Dramatic Growth In Recent Years Research Articles

Can a Holistic View Facilitate the Development of Intelligent Traditional Chinese Medicine? A Survey

Intelligent traditional Chinese medicine (ITCM) is an emerging interdisciplinary subject. It aims to efficiently and precisely promote the prevention and treatment of diseases and health management in Chinese medicine clinical practice via the combination of traditional Chinese medicine (TCM) fundamentals and artificial intelligence technologies. Presently, it is experiencing dramatic growth in recent years. On the one hand, a holistic view, as a crucial philosophy in the theory of TCM, will be guiding the development of ITCM. On the other hand, a comprehensive discussion of the benefits of such a holistic view of ITCM is lacking. To this end, we conduct this survey by introducing the named holistic view first. Then, adaptive learning and field theory will be presented and discussed with respect to their application in ITCM. Ethical issues of ITCM will then be taken into account by human-centered TCM and potentials based on affective computing of ITCM. In addition, we give our opinions and insights on the challenges and open issues regarding the future of ITCM. We hope that this survey article can be a good guide for experts in the relevant fields.

Radiomics: A Primer for Breast Radiologists.

Radiomics has a long-standing history in breast imaging with computer-aided detection (CAD) for screening mammography developed in the late 20th century. Although conventional CAD had widespread adoption, the clinical benefits for experienced breast radiologists were debatable due to high false-positive marks and subsequent increased recall rates. The dramatic growth in recent years of artificial intelligence-based analysis, including machine learning and deep learning, has provided numerous opportunities for improved modern radiomics work in breast imaging. There has been extensive radiomics work in mammography, digital breast tomosynthesis, MRI, ultrasound, PET-CT, and combined multimodality imaging. Specific radiomics outcomes of interest have been diverse, including CAD, prediction of response to neoadjuvant therapy, lesion classification, and survival, among other outcomes. Additionally, the radiogenomics subfield that correlates radiomics features with genetics has been very proliferative, in parallel with the clinical validation of breast cancer molecular subtypes and gene expression assays. Despite the promise of radiomics, there are important challenges related to image normalization, limited large unbiased data sets, and lack of external validation. Much of the radiomics work to date has been exploratory using single-institution retrospective series for analysis, but several promising lines of investigation have made the leap to clinical practice with commercially available products. As a result, breast radiologists will increasingly be incorporating radiomics-based tools into their daily practice in the near future. Therefore, breast radiologists must have a broad understanding of the scope, applications, and limitations of radiomics work.

Evolution of fungal community associated with ready-to-eat pineapple during storage under different temperature conditions

The international market of fresh-cut products has witnessed dramatic growth in recent years, stimulated by consumer's demand for healthy, nutritious and convenient foods. One of the main challenging issues for the quality and safety of these products is the potential microbial spoilage that can significantly reduce their shelf-life. The complete identification of fresh-cut product microbiota together with the evaluation of environmental factors impact on microbial composition is of primary importance. We therefore assessed the fungal communities associated with the spoilage of ready-to-eat (RTE) pineapple using a metagenetic amplicon sequencing approach, based on the ITS2 region. Our results revealed a significant variability on fungal species composition between the different batches of RTE pineapple. The initial microbiota composition was the main influencing factor and determined the progress of spoilage. Temperature and storage time were the secondary factors influencing spoilage and their impact was depending on the initial prevalent fungal species, which showed different responses to the various modifications. Our results strongly suggest that further large-scale sampling of RTE pineapple production should be conducted in order to assess the full biodiversity range of fungal community involved in the spoilage process and for unravelling the impact of important environmental factors shaping the initial microbiota.

