Search results for: artificial stock market

Authors: Mustafa İlhan Akbaş, Özlem Garibay, Ivan Garibay

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The economic entities in innovation ecosystems form various industry clusters, in which they compete and cooperate to survive and grow. Within a successful and stable industry cluster, the entities acquire different roles that complement each other in the system. The universities and research centers have been accepted to have a critical role in these systems for the creation and development of innovations. However, the real effect of research institutions on regional economic growth is difficult to assess. In this paper, we present our approach for the identification of the impact of research activities on the regional entrepreneurship for a specific high-tech industry: optics and photonics. The optics and photonics has been defined as an enabling industry, which combines the high-tech photonics technology with the developing optics industry. The recent literature suggests that the growth of optics and photonics firms depends on three important factors: the embedded regional specializations in the labor market, the research and development infrastructure, and a dynamic small firm network capable of absorbing new technologies, products and processes. Therefore, the role of each factor and the dynamics among them must be understood to identify the requirements of the entrepreneurship activities in optics and photonics industry. There are three main contributions of our approach. The recent studies show that the innovation in optics and photonics industry is mostly located around metropolitan areas. There are also studies mentioning the importance of research center locations and universities in the regional development of optics and photonics industry. These studies are mostly limited with the number of patents received within a short period of time or some limited survey results. Therefore the first contribution of our approach is conducting a comprehensive analysis for the state and recent history of the photonics and optics research in the US. For this purpose, both the research centers specialized in optics and photonics and the related research groups in various departments of institutions (e.g. Electrical Engineering, Materials Science) are identified and a geographical study of their locations is presented. The second contribution of the paper is the analysis of regional entrepreneurship activities in optics and photonics in recent years. We use the membership data of the International Society for Optics and Photonics (SPIE) and the regional photonics clusters to identify the optics and photonics companies in the US. Then the profiles and activities of these companies are gathered by extracting and integrating the related data from the National Establishment Time Series (NETS) database, ES-202 database and the data sets from the regional photonics clusters. The number of start-ups, their employee numbers and sales are some examples of the extracted data for the industry. Our third contribution is the utilization of collected data to investigate the impact of research institutions on the regional optics and photonics industry growth and entrepreneurship. In this analysis, the regional and periodical conditions of the overall market are taken into consideration while discovering and quantifying the statistical correlations.

Keywords: entrepreneurship, industrial clusters, optics, photonics, emerging industries, research centers

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Aisha Ijaz

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The paper focuses on the impact of Muslim religiosity on convenience food purchases and involvement experienced in a non-Muslim culture. There is a scarcity of research on the purchasing patterns of Muslim diaspora communities residing in risk societies, particularly in contexts where there is an increasing inclination toward industrialized food items alongside a renewed interest in the concept of natural foods. The United Kingdom serves as an appropriate setting for this study due to the increasing Muslim population in the country, paralleled by the expanding Halal Food Market. A multi-dimensional framework is proposed, testing for five forms of involvement, specifically Purchase Decision Involvement, Product Involvement, Behavioural Involvement, Intrinsic Risk and Extrinsic Risk. Quantitative cross-sectional consumer data were collected through a face-to-face survey contact method with 141 Muslims during the summer of 2020 in Liverpool located in the Northwest of England. proportion formula was utilitsed, and the population of interest was stratified by gender and age before recruitment took place through local mosques and community centers. Six input variables were used (intrinsic religiosity and involvement dimensions), dividing the sample into 4 clusters using the Two-Step Cluster Analysis procedure in SPSS. Nuanced variances were observed in the type of involvement experienced by religiosity group, which influences behaviour when purchasing convenience food. Four distinct market segments were identified: highly religious ego-involving (39.7%), less religious active (26.2%), highly religious unaware (16.3%), less religious concerned (17.7%). These segments differ significantly with respects to their involvement, behavioural variables (place of purchase and information sources used), socio-cultural (acculturation and social class), and individual characteristics. Choosing the appropriate convenience food is centrally related to the value system of highly religious ego-involving first-generation Muslims, which explains their preference for shopping at ethnic food stores. Less religious active consumers are older and highly alert in information processing to make the optimal food choice, relying heavily on product label sources. Highly religious unaware Muslims are less dietary acculturated to the UK diet and tend to rely on digital and expert advice sources. The less-religious concerned segment, who are typified by younger age and third generation, are engaged with the purchase process because they are worried about making unsuitable food choices. Research implications are outlined and potential avenues for further explorations are identified.

