Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping in Intellectual Capital Measurement in Creative Industries in East Java

In the context of global competition, competition not only occurs in the world of industry and trade, but also applies to creative businesses or more specifically creative industries which are industries that come from the utilization of individual skills, creativity and talent in creating welfare and employment use. Problems in managing SMEs and creative industries that have not been resolved are intellectual capital issues.One approach used in the assessment and measurement of knowledge assets (intellectual property / assets) is Intellectual Capital which consists of 3 main elements, namely Human Capital, Structural Capital, and Relational Capital. Creative industries are industries that are unique and emphasize creativity, innovation and utilization of individual talents need to get maximum management. The purpose of this study is to find a model, the appropriate components of intellectual capital, and to get a real picture of the rules of Human Capital; Structural Capital and Relational Capital for creative industries in East Java. The sample in this study is the owner / manager / leader of 5 creative industry sub-sectors in 9 cities in East Java (Surabaya, Pasuruan, Probolinggo, Mojokerto, Batu, Malang, Kediri, Blitar, and Madiun) with a sample of 45 as respondents. The analysis technique used in this study is the Spider Plot Diagram.Based on the results of the survey and studies, the aspect of mapping of intellectual capital in 5 (five) creative industry sub-sectors in East Java shows that relational capital is more dominant followed by human capital, and the lowest is structural capital.
Safety Evaluation of Discontinuing Late Night Flash Operations at

Background During late-night flash (LNF) mode (from late night to early morning hours), traffic signals flash yellow for one road (typically, the major road), requiring caution but no stopping, and flash red for the other road (typically, the minor road), requiring drivers to stop and then proceed through the intersection after yielding to the traffic on the major road. The intent of LNF is to reduce energy consumption and delay during periods of low traffic demand. However, in recent years, many agencies have begun replacing LNF with normal phasing operation because of safety concerns.
T h e o p e n - a c c e s s j o u r n a l f o r p h y s i c s New Journal of Physics

Evolving out-of-equilibrium networks have been under intense scrutiny recently. In many real-world settings the number of links added per new node is not constant but depends on the time at which the node is introduced in the system.This simple idea gives rise to the concept of accelerating networks, for which we review an existing definition and—after finding it somewhat constrictive—offer a new definition. The new definition provided here views network acceleration as a time dependent property of a given system as opposed to being a property of the specific algorithm applied to grow the network. The definition also covers both unweighted and weighted networks.As time-stamped network data becomes increasingly available, the proposed measures may be easily applied to such empirical datasets. As a simple case study we apply the concepts to study the evolution of three different instances ofWikipedia, namely, those in English, German, and Japanese, and find that the networks undergo different acceleration regimes in their evolution.
Genetic manipulation and biochemical studies of Saccharomyces Cerevisiae

The brewing properties of an industrial strain of Saccharomyces cerevisiae were investigated by laboratory scale brewing trials in the presence or absence of an uncoupler of oxidative phosphorylation (SX-1). When SX-1 was added the change in specific gravity of brewing wort with respect to time was less, yeast produced less biomass and more ethanol per unit drop in specific gravity than the control. Similar fermentation properties were observed for C2, a haploid laboratory yeast strain with the ability to ferment maltose. Recombinant DNA technology was used to generate a C2 pet mutant, specifically in the ATP12 gene, which encodes a protein essential for mitochondrial ATP synthesis. In brewing trials a comparison of C2 and C2:AATP 12 shows similar results to C2 fermentations in the presence or absence of SX-1 although the effects of SX-1 are more dramatic than with C2:AA TP 12. Together, the results of chemical studies and gene disruption mutagenesis suggest that mitochondrial ATP synthesis affects nuclear functions, although the possibility that results obtained are a consequence of changes to the yeast mitochondrial DNA cannot be eliminated. Problems experienced with yeast DNA transformation protocols lead to the development of a new transformation method that is quicker and more efficient than the standard protocol. Initial studies revealed that DMSO could enhance yeast transformation efficiency, and that the optimal concentration of DMSO used is strain specific. The point at which DMSO was added was found to be important, with maximal transformation efficiency achieved when DMSO was added just before heat shocking. The optimised protocol for S. cerevisiae JRY188 routinely enhanced transformation IS- to 25-fold compared with a control transformation protocol. The osmotic condition was found to be important for DNA uptake as transformation was inhibited if yeast were washed in 1M sorbitol and selected on plates containing the same. Significantly, DMSO enhanced transformation even in the absence of captions, therefore this method may prove useful for yeasts which transform poorly by existing cationic-based yeast transformation methods.
Research in WebGIS Vector Spatial Data Compression Methods

