Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of IT-enabled Supply Chain Process Integration on Firm’s Operational Performance

In the context of supply chain integration (SCI), information technology (IT) is regarded as a backbone of process integration within a firm and between partnering organizations. The literature reports mixed results on relationship between IT and firm’s performance. We propose a model that constitutes the relationship between IT capability and flexibility and delivery performance, mediated by supply chain integration, internal and external with suppliers and customers. The empirical study with 117 Japanese manufacturing firms reveals that flexibility performance is improved when both supplier integration and customer integration are supported by supply chain application capability. Delivery performance is enhanced when internal integration is backed with strong cross-functional application capability, along with customer integration supported by supply chain application capability. This study makes significant contributions to the IT and SCI literature by investigating the effect of IT capability on flexibility and delivery performance through internal and external integration, providing managerial implications.
What ’ s Spurious , What ’ s Real ? Measuring the Productivity Impacts of ICT at the Firm-Level

In order to assess the productivity effects of information and communication technologies (ICT), regressions based on cross–sectional firm–level data may yield unreliable results for the commonly employed production function framework. In this paper, various estimation biases and econometric strategies to overcome their sources are discussed. The effects are illustrated on the basis of a representative set of panel data for German service firms. The application of a suited SYS–GMM estimator yields evidence for significant productivity effects of ICT which are substantially smaller though than those suggested by cross–section or pooled OLS estimates.
Rocket Engine SyStem Re-iiability Analyses Using

The reliability of rocket engine systems was analyzed by using probabilistic and fuzzy logic techniques. Fault trees were developed for Integrated Modular Engine (IME) and Discrete engine systems, and then were used with the two techniques to quantify reliability. The IRRAS (Integrated Reliability and Risk Analysis System) computer code, developed for the U.S. Nuclear Regulatory Commission, was used for the probabilistic analyses, and FUZZYFTA ('Fuzzy Fault Tree Analysis), a code developed at NASA Lewis Research Center, was used for the fuzzy logic analyses. Although both techniques provided estimates of the reliability of the IME and Discrete systems, probabilistic techniques emphasized uncertainty resulting from randomness in the system whereas fuzzy logic techniques emphasized uncertainty resulting from vagueness in the system. Because uncertainty can have both random and vague components, both techniques were found to be useful tools in the analysis of rocket engine system reliability. Reliability
Using on-line available sources of bilingual information for word-level machine translation quality estimation

This paper explores the use of external sources of bilingual information available on-line for word-level machine translation quality estimation (MTQE). These sources of bilingual information are used as a black box to spot sub-segment correspondences between a source-language (SL) sentence S to be translated and a given translation hypothesis T in the target-language (TL). This is done by segmenting both S and T into overlapping sub-segments of variable length and translating them into the TL and the SL, respectively, using the available bilingual sources of information on the fly. A collection of features is then obtained from the resulting sub-segment translations, which is used by a binary classifier to determine which target words in T need to be post-edited. Experiments are conducted based on the data sets published for the word-level MTQE task in the 2014 edition of the Workshop on Statistical Machine Translation (WMT 2014). The sources of bilingual information used are: machine translation (Apertium and Google Translate) and the bilingual concordancer Reverso Context. The results obtained confirm that, using less information and fewer features, our approach obtains results comparable to those of state-of-the-art approaches, and even outperform them in some data sets. c � 2015 The authors. This article is licensed under a Creative Commons 3.0 licence, no derivative works, attribution, CCBY-ND.
Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)

In November 2016 we submitted to arXiv our paper "Automated Inference on Criminality Using Face Images". It generated a great deal of discussions in the Internet and some media outlets. Our work is only intended for pure academic discussions; how it has become a media consumption is a total surprise to us. Although in agreement with our critics on the need and importance of policing AI research for the general good of the society, we are deeply baffled by the ways some of them mispresented our work, in particular the motive and objective of our research.
Reef fishes in the marine protected area of Dampier strait, raja ampat islands, West Papua Province, Indonesia