Keywords: consumer behaviour, consumption, convenience food, religion, muslims, UK

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Authors: Prakash Prajapati

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E commerce is certainly one of the business alternatives that individual will have to analyze in the forthcoming years. E-commerce is said to bring about arched type conversion in the world for exchange market. Prognosis E-commerce is presenting dreadful business advancement in our country. Endorsed by ascending online user base & mobile phone presentation, Indian e-commerce has been splendid development in the last few years. Conceding India’s analytical dividend and spiraling internet admittance, the sector is contracted to scale higher heights. Although, India’s overall peddle opportunity is consequential, the sector is beset with some deliberate challenges. The current study has been proceeded to explore the present scenario, status & future advancement of e-commerce in India and review the challenges and opportunities of e-commerce in India.

Keywords: online selling, retail selling online, product process, business opportunity

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Authors: Hasan Vural

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In this study, innovation subject is explained firstly. Later the basic concepts of innovation and new food products development in marketing of bee products are investigated. Examples of the application of research results will be presented. Subject will be discussed benefiting from scientific studies based on literature review. Innovation is widely recognised as important to commercial success in the food industry, as both a major source of competitive advantage and the creation of a company’s future. However, the new product development process is described as being fraught with failures, with only approximately 10% of new products remaining on the market within a year of commercialisation. In addition, for every new food product that does reach commercialisation, there are likely to be many concepts that are rejected during the new food product development process. No roadmap exactly describes a route to a goal: exhortations to follow ‘10 Steps to a successful Product’ or use ‘Smith’s Method to Do Successful Products’ are, therefore, all approximations. Roadmaps do not describe the actual journey, only the general direction.

Keywords: innovation, agrofood product development, beekeeping products, honey marketing

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Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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Authors: Y. C. Bhattacharyulu, Amit J. Agrawal, Vikram S. Chatake, Ketan S. Desai

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In recent years, the improper disposal of waste polymeric materials like plastics, rubber, liquid containers, daily household materials, etc. is posing a grave problem by polluting the environment. On the other hand fluctuations in the oil market and limited stocks of fossil fuels have diverted the interest of researchers to study the production of fuels and hydrocarbons from alternative sources. Hence, to study the production of fuels from waste plastic is the need of hour at present. Effect of alkali solutions of different concentrations with copper comprising catalyst on depolymerisation reactions was studied here. The present study may become a preliminary method for obtaining valuable hydrocarbons from waste plastics and an effective way for depolymerising or degrading waste plastics for their safe disposal without causing any environmental problems.

Keywords: catalyst, depolymerisation, disposal, hydrocarbon liquids, waste plastic

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Natalie Riley, Anita Quigley, Robert M. I. Kapsa, George W. Greene

