo programming approach instead of linear programming. In the De Novo programming, resources are not fixed like in linear programming but resource quantities depend only on available budget. Budget is a new, important element of the De Novo approach. Two different production situations are presented: increasing costs and quantity discounts of raw materials. The focus of this paper is on advantages of the De Novo approach in the optimization of production plan for production company which produces souvenirs made from famous stone from the island of Brac, one of the greatest islands from Croatia.

Keywords: business process, De Novo programming, optimizing, production

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Authors: Wanbao Chen, Qianqian Yao, Zhenming Zhou

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Whole grains with intact pericarp are largely resistant to digestion by ruminants because entire kernels are not conducive to bacterial attachment. But processing methods makes the starch more accessible to microbes, and increases the rate and extent of starch degradation in the rumen. To estimate the feasibility of applying a steam-flaking as the processing technique of grains for ruminants, cereal grains (maize, wheat, barley and sorghum) were processed by steam-flaking (steam temperature 105°C, heating time, 45 min). And chemical analysis, in vitro gas production, volatile fatty acid concentrations, and energetic values were adopted to evaluate the effects of steam-flaking. In vitro cultivation was conducted for 48h with the rumen fluid collected from steers fed a total mixed ration consisted of 40% hay and 60% concentrates. The results showed that steam-flaking processing had a significant effect on the contents of neutral detergent fiber and acid detergent fiber (P < 0.01). The concentration of starch gelatinization degree in all grains was also great improved in steam-flaking grains, as steam-flaking processing disintegrates the crystal structure of cereal starch, which may subsequently facilitate absorption of moisture and swelling. Theoretical maximum gas production after steam-flaking processing showed no great difference. However, compared with intact grains, total gas production at 48 h and the rate of gas production were significantly (P < 0.01) increased in all types of grain. Furthermore, there was no effect of steam-flaking processing on total volatile fatty acid, but a decrease in the ratio between acetate and propionate was observed in the current in vitro fermentation. The present study also found that steam-flaking processing increased (P < 0.05) organic matter digestibility and energy concentration of the grains. The collective findings of the present study suggest that steam-flaking processing of grains could improve their rumen fermentation and energy utilization by ruminants. In conclusion, the utilization of steam-flaking would be practical to improve the quality of common cereal grains.

Keywords: cereal grains, gas production, in vitro rumen fermentation, steam-flaking processing

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Authors: Pavel Shcherban, Vlad Golovanov

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Currently, there is an active geological exploration and development of the subsoil shelf of the Kaliningrad region. To carry out a comprehensive and accurate assessment of the volumes and degree of extraction of hydrocarbons from open deposits, it is necessary to establish not only a number of geological and lithological characteristics of the structures under study, but also to determine the oil quality, its viscosity, density, fractional composition as accurately as possible. In terms of considered works, gas chromatography is one of the most capacious methods that allow the rapid formation of a significant amount of initial data. The aspects of the application of the gas chromatography method for determining the chemical characteristics of the hydrocarbons of the Kaliningrad shelf fields are observed in the article, as well as the correlation-regression analysis of these parameters in comparison with the previously obtained chemical characteristics of hydrocarbon deposits located on the land of the region. In the process of research, a number of methods of mathematical statistics and computer processing of large data sets have been applied, which makes it possible to evaluate the identity of the deposits, to specify the amount of reserves and to make a number of assumptions about the genesis of the hydrocarbons under analysis.