Manufacturer’s Entry in the Product-Sharing Market

Problem definition : Mobile communications technologies and online platforms have enabled large-scale consumer-to-consumer (C2C) sharing of their underutilized products. This paper studies a manufacturer’s optimal entry strategy in the product-sharing market and the economic implications of its entry. Academic/practical relevance : Sharing of products or services among consumers has experienced dramatic growth in recent years. The impact of C2C sharing on traditional firms can be very significant. In response to C2C product sharing, many manufacturers (e.g., General Motors and BMW) have entered the product-sharing market to provide business-to-consumer (B2C) rental services in addition to outright sales to consumers. Methodology : We employ a game-theoretic analytical model for our analysis. Results : Our analysis shows that when C2C sharing has a low transaction cost and the manufacturer’s marginal cost of production is not very high, the manufacturer will find it not optimal to offer its own rental services to consumers. In contrast, when the C2C sharing transaction cost is high or the manufacturer’s marginal cost of production is high, the manufacturer should offer enough units of the products for rental to squeeze out C2C sharing (in expectation). When the C2C-sharing transaction cost and the manufacturer’s marginal cost are both in the middle ranges, the manufacturer’s rental services and the C2C sharing will coexist, in which case the manufacturer’s entry in the sharing market may reduce the total number of units of the product in the whole market, but increase the consumer surplus and the social welfare. This reduced number of products due to the manufacturer’s B2C rental service also suggests less environmental impact from production. Managerial implications : The production cost and the C2C sharing transaction cost play critical roles in determining the manufacturer’s optimal quantity to use for its B2C rental services and the equilibrium outcome. In some situations, the manufacturer’s entry in the sharing market provides not only economic benefits to the firm and consumers, but also environmental benefits to the society as a whole.

Cost Optimal Data Center Servers: A Voltage Scaling Approach

Data centers have experienced dramatic growth in recent years in order to meet the ever-increasing demand for computing. As a result, minimizing the electrical cost to operate data centers has become a crucial issue. In this paper, we observe that electricity prices change over time, and that we can take advantage of periods with low prices by scaling up processor speeds to perform more work, while scaling down speeds during high price periods to reduce cost. We apply this observation to several settings. First, we consider an offline setting which assumes future electricity prices are given, and propose an efficient algorithm for optimally scaling a processor's speed in order to minimize the total electrical cost for completing a task by a deadline. We then consider a more realistic stochastic setting in which future prices are not known, but vary according to a Markov model. We present another efficient algorithm for minimizing the expected cost to meet a deadline. We performed a number of experiments using real electricity price traces to test the performance of our algorithms. We show that our stochastic algorithm is light-weight and relies only on easily obtainable price data, but that it achieves excellent performance, with only a 1 percent cost difference on average from the optimal offline algorithm. In addition, the stochastic algorithm significantly reduced costs compared to several candidate algorithms.

Digital cultural colonialism: measuring bias in aggregated digitized content held in Google Arts and Culture

AbstractIn February 2011, Google launched its Google Art Project, now known as Google Arts and Culture (GA&C), that currently hosts approximately six million high-resolution images of artworks from around the world, with an objective to make culture more accessible. We demonstrate that GA&C has experienced dramatic growth in recent years and includes artworks for almost every country from the UN member list. However, we document a noticeable lack of balance in the aggregator, with some countries and institutions being prioritized, and a major proportion of the holdings featuring content that resides in the USA. Moreover, after examining Russian and French collections, we see the dominance of artworks from their capital cities in GA&C, while art from provinces is clearly underrepresented. Finally, we find a dominance of art from the 20th century with some emphasis on artworks demonstrating a break in canon or ‘otherness’ of non-Western countries. The discrepancies that we observe give evidence to support previously posited ideas of digital cultural colonialism. This may be due to a lack of data transparency or availability of previously digitized content in the countries with a lower representation in the portal, or an unintentional digital amplification of conventional traditions of art collection and interpretation that dominate museum displays in larger Western cities. We call for explicit statement by platforms on their collection and selection criteria and the need for researchers to understand the biases emerging from aggregated digitized content.

