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Predicting Woody Plant Diversity as Key Component of Ecosystems: A Case Study in Central Greece
No full textThe Mediterranean basin is a global hotspot of biodiversity. Woody plants are key components of ecosystems. This article explores the environmental impacts on woody plant species richness and diversity in maquis and abandoned olive groves in an important ecological area of central Greece. The results showed that woody plant species richness and diversity had increasing values in maquis compared to abandoned olive groves. According to Principal Component Analysis, woody plant species richness and diversity (Shannon diversity index) were positively correlated with soil organic matter, plant litter, N, P, K, slope and precipitation in maquis. Also, positive correlations among woody plant species richness and diversity, and soil organic matter, and slope were detected in abandoned olive groves. Conclusively, the present study is the first in the area and the results it will be utilized as a decision support tool for sustainability assessment of ecosystems with the help of the information systems
Visualising the Social Media Conversations of a National Information Technology Professional Association
No full textSocial media systems are important for professional associations (PAs), providing new ways for them to interact with their members and stakeholders. Evaluation of the impact of social media is not straightforward. Here text analytics, specifically multidimensional scaling visualisation, is proposed as an approach for the characterisation of the large scale ‘conversations' occurring between an information and communication technology PA and its stakeholders via the Twitter social media system. In the case presented, there was found to be a significant level of congruence between the corresponding visualisations of tweets from the PA, and tweets to/about the PA, although differences were also observed. The new method proposed and piloted here offers a way for organisations to conceptualise, identify, capture and visualise the large-scale, ephemeral, text conversations about themselves on Twitter, and to assist them with key strategic uses of social media
A Survey on the Acceptability of Equivalence-Based Translation Into Yorùbá Language in the Domain of Information and Communication Technology
No full textThis article contains a descriptive survey on the acceptability of equivalence-based translation of the menu of TECNO Android phones into the Yorùbá language, one of the three major languages in Nigeria. Words translated into Yorùbá were categorized into strategies of borrowing, semantic extension and composition and analysed from equivalence effect. In the follow-up survey, information and communication technology experts and general mobile phone users were carefully chosen and consulted for an assessment of the appropriateness of the translation. The study concluded that equivalence, the key term of linguistic translation theories, is still a viable concept in the translation of information and communication technology and equivalence-based translation into Yorùbá will not only promote the language but also contribute to effective communication in a multilingual global village that the world is fast becoming
Factors Related to EFL/ESL Readers' Reading Strategy Use: A Literature Review
No full textThis Article systematically reviews the use of reading strategies among college-level English as a foreign/second language (EFL/ESL) learners and its relationship with two non-cognitive factors: gender and motivation. The author reviews empirical studies published from 2000 to 2017 in order to answer two research questions: (a) What gender disparities exist in college-level EFL/ESL learners' use of reading strategies? (b) How do motivation factors relate to college-level EFL/ESL learners' use of reading strategies? Findings indicate that: (1) motivation factors, including achievement goals, interest in reading, and self-efficacy, positively relate to reading strategy use. (2) gender has an influence on strategy use and female readers show higher use of reading strategies. (3) Interaction effects among factors exist. EFL/ESL learners' strategy use is shaped by multiple factors jointly
Two-step Procedure Based on the Least Squares and Instrumental Variable Methods for Simultaneous Estimation of von Bertalanffy Growth Parameters
No full textAdvanced in the present article is a Two-step procedure designed on the methods of the least squares (LS) and instrumental variable (IV) techniques for simultaneous estimation of the three unknown parameters L∞, K and t0, which represent the individual growth of fish in the von Bertalanffy growth equation. For the purposes of the present analysis, specific MATLAB-based software has been developed through simulated data sets to test the operational workability of the proposed procedure and pinpoint areas of improvement. The resulting parameter estimates have been analyzed on the basis of consecutive comparison (the initial conditions being the same) between the results delivered by the two-step procedure for simultaneous estimation of L∞, K and t0 and the results obtained via the most commonly employed methods for estimating growth parameters; first, use has been made of the Gulland-and-Holt method for estimating the asymptotic length L∞and the curvature parameter K, followed by the von Bertalanffy method for estimation of t0