Research to study reef fish was carried out at coastal water of eighteen station in the Marine Protected Area of Dampier Strait, Raja Ampat (MPADSRA) on November 2017. Reef fish in the area was observed by using underwater visual census method at a belt transect of 350 m (70 m length, 5 m width). Primary data obtained reef fish found in this research consists of 240 species in 98 genera and 30 families. Coral Fish Diversity Index (CFDI) determined based on six main families indicated that relative diversity of reef fish in the area can be classified into very poor to poor. Categories. Based on CFDI value, the estimated number of reef fish in the Marine Protected Area of Dampier Strait, Raja Ampat was 474 species.
International Journal of Management Sciences and Business Research, June-2023 ISSN (2226-8235) Vol-12, Issue 6

The growing popularity of non-financial reporting has led to an increasing number of companies disclosing information on ESG factors. Non-financial reporting involves presenting environmental, social, and corporate governance issues that are impacted by or impact the company's operations. Initially seen as a corporate social responsibility, there has been a shift in understanding as academic studies have revealed potential advantages associated with the presentation of ESG factors. This has prompted companies and researchers to explore the benefits of incorporating ESG-related aspects into their reporting practices. The current research presents a comprehensive literature review on the influence of ESG factors on company value. The study utilizes a systematic approach to identify relevant literature and evaluates the methodologies employed in the selected studies. The findings are synthesized to identify common themes and trends, while also assessing the limitations and gaps in the literature. The results of the literature review demonstrate the importance of ESG factors in shaping company value. The findings highlight the positive impact of ESG factors on stakeholder relationships, stock performance volatility, stock earnings, financing costs, and overall economic, environmental, and social performance. The study also identifies the influence of company management perceptions and interactions with rating agencies on ESG factor ratings. This article contributes to the existing body of knowledge by providing a comprehensive overview of the influence of ESG factors on company value based on a rigorous literature review. The insights generated from this research can inform decision-making processes and future research endeavors in the field of ESG factors and company valuation.
Groundwater conflicts or disputes? Experience from Mbarali District in Tanzania

This article examines conflicts and or disputes attributed to ineffectiveness of groundwater governance. The study adopted sequential exploratory research design. A random sample of 90 water users was involved in the survey. The key informants and focus group discussions were used to collect qualitative data. Content analysis was used to analyze qualitative data. Frequency and percentage distribution of the responses were computed by using Statistical Package for the Social Sciences (SPSS). The results show that 43 (47.7%) of the sample experienced groundwater disputes, between and or among water users themselves, or between groundwater governance structures, at least in the previous five years since 2013. This is attributed to poor governance and failure of the actors in abiding to the guidelines of the Water Resource Management Acts of 2009 (WRMA), particularly lack of transparency, destruction of water pumps and unequal distribution of water among groundwater users. Some disputes were resolved successfully at water users’ level, while those occurred between governance structures were difficult to resolve. The article concludes that there was poor groundwater governance and therefore disputes occurred. The disputes could develop into conflicts if continue unabated. Therefore, the article recommends strengthening of groundwater governance in abiding to the Acts. It also recommends a comprehensive governance structural arrangement, formal and informal institutions to enhance groundwater governance, specifically resolving groundwater disputes to avoid conflicts in future.
Effect of Planting Dates and Varieties on Potato Yield

Potato is the staple food of almost half of the world’s population (Thiele et al., 2010). India is the second largest producer of potato in the world (Saxena and Mathur, 2013). In Odisha potato is very important among vegetables. The crop is grown in about 7000 hectares in the state with a total production of around 100 thousand tonnes. The low productivity in the state is attributed to several factors. The most important among them is the short, mild and fluctuating winter during which the crop is grown. In the coastal districts where the winter is very short, early varieties and in comparatively longer winter areas of inland districts medium duration varieties are under cultivation. Planting date is considered very important to take the full advantage of the short growing period. Since tuberization rate in potato declines above a temperature of 17°C, increasing temperature may lead to reduced yields in potato varieties now cultivated close to the upper climatic limits of the crop that would not be recovered by higher levels of carbon dioxide. Earlier planting is not possible due to unfavourable weather conditions, particularly late rains. Early planted potatoes are high in starch content (White and Sanderson, 1983) and low in glucose and fructose (Nelson and Shaw, 1976) whereas, delayed planting results in reduced dry matter and starch content and increased reducing sugar (Lisinska and Leszczynski, International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 03 (2018) Journal homepage: http://www.ijcmas. com
p-FP: Extraction, Classification, and Prediction of Website Fingerprints with Deep Learning