This paper introduces author's work in compress to vector spatial data, which will be transported in Internet/Intranet. On the basis of vector spatial data compression method, which is proposed by, the authors proposes next four innovation:(1)For vector spatial data, not only integer but also short data can be used to replace traditional double or float data. (2)The map data are mapped to a "virtual screen", the formula of "virtual screen" width is: width=DispWidthPixel×MaxEnlargeRatio/stepWidth①. (3) In the mapping process, execute "filter points compression" to pattern points of arc(including polygon's boundary arc and line's arc). In the formula ①, if stepWidth=1, "filter compression" has no loss in precise of map displayed, else stepWidth1, it has precise loss in map displayed. (4) "Long edge adding point" to deal with exception of "Offset compress" to pattern points in arc, which offset in adjacent two points may larger than 127. After these compressions, a map vector data may be compressed to 20% or less.
Oblivious RAM: from theory to practice

Privacy of data storage has long been a central problem in computer security, having direct implications for many Internet-era applications such as storage/computation outsourcing and the Internet of Things (IoT). Yet, the prevailing way we protect our data - through encryption techniques - doesn't protect where we read or write in our data. This additional information, the access pattern, can be used to reverse-engineer proprietary programs as they run, reveal a user's physical location or health information, and more, even if data is correctly encrypted. This thesis studies a cryptographic primitive called Oblivious RAM (ORAM) which provably hides a client's access pattern as seen by untrusted storage. While ORAM is very compelling from a privacy standpoint, it incurs a large performance overhead. In particular, ORAM schemes require the client to continuously shuffle its data in untrusted storage. Early work on ORAM proves that this operation must incur a client-storage bandwidth blowup that is logarithmic in the dataset size, which can translate to > 100x in practice. We address this challenge by developing new tools for constructing ORAMs that allow us to achieve constant bandwidth blowup while requiring only small client storage. A reoccurring theme is to grant untrusted storage the ability to perform untrusted computation on behalf of the client, thereby circumventing lower bound results from prior work. Using these tools, we construct a new ORAM called Ring ORAM, the first small client storage ORAM to achieve constant online bandwidth blowup. At the same time, Ring ORAM matches or improves upon the overall bandwidth of all prior ORAM schemes (given equal client storage), up to constant factors. Next, we more heavily exploit computation at the storage to construct Onion ORAM, the first scheme with constant worst-case and overall bandwidth blowup that does not require heavy weight cryptographic primitives such as fully homomorphic encryption (FHE). Instead, Onion ORAM relies on more efficient additively or somewhat homomorphic encryption schemes. Finally, we demonstrate a working ORAM prototype, built into hardware and taped-out in 32 nm silicon. We have deployed the design as the on-chip memory controller for a 25 core processor. This proves the viability of a single-chip secure processor that can prevent software IP or data theft through a program's access pattern to main memory (having applications to computation outsourcing and IoT). From a technical perspective, this work represents the first ORAM client built into silicon and the first hardware ORAM with small client storage, integrity verification, or encryption units. We propose a number of additional optimizations to improve performance in the hardware setting.
Multi-sensor asynchronous information fusion classification strategy based on coupled HMM