Keywords: computer processing of large databases, correlation-regression analysis, hydrocarbon deposits, method of gas chromatography

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Fred Alinda, Marjorie Negesa, Gerald Karyeija

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Like elsewhere in the world, youth unemployment remains a big problem more so to the most educated youth and female. In Rwanda, unemployment is estimated at 13.2% among youth graduates compared to 10.9% and 2.6 among secondary and primary graduates respectively. Though empirical evidence elsewhere associate youth unemployment with education level, relevance of skills and access to business support opportunities, mixed evidence still exist on the significance of these factors to youth employment. As youth employment strategies in countries like Rwanda continue to recognize the potential role university education can play to enhance employment, there is a need to understand the catalysts or barriers. This paper, therefore, draws empirical evidence from a survey on the influence of education qualification, skills relevance and access to business support opportunities on employment of the youth university graduates in Masaka sector, Rwanda. The analysis tested four hypotheses; access to university education significantly affects youth employment, Relevance of university education significantly contributes to youth employment; access to business support opportunities significantly contributes to youth employment, and significant gender differences exist in the employment of youth university graduates. A cross-section survey was used in lieu of the need to explore the prevailing status of youth employment and contributing factors across the sector. A questionnaire was used to collect data on a large sample of 269 youth to allow statistical analysis. This was beefed up with qualitative views of leaders and technical officials in the sector. The youth University graduates were selected using simple random sampling while the leaders and technical officials were selected purposively. Percentages were used to describe respondents in line with the variables under while a regression model for youth employment was fitted to determine the significant factors. The model results indicated a significant influence (p<0.05) of gender, education level and access to business support opportunities on employment of youth university graduates. This finding was also affirmed by the qualitative views of key informants. Qualitative views pointed to the fact that university education generally equipped the youth with skills that enabled their transition into employment mainly for a salary or wage. The skills were, however, deficient in technical and practical aspects. In addition, the youth generally lacked limited access to business support opportunities particularly guarantees for loans, business advisory, and grants for business as well as training in business skills that would help them gain salaried employment or transit into self-employment. The study findings bear an implication on the strategy for catalyzing youth employment through university education. The findings imply that university education should be embraced but with greater emphasis on or supplementation with specialized training in practical and technical skills as well as extending business support opportunities to the youth. This will accelerate the contribution of university education to youth employment.

Keywords: education, employment, self-employment, youth

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Authors: Balarabe Z. Ahmad, Anne-Lorène Vernay

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The emergence of electricity in Nigeria was dated back to 1896. The power plants have the potential to generate 12,522 MW of electric power. Whereas current dispatch is about 4,000 MW, access to electrification is about 60%, with consumption at 0.14 MWh/capita. The government embarked on energy reforms to mitigate energy poverty. The reform targeted the provision of electricity access to 75% of the population by 2020 and 90% by 2030. Growth of total electricity demand by a factor of 5 by 2035 had been projected. This means that Nigeria will require almost 530 TWh of electricity which can be delivered through generators with a capacity of 65 GW. Analogously, the geographical location of Nigeria has placed it in an advantageous position as the source of solar energy; the availability of a high sunshine belt is obvious in the country. The implication is that the far North, where energy poverty is high, equally has about twice the solar radiation as against southern Nigeria. Hence, the chance of generating solar electricity is 66% possible at 11850 x 103 GWh per year, which is one hundred times the current electricity consumption rate in the country. Harvesting these huge potentials may be a mirage if the entrepreneurs in the solar panel business are left with the conventional business models that are not uncertainty resilient. Currently, business entities in RE in Nigeria are uncertain of; accessing the national grid, purchasing potentials of cooperating organizations, currency fluctuation and interest rate increases. Uncertainties such as the security of projects and government policy are issues entrepreneurs must navigate to remain sustainable in the solar panel industry in Nigeria. The aim of this paper is to identify how entrepreneurial firms consider uncertainties in developing workable business models for commercializing solar energy projects in Nigeria. In an attempt to develop a novel business model, the paper investigated how entrepreneurial firms assess and navigate uncertainties. The roles of key stakeholders in helping entrepreneurs to manage uncertainties in the Nigeria RE sector were probed in the ongoing study. The study explored empirical uncertainties that are peculiar to RE entrepreneurs in Nigeria. A mixed-mode of research was embraced using qualitative data from face-to-face interviews conducted on the Solar Energy Entrepreneurs and the experts drawn from key stakeholders. Content analysis of the interview was done using Atlas. It is a nine qualitative tool. The result suggested that all stakeholders are required to synergize in developing an uncertainty resilient business model. It was opined that the RE entrepreneurs need modifications in the business recommendations encapsulated in the energy policy in Nigeria to strengthen their capability in delivering solar energy solutions to the yawning Nigerians.