Recent advances in learning Deep Neural Network (DNN) architectures have received a great deal of attention due to their ability to outperform state-of-the-art classifiers across a wide range of applications, with little or no feature engineering. In this paper, we broadly study the applicability of deep learning to website fingerprinting. We show that unsupervised DNNs can be used to extract low-dimensional feature vectors that improve the performance of state-of-the-art website fingerprinting attacks. When used as classifiers, we show that they can match or exceed performance of existing attacks across a range of application scenarios, including fingerprinting Tor website traces, fingerprinting search engine queries over Tor, defeating fingerprinting defenses, and fingerprinting TLS-encrypted websites. Finally, we show that DNNs can be used to predict the fingerprintability of a website based on its contents, achieving 99% accuracy on a data set of 4500 website downloads.
Evaluating formal properties of feature diagram languages

Feature diagrams (FDs) are a family of popular modelling languages, mainly used for managing variability in software product lines. FDs were first introduced by Kang et al. as part of the feature-oriented domain analysis (FODA) method back in 1990. Since then, various extensions of FODA FDs were devised to compensate for purported ambiguity and lack of precision and expressiveness. Recently, the authors surveyed these notations and provided them with a generic formal syntax and semantics, called free feature diagrams (FFDs). The authors also started investigating the comparative semantics of FFD with respect to other recent formalisations of FD languages. Those results were targeted at improving the quality of FD languages and making the comparison between them more objective. The previous results are recalled in a self-contained, better illustrated and better motivated fashion. Most importantly, a general method is presented for comparative semantics of FDs grounded in Harel and Rumpe's guidelines for defining formal visual languages and in Krogstie et al.'s semiotic quality framework. This method being actually applicable to other visual languages, FDs are also used as a language (re)engineering exemplar throughout the paper.
World Journal on Educational Technology: Current Issues

The coronavirus disease 2019 pandemic still leaves problems, one of which is in the world of education. Online learning has not become the optimal alternative for learning mathematics, especially for elementary school students. Hybrid learning is learning that integrates face-to-face learning and online learning. Learning by including limited face-to-face meetings can be one of the considerations to deal with the characteristic needs of elementary school students. Therefore, the purpose of this study is to examine the effect of elementary school students’ mathematics learning motivation in hybrid learning on their learning achievement, the effect of elementary school students' mathematics self-efficacy in hybrid learning on their learning achievement and also the effect of elementary school students' motivation and mathematics self-efficacy in hybrid learning on learning achievement. The method used is regression analysis using SPSS 23.0. Previously, the prerequisite test and normality test were carried out. This research was conducted in 5 schools with a sample of 132 elementary school students. After the research was conducted, the results showed that partially the motivation and self-efficacy variables of students' mathematics influenced students’ achievement. The variable of mathematics self-efficacy affects the achievement of 20.1%. Mathematics self-efficacy affects the achievement of 20.7%. Meanwhile, the two independent variables also influence the learning achievement of elementary school students, which is 23.6%. From these data, it can be seen that the variables of mathematics self-efficacy and student learning motivation together have a more significant effect than their partial effect on elementary school students’ learning achievement.
Processes for Occurrence of Strong Cold Events over Eastern China

AbstractA strong cold event hit eastern China around 24 January 2016 with surface air temperature reaching more than 10°C below the climatological mean in most regions of eastern China south of 40°N. A total of 37 strong cold events similar to the January 2016 event with temperature anomalies over eastern China exceeding −5°C have been identified during the winters from 1979/80 to 2015/16. A comparative analysis of events with surface temperature anomalies of the same intensity but limited to north of 40°N indicates that the southward invasion of cold air to eastern China south of 40°N is related to two factors. One is the latitudinal location of the upper-level wave train, the surface Siberian high, and the midtropospheric East Asian trough over the mid- to high-latitude Eurasian continent. The other is a subtropical upper-level wave train emanating from the midlatitude North Atlantic. The emergence of the subtropical wave train is related to the positive phase of the North Atlantic Oscillation (NAO). Wh.
Chapter 2: Dynamic vegetation modeling of forest, woodland, shrubland, and grassland vegetation communities in the Pacific Northwest and Southwest Regions of the United States