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As the fields of medicine and bionics grow rapidly in technological advancement, the future and success of it depends on the ability to effectively interface between the artificial and the biological worlds. The biggest obstacle when it comes to implantable, electronic medical devices, is maintaining a ‘clean’, low noise electrical connection that allows for efficient sharing of electrical information between the artificial and biological systems. Implant fouling occurs with the adhesion and accumulation of proteins and various cell types as a result of the immune response to protect itself from the foreign object, essentially forming an electrical insulation barrier that often leads to implant failure over time. Lubricin (LUB) functions as a major boundary lubricant in articular joints, a unique glycoprotein with impressive anti-adhesive properties that self-assembles to virtually any substrate to form a highly ordered, ‘telechelic’ polymer brush. LUB does not passivate electroactive surfaces which makes it ideal, along with its innate biocompatibility, as a coating for implantable bionic electrodes. It is the aim of the study to investigate LUB’s anti-fouling properties and its potential as a safe, bioinspired material for coating applications to enhance the performance and longevity of implantable medical devices as well as reducing the frequency of implant replacement surgeries. Native, bovine-derived LUB (N-LUB) and recombinant LUB (R-LUB) were applied to gold-coated mylar surfaces. Fibroblast, chondrocyte and neural cell types were cultured and grown on the coatings under both passive and electrically stimulated conditions to test the stability and anti-adhesive property of the LUB coating in the presence of an electric field. Lactate dehydrogenase (LDH) assays were conducted as a directly proportional cell population count on each surface along with immunofluorescent microscopy to visualize cells. One-way analysis of variance (ANOVA) with post-hoc Tukey’s test was used to test for statistical significance. Under both passive and electrically stimulated conditions, LUB significantly reduced cell attachment compared to bare gold. Comparing the two coating types, R-LUB reduced cell attachment significantly compared to its native counterpart. Immunofluorescent micrographs visually confirmed LUB’s antiadhesive property, R-LUB consistently demonstrating significantly less attached cells for both fibroblasts and chondrocytes. Preliminary results investigating neural cells have so far demonstrated that R-LUB has little effect on reducing neural cell attachment; the study is ongoing. Recombinant LUB coatings demonstrated impressive anti-adhesive properties, reducing cell attachment in fibroblasts and chondrocytes. These findings and the availability of recombinant LUB brings into question the results of previous experiments conducted using native-derived LUB, its potential not adequately represented nor realized due to unknown factors and impurities that warrant further study. R-LUB is stable and maintains its anti-fouling property under electrical stimulation, making it suitable for electroactive surfaces.

Keywords: anti-fouling, bioinspired, cell attachment, lubricin

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Authors: Yaprak Aydin

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The rural is no longer a space of only agricultural activities that gave into the global market demands; or an idyll to return after retirement; or only a reservoir of cultural values, but rather a vision to redefine the future in terms of production and consumption relations. Gulpınar in Turkey and Ashtarak in Armenia are two towns where a new ground of dialogue between two communities has been initiated: ‘energy democracy’, which is a significant driving force in a sense of gathering people of two historically conflicted communities around common future concerns; and in a sense of transforming the accepted knowledge on the rurality and all the social structures it represents. This paper seeks to provoke a discussion of to what extent such a rurality is attainable by contextualizing – through visits and meetings in person – two towns and two communities within a renewable energy project called 'Under the Same Sun' carried out by two local civil society organizations together at two public spaces.

Keywords: civil society, energy democracy, prosumer communities, renewable energy, transnational rurality

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Authors: Patrick C. H. Morel, Ian W. Barugh, Kirsty L. Chidgey