Keywords: uncertainties, entrepreneurial, business model, solar-panel

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Authors: Krisada Sungkhamanee

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The objectives of this research are to search the management pattern of one district lodging entrepreneurs by sufficient economy ways, to know the constrains that affects this sector and design fit arrangement shape to sustain their business with Samut Songkram style. What will happen if they do not use this approach? Will they have a monetary crisis? The data and information are collected by informal discussions with 8 managers and 400 questionnaires. A mixed methods of both qualitative research and quantitative research are used and Bent Flyvbjerg’s phronesis is utilized for this analysis. Our paper will prove that sufficient economy can help small business firms to solve their problems. We think that the results of our research will be a financial pattern to solve many problems of the entrepreneurs and this way will can be a super model for other provinces of Thailand.

Keywords: Samut Songkram, service sector, sufficient economy, management pattern

Procedia PDF Downloads 365

Authors: E. Koyuncu

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The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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Authors: Kapil Pandey, Vishnu Goyal

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Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

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Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

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In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: breakage, computer vision, husking, rice kernel

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Authors: Sabiha Shahid Antora, Young Ki Chang

Abstract:

Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

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Authors: Muhammad Irfan, Guillermo Requena, Jan Haubrich

Abstract:

Adhesively bonded aluminum joints are common in automotive and aircraft industries and are one of the enablers of lightweight construction to minimize the carbon emissions during transportation for a sustainable life. This study is focused on the effects of two thermal processing routes, i.e., by direct and induction heating, and their parameters on void formation in PA6 bonded aluminum EN-AW6082 joints. The joints were characterized microanalytically as well as by lap shear experiments. The aging resistance of the joints was studied by accelerated aging tests at 80°C hot water. It was found that the processing of single lap joints by direct heating in a convection oven causes the formation of a large number of voids in the bond line. The formation of voids in the convection oven was due to longer processing times and was independent of any surface pretreatments of the metal as well as the processing temperature. However, when processing at low temperatures, a large number of small-sized voids were observed under the optical microscope, and they were larger in size but reduced in numbers at higher temperatures. An induction heating process was developed, which not only successfully reduced or eliminated the voids in PA6 bonded joints but also reduced the processing times for joining significantly. Consistent with the trend in direct heating, longer processing times and higher temperatures in induction heating also led to an increased formation of voids in the bond line. Subsequent single lap shear tests revealed that the increasing void contents led to a 21% reduction in lap shear strengths (i.e., from ~47 MPa for induction heating to ~37 MPa for direct heating). Also, there was a 17% reduction in lap shear strengths when the consolidation temperature was raised from 220˚C to 300˚C during induction heating. However, below a certain threshold of void contents, there was no observable effect on the lap shear strengths as well as on hydrothermal aging resistance of the joints consolidated by the induction heating process.

Keywords: adhesive, aluminium, convection oven, induction heating, mechanical properties, nylon6 (PA6), pretreatment, void

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Authors: Ivana Tadić, Željana Aljinović Barać, Nikolina Plazonić

Abstract:

Living today in turbulent business environment forces companies to distinguish from each other, securing sustainable competitive growth and competitive advantage. The best possible solution is to invest (effort and financial resources) within companies’ different practices of human resource management (HRM), more specifically in employees’ knowledge, skills and abilities. Applying this approach companies will create enviable level of human capital securing its economic growth. Employees become human capital for their employers at the moment when they contribute with their own knowledge and abilities in creating material and non-material value of the company. The main aim of this research is to explore the relations between human capital investments and business excellence of Croatian companies. Furthermore, the differences in the level of human capital investments with regard to several companies’ characteristics (e.g. size of the company, ownership and type of the industry) are investigated.