Machine learning strategies for high-entropy alloys

The study of high-entropy (HE) alloys has seen dramatic growth in recent years as, in some cases, these systems can exhibit exceptional properties, including enhanced oxidation resistance, superior mechanical properties, and desirable magnetic properties. The identification of promising HE alloys is, however, extremely challenging due to the extraordinarily large number of distinct systems that may be fabricated from the available palette of elements. For this reason, machine learning strategies have been employed to reduce the size of the associated chemistry/composition space. In this review, we outline several computational strategies that have led to the identification of useful alloys and discuss the relative merits and shortcomings of these approaches. We also present short tutorials illustrating the use of selected computational approaches to HE characterization and design.

RETRACTED: Optimization of Communication Network Fault Identification Based on NB-IoT

The Internet of Things (IoT) has developed an industrial and medical application in dramatic growth in recent years. Narrow Band-Internet of Things (NB-IoT) is a wireless communication and low power wide area technology based on new IoT devices and enables various services to grow. NB-IoT communication significantly increases the power consumption of user equipment, computer capacity, and spectrum performance. Network communication is complex, and the amount of information these networks have made it extremely difficult to manage the transmissions. Since the communication network failure is inevitable, rapid detection, identification, and recovery are the most reliable; it is essential to the high-speed operation. Narrow Band-IoT (NB-IoT) networking technology has proposed the idea of detecting network communication fault. The NB-IoT technique can help save a lot of energy by significantly reducing the number of retransmission required. The proposed technology proves that this research is a powerful proposition for achieving the ideal energy potential. Performance analysis and simulation results show that the detection mechanism can improve transmission efficiency and effectively reduce network communication failures power consumption.

Manufacturer's Entry in the Product-Sharing Market

Problem Definition：Mobile communications technologies and online platforms have enabled large-scale consumer-to-consumer (C2C) sharing of their under-utilized products. This paper studies a manufacturer’s optimal entry strategy in the product-sharing market and the economic implications of its entry. Academic/Practical Relevance: Sharing of products or services among consumers has experienced dramatic growth in recent years. The impact of C2C sharing on traditional firms can be very significant. In response to C2C product sharing, many manufacturers (e.g., General Motors, BMW) have entered the product-sharing market to provide business-to-consumer (B2C) rental services in addition to outright sales to consumers. Methodology: We employ a game-theoretic analytical model for our analysis. Results: Our analysis shows that when C2C sharing has a low transaction cost and the manufacturer’s marginal cost of production is not very high, the manufacturer will find it not optimal to offer its own rental services to consumers. In contrast, when the C2C sharing transaction cost is high or the manufacturer’s marginal cost of production is high, the manufacturer should offer enough units of the products for rental to squeeze out C2C sharing (in expectation). When the C2C sharing transaction cost and the manufacturer’s marginal cost are both in the middle ranges, the manufacturer’s rental services and the C2C sharing will coexist, in which case the manufacturer’s entry in the sharing market may reduce the total number of units of the product in the whole market but increase the consumer surplus and the social welfare. This reduced number of products due to the manufacturer’s B2C rental service also suggests less environmental impact from production. Managerial Implications: The production cost and the C2C sharing transaction cost play critical roles in determining the manufacturer’s optimal quantity to use for its B2C rental services and the equilibrium outcome. In some situations, the manufacturer’s entry in the sharing market provides not only economic benefits to the firm and consumers but also environmental benefits to the society as a whole.

Electricity Cost Minimization for Interruptible Workload in Datacenter Servers

Datacenters have experienced dramatic growth in recent years, and the cost for powering them has become a significant problem. This paper proposes methods to minimize the energy cost for performing a task on a datacenter server before a deadline. We observe that energy prices fluctuate over time, and schedule the task to execute in periods of relatively low cost, despite not having knowledge of future costs during the execution. This problem is studied in several models, starting with an online setting where electricity prices can change arbitrarily. A $\sqrt{\varphi }$ φ -competitive algorithm is proposed, where $\varphi$ φ is the ratio between the maximum and minimum electricity prices, and this algorithm is also shown to be optimal by proving a matching lower bound. Next, we consider a stochastic setting in which prices vary in a Markovian fashion and propose an optimal algorithm based on dynamic programming. We then study the performance of our algorithms in practice using prices derived from real world data. The results show that the stochastic algorithm is very effective, and achieves cost that is within 3.4 percent of the optimum. Moreover, it performs well compared to several heuristics used in practice.