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The aim of this study was to quantify the level of piglet deaths in outdoor farrowing systems in New Zealand. A total of 14 farms were visited, the farmers interviewed, and data collected. A total of 10,154 sows were kept on those farms representing an estimated 33% of the NZ sow herd or 80% of the outdoor sow herd in 2016. Data from 25,911 litters was available for the different analyses. The characteristics and reproductive performance for the years 2015-2016 from the 14 farms surveyed in this study were analysed, and the following results were obtained. The average percentage of stillbirths was 7.1% ranging between 3.5 and 10.7%, and the average pre-weaning live-born mortality was 16.7% ranging between 3.7% and 23.6%. The majority of piglet deaths (89%) occurred during the first week after birth, with 81% of deaths occurring up to day three. The number of piglets born alive was 12.3 (8.0 to 14.0), and average number of piglets weaned per sow per year was 22.4, range 10.5-27.3. The average stocking rate per ha (number of sows and mated gilts) was 15.3 and ranged from 2.8 to 28.6. The sow to boar ratio average was 20.9:1 and the range was 7.1: 1 to 63:1. The sow replacement rate ranged between 37% and 78%. There was a large variation in the piglet live-born mortality both between months within a farm and between farms within a given month. The monthly recorded piglet mortality ranged between 7.7% and 31.5%, and there was no statistically significant difference between months on the number of piglets born, born alive, weaned or on pre-weaning piglet mortality. Twelve different types of hut/farrowing systems were used on the 14 farms. No difference in piglet mortality was observed between A-Frame, A-Frame Modified and for Box-shape huts. There was a positive relationship between the average number of piglets born per litter and the number of piglets born alive (r=0.975) or the number weaned per litter (r=0.845). Moreover, as the average number of piglets born-alive increases, both pre-weaning live-born mortality rate and the number of piglets weaned increased. An increase of 1 piglet in the number born alive corresponds to an increase of 2.9% in live-born mortality and an increase of 0.56 piglets weaned. Farmers reported that staff are the key to success with the key attributes being: good and reliable with attention to detail and skills with the stock.

Keywords: mortality, piglets, outdoor, pig farm

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Anis A. Ansari, Aftab A. Ansari

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Electronic waste is inundating the traditional solid-waste-disposal facilities, which are inadequately designed to handle and manage such type of new wastes. Since electronic waste contains mostly hazardous and even toxic materials, the seriousness of its effects on human health and the environment cannot be ignored in present scenario. Waste from the electronic industry is increasing exponentially day by day. From the last 20 years, we are continuously generating huge quantities of e-waste such as obsolete computers and other discarded electronic components, mainly due to evolution of newer technologies as a result of constant efforts in research and development in this sector. Polymers, one of the major constituents in almost every electronic waste, such as computers, printers, electronic equipment, entertainment devices, mobile phones, television sets etc., are if properly recycled can create a new business opportunity. This would not only create potential market for polymers to improve economy but also the priceless land used as dumping sites of electronic waste, can be utilized for other productive purposes.

Keywords: polymer recycling, electronic waste, hazardous materials, electronic components

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Authors: Mawardati Mawardati

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This research was carried out on the traditional milkfish and shrimp culture cultivation from March to May 2018 in East Aceh District. This study aims to to analyze the differences between traditional milkfish cultivation and shrimp farming in East Aceh District, Aceh Province. The analytical method used is acquisition analysis and Independent Sample T test analysis. The results showed a significant difference between milkfish farming and shrimp farming in East Aceh District, Aceh Province. Based on the results of the analysis, the average profit from shrimp farming is higher than that of milkfish farming. This demand exceeds market demand for exports. Thus the price of shrimp is still far higher than the price of milk fish.

Keywords: comparative, profit, shrimp, milkfish

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

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Authors: Charalampos Saridakis, Stelios Tsafarakis

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Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution

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Authors: Amit Kumar Dwivedi, Priyanko Ghosh

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Data Envelopment analysis (DEA) has been used to calculate the technical and scale efficiency measures of the public and private sugar manufacturing firms of the Indian Sugar Industry (2006 to 2010). Within DEA framework, the input & Output oriented Variable Returns to Scale (VRS) & Constant Return to Scale (CRS) model is employed for the study of Decision making units (DMUs). A representative sample of 43 firms which account for major portion of the total market share is studied. The selection criterion for the inclusion of a firm in the analysis was the total sales of INR 5,000 million or more in the year 2010. After reviewing the literature it is found that no study has been conducted in the context of Indian sugar manufacturing firms in the Post-liberalization era which motivates us to initiate the study.

