scholarly journals A Study on Intelligent Technology Valuation System: Introduction of KIBO Patent Appraisal System II

2021 ◽  
Vol 13 (22) ◽  
pp. 12666
Author(s):  
Min-Seung Kim ◽  
Chan-Ho Lee ◽  
Ji-Hye Choi ◽  
Yong-Ju Jang ◽  
Jeong-Hee Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
New Technologies ◽  
Small And Medium Enterprises ◽  
Economic Value ◽  
Valuation Theory ◽  
Appraisal System ◽  
Discounted Cash Flow ◽  
Economic Values ◽  
Economic Trends ◽  
Intelligent Technology

Technology finance, which has attracted worldwide attention for the successful business development of small-and-medium enterprises (SMEs) or start-ups, has advanced an innovation or stagnation way-out resolution strategy for companies in line with the low-growth economic trends. Although the development of new technologies and the establishment of active R&D and commercialization strategies are essential factors in a company’s management sustainability, the activation of the technology market in practice is still in progress for its golden age. In this study, to promote a technology transfer-based company’s growth and to run technology-based various financial support activities, we develop and propose a new intelligent, deep learning-based technology valuation system that enables technology holders to estimate the economic values of their innovative technologies and further to establish a firm’s commercialization strategy. For the last years, the KIBO Patent Appraisal System (KPAS-II) herein proposed has been advanced by KIBO as a web-based, artificial intelligence (AI) and evaluation data applications valuation system that automatically calculates and estimates a technology’s feasible economic value by utilizing both the intrinsic and extrinsic index information of a patent and the commercialization entity’s business capabilities, and by applying to the discounted cash flow (DCF) method in valuation theory, and finally integrating with deep learning results based on the in-advance previously established patent DB and the financial DB. The KPAS-II proposed in this study can be said to have dramatically overcome the long-term preparation period and high levels of R&D and commercialization costs in terms of the limitations that the existing technology valuation method possesses by enhancing the reliability of approximate economic values from the deep learning results based on financial data and completed valuation data. In addition, it is expected that technology marketing coordinators, researchers, and non-specialty business agents, not limited to valuation experts, can easily estimate the economic values of their patents or technologies, and they can be actively utilized in a technology-based company’s decision-making and technologically dependent financial activities.

scholarly journals Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery—A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 575
Author(s):  
Jelena Ochs ◽  
Ferdinand Biermann ◽  
Tobias Piotrowski ◽  
Frederik Erkens ◽  
Bastian Nießing ◽  
...  
Keyword(s):  
Stem Cells ◽  
Deep Learning ◽  
High Throughput ◽  
High Speed ◽  
New Technologies ◽  
Human Mesenchymal Stem Cells ◽  
Simulation Software ◽  
System Capacity ◽  
Small Scale ◽  
Production Environment

Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.

Assessing the Accuracy of Fault Interpretation using Machine Learning Techniques when Risking Faults for CO2 Storage Site Assessment

2021 ◽  
pp. 1-55
Author(s):  
Emma A. H. Michie ◽  
Behzad Alaei ◽  
Alvar Braathen
Keyword(s):  
Deep Learning ◽  
New Technologies ◽  
Co2 Storage ◽  
Fault Reactivation ◽  
Machine Learning Techniques ◽  
Close Similarity ◽  
Storage Site ◽  
Site Assessment ◽  
Learning Techniques ◽  
Fault Interpretation

Generating an accurate model of the subsurface for the purpose of assessing the feasibility of a CO2 storage site is crucial. In particular, how faults are interpreted is likely to influence the predicted capacity and integrity of the reservoir; whether this is through identifying high risk areas along the fault, where fluid is likely to flow across the fault, or by assessing the reactivation potential of the fault with increased pressure, causing fluid to flow up the fault. New technologies allow users to interpret faults effortlessly, and in much quicker time, utilizing methods such as Deep Learning. These Deep Learning techniques use knowledge from Neural Networks to allow end-users to compute areas where faults are likely to occur. Although these new technologies may be attractive due to reduced interpretation time, it is important to understand the inherent uncertainties in their ability to predict accurate fault geometries. Here, we compare Deep Learning fault interpretation versus manual fault interpretation, and can see distinct differences to those faults where significant ambiguity exists due to poor seismic resolution at the fault; we observe an increased irregularity when Deep Learning methods are used over conventional manual interpretation. This can result in significant differences between the resulting analyses, such as fault reactivation potential. Conversely, we observe that well-imaged faults show a close similarity between the resulting fault surfaces when both Deep Learning and manual fault interpretation methods are employed, and hence we also observe a close similarity between any attributes and fault analyses made.