Land management planning at broad scales requires integrative techniques to understand and synthesize the effects of different land management activities and address socioeconomic and conservation concerns. The Integrated Landscape Assessment Project was developed to support the vital but complex task of broadscale integration of information to assess ecological sustainability at multiple scales. The project supports ecosystem management planning at a regional scale across all lands of Arizona, New Mexico, Oregon, and Washington by simulating landscape dynamics using state-and-transition models (STMs) and linking model output to management planning considerations such as fuel conditions, wildlife habitat, community economics, and climate change. The stakeholders and target users for the Chapter 2: Dynamic Vegetation Modeling of Forest, Woodland, Shrubland, and Grassland Vegetation Communities in the Pacific Northwest and Southwest Regions of the United States
Improving landfill monitoring programs with the aid of geoelectrical-imaging techniques and geographical information systems

The discovery of an extremely high effective electron mass in CeAl3 by Andres et al in 1975 was the starting point for Heavy Fermion physics. One possible theory for explaining this heavy fermion behaviour is the Kondo lattice model which is investigated in this master thesis. With a slave boson mean field approach using Green’s functions, a set of mean field equations are derived and solved. The solutions of these equations determine the model behaviour as a function of various input parameters. In addition, a system where the Kondo lattice model is in close proximity to a Scanning Tunneling Microscope is considered. By the use of non-equilibrium Keldysh formalism, a tunneling current and differential conductance is calculated. The differential conductance is seen to map out the Kondo lattice density of states.
Improving landfill monitoring programs with the aid of geoelectrical-imaging techniques and geographical information systems

GPGPU (general purpose computing on graphics processing units) programming is one interesting way to increase performance; unfortunately it is not easily done, because extensive knowledge of the GPU’s architecture is required to write programs that are faster than CPU programs. Obsidian is an embedded domain specific language for writing GPGPU kernels, which tries to make GPUs more programmable, but it still requires extensive knowledge of the GPU’s architecture to write fast kernels. This thesis demonstrates extensions to Obsidian, which increase the programmability of graphics processors. The methods described in this thesis increase the programmability by providing the programmer with feedback about their code through static analysis regarding possible performance bottlenecks, and common programming mistakes. This thesis also demonstrates how many of the decisions of optimizing kernels can be automated through different code transformations. The resulting domain specific language improves upon Obsidian by requiring less knowledge of GPU programming, making it easier to write correct programs, while still providing programs that are as fast and as expressive. The different kinds of feedback provided to the programmer using static analysis are many. Out of bounds checking and race condition detection are useful for determining correctness of code. Memory access patterns analysis for determining coalescing and bank conflict issues, divergent branch detection, unnecessary synchronization detection, and a cost model are useful for finding bottlenecks. The code transformations used are scalar depromotion, unnecessary synchronization removal, and some traditional loop transformations that enable an arbitrarily structured program to be transformed into a kernel efficiently runnable on a GPU.
Design of practical color filter array interpolation algorithms for digital cameras

Single-chip digital cameras use a color filter array and subsequent interpolation strategy to produce full-color images. WHile the design of the interpolation algorithm can be grounded in traditional sampling theory, the fact that the sampled data is distributed among three different color planes adds a level of complexity. Previous ways of treating this problem were based on computationally intensive approaches, such as iteration. Such methods, while effective, cannot be implemented in todays crop of digital cameras due to the limited computing resources of the cameras and the accompanying host computers. These previous methods are usually derived from general numerical methods that do not make many assumptions about the nature of the data. Significant computational economies, without serious losses in image quality, can be achieved if it is recognized that the data is image data and some appropriate image model is assumed. To this end, the design of practical, high- quality color filter array interpolation algorithms based on a simple image model is discussed.
Costly Dividend Signaling: The Case of Loss Firms with Negative Cash Flows

We examine the dividend-signaling hypothesis in a sample of firms for which dividend increases are particularly costly, namely loss firms with negative cash flows. When compared to loss firms with positive cash flows, we find the predictive power of dividend increases for future return on assets to be greater for loss firms with negative cash flows, consistent with the predictive power of the dividend signal being stronger when its cost is higher. Our results provide support for the dividend-signaling hypothesis and have broader implications since loss firms comprise a large and increasing share of publicly-traded firms.