Evaluation Methods in Process-Aware Information Systems Research with a Perspective on Human Orientation

Research on process-aware information systems (PAIS) has experienced a dramatic growth in recent years. Lately, a particular increase of empirical studies and focus on human oriented research questions could be observed, leading to an expansion of applied evaluation methods in PAIS research. At the same time, it can be observed that evaluation methods are not always applied in a systematic manner and related terminology is at times used in an ambiguous way. Hence, the paper aims at investigating evaluation methods that are typically employed in PAIS research with a special focus on human orientation. The applied methodology includes a literature review, an expert survey, and a focus group. The authors present their findings as a collection of typical evaluation methods and the related PAIS artifacts. They highlight which evaluation methods are currently used and which evaluation methods could be of interest for future PAIS research efforts.

Extraction of Terminology and Phraseology Towards the Design of Instructional Resources for Legal Translation

Computer-assisted translation (CAT) technology has experienced a dramatic growth in recent years and its use has spread to specialties like legal translation, not so much for their performance and productivity but for their quality control functions. The aim of this work is to propose a protocol to extract frequent terminology and phraseology in order to increase CAT tools performance, improve quality control features and help to produce resources with teaching purposes in the translation of contracts.

Developmental progress and current status of the Animal QTLdb

The Animal QTL Database (QTLdb; http://www.animalgenome.org/QTLdb) has undergone dramatic growth in recent years in terms of new data curated, data downloads and new functions and tools. We have focused our development efforts to cope with challenges arising from rapid growth of newly published data and end users’ data demands, and to optimize data retrieval and analysis to facilitate users’ research. Evidenced by the 27 releases in the past 11 years, the growth of the QTLdb has been phenomenal. Here we report our recent progress which is highlighted by addition of one new species, four new data types, four new user tools, a new API tool set, numerous new functions and capabilities added to the curator tool set, expansion of our data alliance partners and more than 20 other improvements. In this paper we present a summary of our progress to date and an outlook regarding future directions.

PENTECOSTAL CHRISTIANITY AND CHURCH-STATE RELATIONS IN CHINA: THE CASE OF THE TRUE JESUS CHURCH MOVEMENT

In-depth study of the True Jesus Church, a completely indigenous Pentecostal Chinese religious group that has experienced dramatic growth in recent years, reveals the complex and diverse reality of variation in church-state relationships in China. The True Jesus Church is distinct in that, in many regions, it is not a part of the overall “Three-Self Patriotic Movement” structure, nor does it belong to the “house church” movement. In China today, a society where an overarching rule-of-law system is missing, fates of religious congregations often lie in the hands of local bureaucrats. The quality of relationships—the “Guanxi”— with the local government often determines the degree of freedom for religious practices.

URBAN GROWTH IN THE NATIONAL CAPITAL REGION OF INDIA: TESTING THE DIFFERENTIAL URBANISATION MODEL

ABSTRACTRecent research on the differential urbanisation (DU) model has examined the successive stages of concentration and dispersal of population in a set of hierarchy of cities at the national scale in many countries. Delhi, the capital city of India, and its adjoining areas, have experienced dramatic growth in recent years. In order to mitigate the adverse impact of growth, a National Capital Region (NCR) was delineated for co‐ordinating growth related activities within the region. Based on the postulates of the DU model, we explore the urban structural pattern of the NCR over the past three decades. Our empirical findings of the growth of cities and towns within the core and periphery of the NCR support the usefulness of the DU approach in assessing the urban regional development patterns. Urbanisation trends, as observed in the hierarchical restructuring of population would have implications for regional development policies and programmes.