To solve the problem of multi-sensor asynchronous information fusion,this paper proposed a new fusion strategy based on coupled HMM.This approach not only realized time correlation,but also solved the information asynchronism among multi channels.Second,simplified the model structure by confining state numbers and limitting the asynchronism.Furthermore,to realize algorithm of coupled HMM,represented CHMM by a equivalent 2-stream HMM,so traditional HMM algorithm could be directly used on CHMM.The experiments performed on the fusion of speech and lipreading have shown that this strategy achieves better results than early synchronous fusion strategy.
KEY SUCCESS FACTORS FOR ENTREPRENEURS IN THE HEALTHCARE BUSINESS OF THAILAND

Healthcare business in Thailand has been hugely popular among foreigners and retired persons especially. The research presented here focuses on the question “How to become and remain a healthcare entrepreneur? ”. The objectives have been formulated in the following way: 1) to study the success factors of the healthcare business in Thailand, and 2) to analyze the key success factors of entrepreneurs in this field. The population of the study is 6,717 people. The sample group has been 315 people, the stratified random sampling has been applied. The key success factors include education, investment plan, place/location, nurses, supporting staff and strategy. Education has got the highest score - 0.75. Most entrepreneurs have graduated with a bachelor degree or higher. The second comes strategy with the score of 0.636. As this business is quite famous, the competitors apply various strategies to get more customers, both local and international. Information technology and 4Ps are used for campaigns, for example. The lowest score in terms of business success impact got the investment plan with 0.528.
Signal Processing: Image Communication ARTICLE IN PRESS

Data hiding has become increasingly important for many applications, like confidential transmission, video surveillance, military and medical applications. In this paper we present a new approach of 3D object data hiding without changing the position of vertices in the 3D space. The main idea of the proposed method is to find and to synchronize particular areas of the 3D objects used to embed the message. The embedding is carried out by changing the connectivity of edges in the selected areas composed of quadruples. The proposed approach of data hiding in 3D objects is based on minimum spanning tree (MST). This method is lossless in the sense that the positions of the vertices are remaining the same before and after embedding. Moreover the method is blind and does not depend of the order of the data in the files. This approach is very interesting when the 3D objects have been digitalized with high precision.
A Study of the Relationships among Human and Social Capital of Korean Venture Capitalists, Their Investment Strategies, and Performance

The purpose of this study is to investigate how the human and social capitals of Korea venture capitalists influence their investment strategy and performance, considering the mediating role of the investment strategy they use. The database in which Korea Venture Investment Corp. recorded the investment or return that took place in the venture investment fund in which they invested was used. The analysis methods employed include descriptive statistics, correlation analysis, and hierarchical regression analysis with the use of the SPSS statistics package. It was found that venture capitalists with an output function background or with more experience in venture investment pursue the strategy of investing in earlier stage ventures or in more specialized industries. It was also found that the strategy of investing in earlier stage ventures mediates the relationship between output function background or more investment experience that venture capitalist has and their investment performance. For contributions and implications, first, this study pioneered the field of venture capitalist research as the first study to study the relation between investment behavior and investment performance at the individual level of venture capitalist list. Second, if venture capitalists are employed in venture capital, practical implications can be provided through the results of this study.
Real Estate Performance, the Macroeconomy and Leverage

Using U.S. data for 1986-2017, the paper focuses on the impacts of macroeconomic risk factors and leverage on the performance of the various types of real estate exposure (direct, non-listed, and listed). The response of core funds to economic risk factors is akin to that of direct investments; however, real estate fund and direct investment performance are less tightly related as more aggressive (i.e., value-added and opportunistic) strategies are envisaged. Only REIT performance is linked to that of the stock market. Leverage matters as it amplifies the responses to the economic factors and hence investment risk.
Risk, Competition and Cost Efficiency in the Chinese Banking Industry

Using a sample of Chinese commercial banks over the period 2003-2013, this paper tests the interrelationships between credit risk, competition and cost efficiency in the Chinese banking industry under a three-stage least square estimator. The findings suggest that a higher level of competition leads to higher credit risk of Chinese commercial banks and a higher level of efficiency leads to lower credit risk. In addition, it is found that higher level of efficiency results in higher level of competition in the Chinese banking industry and higher levels of credit risk precede an increase in the level of competition. Finally, the results show that Chinese commercial banks with higher levels of credit risk have lower levels of cost efficiency and competition-efficiency hypothesis holds in the Chinese banking industry. The results provide policy implications to the Chinese Government and banking regulatory authorities.
From precision agriculture to Industry 4.0