Identification of Cherry Leaf Disease Infected by Podosphaera Pannosa via Convolutional Neural Network
No full textThe cherry leaves infected by Podosphaera pannosa will suffer powdery mildew, which is a serious disease threatening the cherry production industry. In order to identify the diseased cherry leaves in early stage, the authors formulate the cherry leaf disease infected identification as a classification problem and propose a fully automatic identification method based on convolutional neural network (CNN). The GoogLeNet is used as backbone of the CNN. Then, transferred learning techniques are applied to fine-tune the CNN from pre-trained GoogLeNet on ImageNet dataset. This article compares the proposed method against three traditional machine learning methods i.e., support vector machine (SVM), k-nearest neighbor (KNN) and back propagation (BP) neural network. Quantitative evaluations conducted on a data set of 1,200 images collected by smart phones, demonstrates that the CNN achieves best precise performance in identifying diseased cherry leaves, with the testing accuracy of 99.6%. Thus, a CNN can be used effectively in identifying the diseased cherry leaves
The Direction of Causality Between Supply Chain Excellence and Firm Performance
No full textA widely-accepted measure of supply chain excellence is the Supply Chain Top 25 List published annually by Gartner Research. It evaluates firms from five quality dimensions: return on assets, inventory turns, revenue growth, peer evaluation, and Gartner opinion. However, subjective voting by industrial experts and Gartner consultants are likely to be influenced by financial market variables, such as a firm's market value, alpha, beta, and market return. This article investigates whether the Gartner list is a true reflection of a firm's SCM excellence and how market variables affect the Gartner list, especially its subjective quality dimensions. Correlation and regression analysis show that the Gartner list is largely affected by a firm's market value and alpha, but is not associated with the firm's beta and market return. Moreover, the Gartner list is influenced by a firm's prior market information, but is not capable to predict its future performance
CloudIoT: Towards Seamless and Secure Integration of Cloud Computing With Internet of Things
No full textThe Internet of Things (IoT) is seen as a novel paradigm enabling ubiquitous and pervasive communication of objects with each other and with the physical/virtual world via internet. With the exponential rise of sensor and RFID-based communication, much data is getting generated; which becomes arduous to manage given the constrained power and computation of low-powered devices. To resolve this issue, the integration of Cloud and IoT, also known as CloudIoT, is seen as panacea to create more heterogeneous smart services and handle increasing data demands. In this article, the authors examine and survey literature with a focus on the integration components of CloudIoT and present diverse applications including driving factors for CloudIoT integration. The article also identifies security vulnerabilities implied by the integration of Cloud and IoT and outlines some suggested measures to mitigate the challenge. Finally, the article presents some open issues and challenges providing potential directions for future research in this area
Using Naturalistic Vehicle-Based Data to Predict Distraction and Environmental Demand
No full textThis research utilized vehicle-based measures from a naturalistic driving dataset to detect distraction as indicated by long off-path glances (≥ 2 s) and whether the driver was engaged in a secondary (non-driving) task or not, as well as to estimate motor control difficulty associated with the driving environment (i.e. curvature and poor surface conditions). Advanced driver assistance systems can exploit such driver behavior models to better support the driver and improve safety. Given the temporal nature of vehicle-based measures, Hidden Markov Models (HMMs) were utilized; GPS speed and steering wheel position were used to classify the existence of off-path glances (yes vs. no) and secondary task engagement (yes vs. no); lateral (x-axis) and longitudinal (y-axis) acceleration were used to classify motor control difficulty (lower vs. higher). Best classification accuracies were achieved for identifying cases of long off-path glances and secondary task engagement with both accuracies of 77%
The Impact of Dual-Fairness Concerns Under Different Power: Structures on Green-Supply-Chain Decisions
No full textBy analyzing the impact of different fairness concerns on a green supply chain, this study determines the optimal decisions under different power structures and conducts a comparative analysis of them. The findings of this study are summarized as follows: 1) under the manufacturer-dominated structure, retail price, wholesale price, product greenness, the manufacturer's profit, the total profit of the supply chain, the manufacturer's utility, and the retailer's utility are all negatively correlated with fairness concerns, but positively correlated with the retailer's profit; 2) under the retailer-dominated structure, fairness concerns have no impact on retail price, product greenness, or the total profit of the supply chain, are positively correlated with wholesale price and the manufacturer's profit and utility, and are negatively correlated with the retailer's profit and utility; 3) under the Nash equilibrium structure, fairness concerns have no impact on the green supply chain