Information Systems outsourcing: An empirical study of success factors

Although Information Systems Outsourcing has experienced a dramatic growth in recent years, there is a lack of success in many of these contracts, which makes it necessary to study the factors determining that success. The present paper proposes a set of key factors to achieve IS outsourcing success. It also establishes a number of measures meant to assess the degree of success reached by firms at outsourcing. We have validated both things (the proposed success factors and the factors to measure success) through a survey carried out among the Information Systems managers of the largest Spanish firms. The perceived benefits of outsourcing can be reduced to three types: technological, strategic and economic. Strategic motivations stand out as the most important ones in this study. This paper not only identifies the most important outsourcing success factors, from the client’s point of view, but also studies the evolution of these success factors during the last few years in the Spanish context, and offers a number of measures to assess the degree of success obtained by firms with IS outsourcing. So the model could be useful both for teaching and for the industry practice.

Stimulation or Saturation?

The European low-cost carriers have enjoyed dramatic growth in recent years and have substantially altered the network of short-haul air services provided. Demand for low-cost services has proved more volatile than in the United States, however, and there are incipient signs that the carriers’ ability to stimulate traffic is diminishing. Many new entrants have jumped on the bandwagon, and the traditional airlines have started to fight back. An analysis of different routes from London shows that the low-cost carriers have been much more successful in some markets than others. The major airlines remain dominant in sectors involving their principal hub airports whereas thin routes within northern Europe have shown little growth from low-cost carrier entry, some remaining the preserve of regional carriers. The low-cost airlines have performed best on dense routes not involving major airports and leisure routes between northern and southern Europe. Competitive strategies that are examined include the ability of low-cost airlines to attract traffic to secondary and regional airports that were previously underutilized. It is shown that on some routes from major cities, secondary airports are now handling a majority of the local passengers. However, the ability of airports to grow beyond the traffic potential of their own local catchment area diminishes as more locations gain low-cost service. Although some untapped opportunities may remain in countries such as France and for services with smaller aircraft, new routes are tending to dilute existing demand. The focus is therefore likely to turn to more head-to-head competition in the denser markets.

RESEARCH NOTE: THE RELATIONSHIP BETWEEN VACATION CLUB PROGRAM COMPONENTS AND OWNER SATISFACTION: THE CASE OF THE VACATION OWNERSHIP INDUSTRY

The timeshare/vacation ownership segment of the hospitality industry has experienced dramatic growth in recent years. As the segment matures and evolves, the need for consumer education of the components of the product continues to increase. Timeshare owners from one of the leading timeshare companies in the US were surveyed to determine their consumers’ level of product knowledge of 12 different components of the timeshare product, varying from maintenance fees and membership dues to the concept of borrowing and depositing points. The owners were also surveyed to determine their satisfaction level with the timeshare product offerings. Results indicate that the higher the level of knowledge that the owners have of the timeshare product the greater their satisfaction level. The results show the need for continued education of the timeshare owner for lasting satisfaction with their ownership.

Techniques for Interacting with Large Information Spaces on Small-Screen Displays

The dramatic growth in recent years of computing devices with small display surfaces (e.g., PDAs, WAP phones, handheld computers) has spawned the need to consider new interaction methodologies that will allow users to interact with information spaces that might require more space than the display can provide. This paper describes potential solutions to allow users to interact easily and intuitively with large information spaces when presented on a small screen. We used a human-centered iterative design approach consisting of knowledge elicitation tasks, user feedback sessions, and concept development to identify two primary interaction methodologies: Dynamic Information Magnification (DIM) and Dynamic Information Labeling (DIL). DIM is a way for the user to enhance relevant portions of an information space through magnification functions while DIL is a way to enhance information through smart highlighting and labeling. These two techniques were applied to complex flight performance charts as part of an ONR-funded program that is focusing on the development of an electronic checklist and procedure manual. Early findings suggest that the Dynamic Information Labeling concept shows the most promise for the particular domain to which this technique was applied. Concept descriptions, informal user feedback, and implications of interaction methodologies for use with large information spaces on small-screen displays are described.