Keywords: technical efficiency, Indian sugar manufacturing units, DEA, input output oriented

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Authors: Paulina Pietrzak

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The understanding of the role of the contemporary translator is fraught with contradictions and idealistic visions of individuals who, by definition, should be fully competent and versatile. In spite of the fact that lots of translation researchers have probed into the identification and exploration of the concept of translator competence, little study has been devoted to its metacognitive aspects. Due to the dynamic nature of the translator’s occupation, it is difficult to predict what specific skills will prove useful for novice translators in their professional career. Thus, it is crucial that the translator is self-regulated enough to adapt to changing job demands and effectively function in the contemporary, highly dynamic, translation market. The objective of the presentation is to investigate the role and nature of the translator’s self-regulation. It will also demonstrate the results of a pilot study into translation trainees’ self-regulatory skills and explore implications of these findings for translator training in relation to theories of student empowerment.

Keywords: cognitive translation research, translator competence, self-regulatory skills, translator training

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Authors: N. Drir, L. Barazane, M. Loudini

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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

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Authors: Yu Chen

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In line with existing philosophical approaches, this research proposes a conceptual model with an innovative spatial vision and aesthetic principles for Artificial Intelligence (AI) application in brand advertising. The model first identifies the major constituencies in contemporary advertising on three spatial levels—physical, psychological, and symbolic. The model further incorporates the relationships among AI, aesthetics, branding, and advertising and their interactions with the major actors in all spaces. It illustrates that AI may follow the aesthetic principles-- beauty, elegance, and simplicity-- to reinforce brand identity and consistency in advertising, to collaborate with stakeholders, and to satisfy different advertising objectives on each level. It proposes that, with aesthetic guidelines, AI may assist consumers to emerge into the physical, psychological, and symbolic advertising spaces and helps transcend the tangible advertising messages to meaningful brand symbols. Conceptually, the research illustrates that even though consumers’ engagement with brand mostly begins with physical advertising and later moves to psychological-symbolic, AI-assisted advertising should start with the understanding of brand symbolic-psychological and consumer aesthetic preferences before the physical design to better resonate. Limits of AI and future AI functions in advertising are discussed.

Keywords: AI, spatial, aesthetic, brand advertising

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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Authors: Sanjiv Kumar Soni, Chetna Janveja

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The approach of utilizing zero cost kitchen waste residues for growing suitable strains of fungi for the induction of a cocktail of hydrolytic enzymes and ethanol generation has been validated in the present study with the objective of developing an indigenous biorefinery for low cost bioethanol production with the generation of zero waste. Solid state fermentation has been carried out to evaluate the potential of various steam pretreated kitchen waste residues as substrates for the co-production of multiple carbohydrases including cellulases, hemicellulases, pectinase and amylases by a locally isolated strain of Aspergillus niger C-5. Of all the residues, potato peels induced the maximum yields of all the enzyme components corresponding to 64.0±1.92 IU of CMCase, 17.0±0.54 IU of FPase , 42.8±1.28 IU of β-glucosidase, 990.0±28.90 IU of xylanase, 53.2±2.12 IU of mannanase, 126.0±3.72 IU of pectinase, 31500.0±375.78 IU of α-amylase and 488.8±9.82 IU of glucoamylase/g dry substrate respectively. Saccharification of various kitchen refuse residues using inhouse produced crude enzyme cocktail resulted in the release of 610±10.56, 570±8.89, 435±6.54, 475±4.56, 445±4.27, 385±4.49, 370±6.89, 490±10.45 mg of total reducing sugars/g of dried potato peels, orange peels, pineapple peels, mausami peels, onion peels, banana stalks, pea pods and composite mixture respectively revealing carbohydrate conversion efficiencies in the range of 97.0-99.4%. After fermentation of released hexoses by Saccharomyces cerevisae, ethanol yields ranging from 80-262 mL/ kg of dry residues were obtained. The study has successfully evaluated the valorization of kitchen garbage, a highly biodegradable component in Municipal Solid Waste by using it as a substrate for the in-house co-production of multiple carbohydrases and employing the steam treated residues as a feed stock for bioethanol production. Such valorization of kitchen garbage may reduce the level of Municipal Solid Waste going into land-fills thus lowering the emissions of greenhouse gases. Moreover, the solid residue left after the bioconversion may be used as a biofertilizer for improving the fertility of the soils.