Keywords: business excellence, Croatian industries, human capital investments, human resource management

Procedia PDF Downloads 362

Authors: Dalia Suša Vugec, Ana-Marija Stjepić, Darija Ivandić Vidović

Abstract:

Digital transformation is one of the latest trends on the global market. In order to maintain the competitive advantage and sustainability, increasing number of organizations are conducting digital transformation processes. Those organizations are changing their business processes and creating new business models with the help of digital technologies. In that sense, one should also observe the role of business process management (BPM) and its maturity in driving digital transformation. Therefore, the goal of this paper is to investigate the role of BPM in digital transformation process within one organization. Since experiences from practice show that organizations from financial sector could be observed as leaders in digital transformation, an insurance company has been selected to participate in the study. That company has been selected due to the high level of its BPM maturity and the fact that it has previously been through a digital transformation process. In order to fulfill the goals of the paper, several interviews, as well as questionnaires, have been conducted within the selected company. The results are presented in a form of a case study. Results indicate that digital transformation process within the observed company has been successful, with special focus on the development of digital strategy, BPM and change management. The role of BPM in the digital transformation of the observed company is further discussed in the paper.

Keywords: business process management, case study, Croatia, digital transformation, insurance company

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Authors: Néstor Iván Rojas, Wilson Medina Sierra

Abstract:

Managing spatial information is described through a Geographic Information System (GIS), for some neighborhoods in the city of Tunja, in relation to the structural typology of the buildings. The use of GIS provides tools that facilitate the capture, processing, analysis and dissemination of cartographic information, product quality evaluation of the classification of buildings. Allows the development of a method that unifies and standardizes processes information. The project aims to generate a geographic database that is useful to the entities responsible for planning and disaster prevention and care for vulnerable populations, also seeks to be a basis for seismic vulnerability studies that can contribute in a study of urban seismic microzonation. The methodology consists in capturing the plat including road naming, neighborhoods, blocks and buildings, to which were added as attributes, the product of the evaluation of each of the housing data such as the number of inhabitants and classification, year of construction, the predominant structural systems, the type of mezzanine board and state of favorability, the presence of geo-technical problems, the type of cover, the use of each building, damage to structural and non-structural elements . The above data are tabulated in a spreadsheet that includes cadastral number, through which are systematically included in the respective building that also has that attribute. Geo-referenced data base is obtained, from which graphical outputs are generated, producing thematic maps for each evaluated data, which clearly show the spatial distribution of the information obtained. Using GIS offers important advantages for spatial information management and facilitates consultation and update. Usefulness of the project is recognized as a basis for studies on issues of planning and prevention.

Keywords: microzonation, buildings, geo-processing, cadastral number

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Authors: Rik van Leeuwen, Ger Koole

Abstract:

Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

Procedia PDF Downloads 108

Authors: Yusuf Sani Abubakar

Abstract:

This paper investigates mechanisms of settlement of disputes at the Islamic Financial Institutions (IFIs). Dispute settlement at the Islamic Financial Institutions (IFIs) can be both through litigation as well as Alternative Dispute Resolution (ADR). The paper aims to investigate how disputes are settled at the Islamic Financial Institutions (IFIs), as it is natural to have disagreements between different parties involved in the business of Islamic Financial Institutions (IFIs). The paper adopts a qualitative methodology where the sources are taken from journals, books, websites etc. In analyzing the data obtained from the sources, content analysis will be used. In addition to writings on this topic by various writers, this paper will add to the literature and will recommend certain effective ways of solving disputes arising between parties participating in the business of Islamic Financial Institutions (IFIs).

Keywords: Islamic finance, dispute resolution, Islamic financial institutions, litigation

Procedia PDF Downloads 166