The Australian sheep industry - undergoing transformation

2010 ◽  
Vol 50 (12) ◽  
pp. 991 ◽  
Author(s):  
J. B. Rowe
Keyword(s):  
New Technologies ◽  
Economic Value ◽  
Genetic Selection ◽  
High Rate ◽  
Meat Production ◽  
Sheep Industry ◽  
Sheep Meat ◽  
Productivity Gain ◽  
Australian Sheep ◽  
Meat Market

Changes in the sheep industry over the last 20 years represent a trend that is unlikely to be reversed. The farm gate value of wool production has decreased from over $6 billion to ~$2.5 billion and the value of sheep meat has increased from $0.5 to $2.2 billion. Wool and meat are now on an equal footing in terms of the economic value of each sector of the industry. Future profitability of both wool and sheep meat production depends on achieving a high rate of productivity gain and improving quality attributes valued by consumers. Wool and sheep meat cannot compete on price or volume with synthetics and cotton in the textile market or with chicken and pork in the meat market. Differentiation based on quality and consistency needs to be measurable and clearly understood by consumers. The combination of genetic selection and good management can deliver improved productivity gain. Skills development and training will be essential for the industry to fully utilise available knowledge and new technologies.

scholarly journals Economic and non-economic values and objectives in the EU’s international trade: Normative tensions, actors and processes

2019 ◽  
Author(s):  
Urszula Jaremba ◽  
Machiko Kanetake ◽  
Ingrid Koning
Keyword(s):  
Sustainable Development ◽  
Human Rights ◽  
New Technologies ◽  
Economic Values ◽  
Trade Relations ◽  
Trade Law ◽  
Law And Policy ◽  
Recent Developments ◽  
The One ◽  
The Impact

This Europe and the World: A law review special issue comprises selected papers presented at a RENFORCE workshop on the theme of tensions between the EU’s trade and non-economic values, held at Utrecht University in November 2017. The symposium addresses normative dilemmas underlying the EU’s trade law and policy. Normative dilemmas subsist between, on the one hand, the EU’s basic pursuit of its commercial interests and trade liberalization, and, on the other hand, the EU’s mandate to promote and safeguard a number of non-economic values, including human rights and sustainable development. The journal symposium aims to unveil normative tensions existing in the EU’s trade and investment policy, and understand some of the key actors and processes through which normative tensions are created and also mitigated. While the tensions between economic and non-economic values in the EU’s trade law and policy have been extensively discussed in literature, the present symposium highlights some of the recent developments in the EU’s trade relations, analyses not only human rights but also sustainable development, and examines the impact of new technologies.

scholarly journals A Brief Overview of the IPO Valuation Methods

2020 ◽  
Vol 15 (12) ◽  
pp. 41
Author(s):  
Olga Ferraro
Keyword(s):  
Cash Flow ◽  
Initial Public Offering ◽  
Professional Practice ◽  
Economic Value ◽  
Value Added ◽  
Economic Value Added ◽  
Discounted Cash Flow ◽  
Business Valuation ◽  
Valuation Methods ◽  
Public Offering

The method adopted for pricing in an Initial Public Offering is a key issue in the studies on business valuation. In particular, various researches sought to verify which valuation methodologies are preferable in the context of an initial public offering. The review of the main literature shows that Discounted Cash Flow, Market Multiples, Dividend Discount Model and, even if just to some degree, Economic Value Added are the most popular methodologies in the valuation practice. The comparison among different valuation methods, proposed in the literature and variously applied in national and international practices, reveals the necessity to pay more attention to valuation mechanisms that drive the pricing of the shares to be listed. The topic is linked to the ever more pertinent debate on the use of different methods in professional practice: financial experts and analysts tend, in fact, to compare results according to different estimates.

scholarly journals Valuation of agrifood SMEs. Lessons to be learnt from the stock market

2018 ◽  
Vol 15 (4) ◽  
pp. e0118 ◽  
Author(s):  
Raül Vidal ◽  
Javier Ribal
Keyword(s):  
Stock Market ◽  
Capital Structure ◽  
Small And Medium Enterprises ◽  
Cost Of Equity ◽  
Discounted Cash Flow ◽  
Return On Equity ◽  
Valuation Process ◽  
Two Parameters ◽  
Medium Enterprises ◽  
The Capital Structure