Keywords: kitchen waste, bioethanol, solid waste, bioconversion, waste management

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Authors: Surinder Sood, Debajyoti Mukherjee

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Formal verification techniques have become widely popular in pre-silicon verification as an alternate to constrain random simulation based techniques. This paper proposed a novel formal verification-based coverage augmentation technique in verifying complex RTL functional verification faster. The proposed approach relies on augmenting coverage analysis coming from simulation and formal verification. Besides this, the functional qualification framework not only helps in improving the coverage at a faster pace but also aids in maturing and qualifying the formal verification infrastructure. The proposed technique has helped to achieve faster verification sign-off, resulting in faster time-to-market. The design picked had a complex control and data path and had many configurable options to meet multiple specification needs. The flow is generic, and tool independent, thereby leveraging across the projects and design will be much easier

Keywords: COI (cone of influence), coverage, formal verification, fault injection

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Authors: M. N. Akhtar, J. N. Akhtar

Abstract:

The present study evaluates the properties of class F fly ash as a replacement of natural materials in civil engineering construction industry. The low-lime flash similar to class F is the prime variety generated in India, although it has significantly smaller volumes of high-lime fly ash as compared to class C. The chemical and physical characterization of the sample is carried out with the number of experimental approaches in order to investigate all relevant features present in the samples. For chemical analysis, elementary quantitative results from point analysis and scanning electron microscopy (SEM)/dispersive spectroscopy (EDS) techniques were used to identify the element images of different fractions. The physical properties found very close to the range of common soils. Furthermore, the fly ash-based bricks were prepared by the same sample of class F fly ash and the results of compressive strength similar to that of Standard Clay Brick Grade 1 available in the local market of India.

Keywords: fly ash, class F, class C, chemical, physical, SEM, EDS

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Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

Abstract:

When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: degree of coverage, deposition of liquid, nozzle, spraying

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Authors: Huseyin Cetin, Halil Akmese, Sercan Aras, Vahit Aytekin

Abstract:

Economic crisis, terrorism, global crisis and the relations between countries are the factors affecting tourism industry and tourism industry is vulnerable against these factors. In our study, there are two dimensions about Russian crisis. The crisis between Russia and Ukraine and decreased oil prices in global market have been entailed Russian economic crisis. This crisis has induced that the ruble, Russian currency, has depreciated against American dollars and consequently the purchasing power of Russian has weakened. This is the first dimension of our study. Second dimension is a political crisis between Turkey and Russia owing to the fact that the Russian Warcraft was brought down by Turkish army. The aim of this study is to explain the impact of the consequences of Russian crisis on Turkish tourism industry. The study has been limited only Antalya province.

Keywords: economic crisis, Turkey-Russian crisis, Turkey's tourism industry, tourism in Turkey

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Authors: Jacques Wels

Abstract:

Japan has one of the highest average retirement ages within the OCDE and is paving the way to raise the retirement age to 70. However, the Japanese labour market is facing two main issues that can have detrimental effects on health: non-standard employment forms are widespread among the ageing workforce, and poor working conditions can contribute to explain poor health in late career. To assess such a relationship, the study uses data from JSTAR. Using mediation analysis, it particularly looks at the association between job dissatisfaction, employment status, self-perceived health (SPH), and use of health care services. Results show that work quality and employment status are associated with SPH. Contract work has a particularly negative impact and therefore contributes to explain the use of health care services but is not significantly associated with lower job satisfaction levels. SPH is a good predictor of the use of health care services.

Keywords: self-reported health, occupational health, employment, older workers, mediation

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

Abstract:

The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Abe D. Desta

Abstract:

This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

Procedia PDF Downloads 126