Purpose Circumstances that are have a significant impact on it. In particular, environmental sustainability related to the increase of worldwide population, and market demand for agricultural products (with consumers more and more aware about cultivation and breeding techniques and interested in healthy and high-quality products) represent two of the key challenges that the agricultural sector is going to face in next years. In such a landscape, technological innovations that can support organizations and entrepreneurs to face these problems become increasingly important, and Industry 4.0 is the most striking example. Indeed, the Industry 4.0 paradigm aims to integrate digital technologies into business processes to raise productivity levels and to develop new business models. Accordingly, digital technologies play a similar role in the precision agriculture domain, and the purpose of this paper is to understand if the technologies at the basis of these two paradigms are the same or not. Design/methodology/approach The present work investigates how the two domains of Industry 4.0 and precision agriculture are connected to one another by analyzing the most used technologies in both the fields in order to highlight common patterns and technological overlaps. To reach such goal, an approach combining manual and automated analysis was developed. Findings The research work generated three main results: a dictionary of precision agriculture technologies including 324 terms; a graph, describing the connections between the technologies composing the dictionary; and a representation of the main technological clusters identified. Originality/value These show how the two domains under analysis are directly connected and describe the most important technologies to leverage when approaching digital transformation processes in the agricultural sector.
Investment Process Resource Provision in the Agricultural Sector

Based on the statistical data and analytical documents analysis, the purpose in this paper is to develop a methodology for determining the directions of the investment process regulation at various stages of its implementation and the optimal investment resources allocation. According to the purpose of the research, the following objects are defined in this paper: to explore the current state of the investment process development in the agricultural sector of the Russian Federation and the Republic of Crimea; to identify the goals for the investment process development in the agricultural sector of the Republic of Crimea in accordance with the main state program documents; to develop a methodology for determining the financial management centers at various stages of the investment process implementation; to develop a methodology for determining the interrelated modules that affect the modeled management system for the investment process adaptability in the agricultural sector; to identify the elements of the block system for managing the resource support of the investment process.
Designing Efficient Topic-Driven Web Crawlers

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Collaborative Coding Interfaces on the Web

The recent developments in Web technologies, including full‐stack reactive application frameworks, peer‐to‐peer communication and client‐side audiovisual APIs have introduced the possibility of creative collaboration in a number of contexts. Such technologies have the potential to transform the way Internet users interact with code. This paper introduces a theoretical and technical methodology for developing collaborative coding interfaces as web applications, tackling the issues of interactive rendering, user‐platform interaction and collaboration. A number of existing interactive programming environments are reviewed, followed by a technical description and evaluation of CodeCircle, a collaborative coding web platform developed at Goldsmiths, University of London.
A Preliminary Study of Fintech Industry: A Two-Stage Clustering Analysis for Customer Segmentation in the B2B Setting

ABSTRACT This practitioner note proposes a new approach considering two-stage clustering and LRFMP model (Length, Recency, Frequency, Monetary and Periodicity) simultaneously for customer segmentation and behavior analysis and applies it among the Iranian Fintech companies. In this practitioner note, the K-means clustering algorithm and LRFMP model are combined in the customer segmentation process. After initial clustering, for a better understanding of valuable customers, additional clustering is implemented in segments that needed further investigation. This approach contributes to a better interpretation of different customer segments. Customer segments, consisting of 23524 business customers are analysed based on their characteristics and appropriate strategies are recommended accordingly. The first stage clustering result shows that customers are best segmented into four groups. The first and fourth segments are clustered again and the final 11 groups of customers are determined. This note provides a systematic and practical approach for researchers and practitioners for segmentation, interpretation, and targeting of customers especially in the B2B setting and the Fintech industry and helps managers to make effective marketing strategies and enhance customer relationship and marketing intelligence.