The European agrifood industry is mostly characterized by small and medium enterprises (SMEs); as in 2013, SMEs represented 99.13% of the total number of companies. The valuation of SMEs not listed in any stock market is a complex task since there is not enough information on comparable transactions. When applying discounted cash flow (DCF) models to value private agrifood companies, the capital structure and the cost of equity are two key parameters to be determined. The implications of these parameters in the value of the enterprise are not clear inasmuch as it is not possible to carry out a contrast due, precisely, to the lack of comparables. The main goal of this study is to determine the biases that those two parameters can introduce into the valuation process of an agrifood company. We have used the stock market as a framework wherein to apply a simple fundamental model to the companies of the European food industry in order to obtain three valuation multiples. By means of two bootstrap approaches, the bias induced in the multiples has been assessed for every year from 2002-2013. Results show that the use of the return on equity as cost of equity tends to undervaluation; the use of capital asset pricing model (CAPM) tends to a slight overvaluation, whereas using the total beta induces an undervaluation bias. Moreover, the capital structure shows little influence on the valuation multiples. The conclusions drawn from this paper can be useful for managers and shareholders of privately-held agrifood companies.

scholarly journals Pemanfaatan Pelepah Pisang Menjadi Produk Inovatif sebagai Upaya Peningkatan Pendapatan Ekonomi Keluarga di Desa Jamberejo Kecamatan Kedungadem Kabupaten Bojonegoro

2019 ◽  
Vol 3 (1) ◽  
pp. 21-31
Author(s):  
Nur Laila Rahmawati ◽  
Indah Fajrotuz Zahro ◽  
Asnawi ◽  
Nurul Fitriandari ◽  
Eryul Mufidah
Keyword(s):  
Higher Education ◽  
Small And Medium Enterprises ◽  
Economic Value ◽  
Business Community ◽  
Participatory Action ◽  
Economic Competition ◽  
Social Community ◽  
The Social ◽  
Asean Countries ◽  
Medium Enterprises

The economic challenge in the era of ASEAN Economic Community (MEA) is economic competition in the ASEAN countries. Consequently, efforts to improve Small and Medium Enterprises (SMEs) must be sustainable and should be done by synergizing among the social community, higher education, and the business community. To implement it, Jamberejo village of Kedungadem Sub-district, Bojonegoro developed assets that the social community has, that is banana bark which was able to be used as crafts that have economic value. By using Participatory Action Research (PAR) method, 57 women and higher education were invited to make crafts from banana bark to be used as a home industry business. Based on 6 samples of product, the business got a profit of Rp. 2,100,000. Return of Investment (ROI) is about 2.2 months. Then the average income level of the Jamberejo people has increased by 42.9% or equivalent to Rp. 900,000 per month. It happened after they got a mentoring program for the innovation of banana bark

Green Spaces of the Metropolitan Area of Guadalajara

2019 ◽  
pp. 151-179
Author(s):  
Roberto Jiménez ◽  
Paula Lourdes Guerrero Rodríguez ◽  
Rogelio Rivera Fernández
Keyword(s):  
Metropolitan Area ◽  
New Technologies ◽  
Economic Value ◽  
Green Spaces ◽  
Metropolitan Region ◽  
Public Parks ◽  
Urban Green Spaces ◽  
Natural Systems ◽  
Green Areas ◽  
Social Environmental

The analysis of some systems of green areas and public parks of the metropolitan area of Guadalajara, other cities of our country Mexico and Latin America, shows common problems such as the deficit of urban green spaces, insecurity, unemployment, and uncertainty with a social exclusion in these areas of stress. Likewise, the lack of economic value of the services provided by such natural systems as recreation is added. Together they are important factors in the allocation of territories destined to this use with respect to others that generate Urban speculation. Therefore, it is proposed to develop a typology of green areas appropriate to the needs of the metropolitan region. It will facilitate the production of inventories that estimate indicators of territorial cohesion, governance, economic profitability, social, environmental quality and innovation, as well as incorporating new technologies that improve geographic information systems and internet media that support management.

FinTech Adoption in China

2021 ◽  
pp. 166-173
Author(s):  
Gagan Kukreja
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Financial Services ◽  
New Technologies ◽  
Large Population ◽  
Financial Inclusion ◽  
High Penetration ◽  
Digital Payments ◽  
Almost All

Almost all financial services (especially digital payments) in China are affected by new innovations and technologies. New technologies such as blockchain, artificial intelligence, machine learning, deep learning, and data analytics have immensely influenced all most all aspects of financial services such as deposits, transactions, billings, remittances, credits (B2B and P2P), underwriting, insurance, and so on. Fintech companies are enabling larger financial inclusion, changing in lifestyle and expenditure behavior, better and fast financial services, and lots more. This chapter covers the development, opportunities, and challenges of financial sectors because of new technologies in China. This chapter throws the light on opportunities that emerged because of the large population of 1.4 billion people, high penetration, and access to the latest and affordable technology, affordable cost of smartphones, and government policies and regulations. Lastly, this chapter portrays the untapped potentials of Fintech in China.

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