Miracle-dz/UniFAR-FTUs huggingface dataset:
Climatic and biological drivers of temporal dynamics and feedbacks of the carbon balance of forests

Forest ecosystems, covering a third of the world’s land surface, play a major role in the global carbon (C) cycle due to their ability to take up and store large amounts of atmospheric carbon dioxide (CO2). Thus, accurate and reliable estimates of annual forest C budgets are needed, e.g. for post-Kyoto agreements on national levels. However, the large inter-annual variability and still existing knowledge gaps on drivers and their underlying ecophysiological mechanisms of C exchange processes result in profound difficulties explaining and calculating annual forest C budgets. Uncertainties of these estimates need to be substantially reduced. Hence, this PhD project investigated climatic and biological drivers of temporal and dynamic feedbacks of the C balance of forest ecosystems, including tree growth as its major component. The aim of this thesis was addressed by analysing data of eddy covariance (EC) measurements of the CO2 exchange as well as dendrometer and tree-ring derived data on tree growth of Swiss, European, and North American forests, covering a broad gradient of climatic conditions and strongly varying site characteristics. First, concentrating on Swiss forests, we showed that the C balance of a subalpine coniferous forest was both strongly and positively driven by current and previous year’s weather conditions in spring (March, April, May). Explained inter-annual variability of the net ecosystem productivity (NEP) rose from 20% to 53%, when the previous year was included into the statistical analysis, indicating delayed responses of forest NEP to previous year’s weather. The relevance of (current year) spring weather was also confirmed by tree-ring analysis of the same subalpine forest as well as by analysis of EC data of a mixed deciduous mountain forest in Switzerland. Air and soil temperature in spring were frequently identified as the driving climate variables of NEP. By expanding our analysis to the European scale and additionally including two North American forest ecosystems, we could confirm both the single-site results of the influence of the previous year on and the importance of spring for the C balance of strongly differing forests. We quantified that on average (eight out of nine sites), explained inter-annual variability of NEP rose from 49% to 64% when considering both current and previous year’s weather, with weather conditions in current and previous year’s spring being highly influential for forest NEP also on this larger
University of Birmingham Usability and Effectiveness Evaluation of Adaptivity in E-Learning Systems

Designing effective and usable adaptive e-learning systems represents a challenge because of the complexity which arises when meeting the needs of learners. This is compounded by the lack of welldesigned experimental evaluations of adaptive elearning systems in general, and of their usability and effectiveness in particular. This paper offers an experimental evaluation of the effect of adaptation, taking into account both the perceived usability level and learning effectiveness. A controlled experiment was conducted with 75 participants and produced significant results. They indicate that an adaptive version has a significantly higher level of perceived usability and learning effectiveness than a non-adaptive version.
Personalized search based on user search histories

User profiles, descriptions of user interests, can be used by search engines to provide personalized search results. Many approaches to creating user profiles collect user information through proxy servers (to capture browsing histories) or desktop bots (to capture activities on a personal computer). Both these techniques require participation of the user to install the proxy server or the bot. In this study, we explore the use of a less-invasive means of gathering user information for personalized search. In particular, we build user profiles based on activity at the search site itself and study the use of these profiles to provide personalized search results. By implementing a wrapper around the Google search engine, we were able to collect information about individual user search activities. In particular, we collected the queries for which at least one search result was examined, and the snippets (titles and summaries) for each examined result. User profiles were created by classifying the collected information (queries or snippets) into concepts in a reference concept hierarchy. These profiles were then used to re-rank the search results and the rank-order of the user-examined results before and after re-ranking were compared. Our study found that user profiles based on queries were as effective as those based on snippets. We also found that our personalized re-ranking resulted in a 34% improvement in the rankorder of the user-selected results.
COMPARATIVE ANALYSIS OF MEDICAL IMAGE COMPRESSION TECHNIQUES

The rapidly increasing use of images in various applications like in automation, security systems, in robotics and in medical treatments have paved the compression techniques to be more efficient. The medical images like Ultrasound, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) contains large volume of data. The recent growth of data intensive multimedia-based web applications have not only have up the need for more important ways to encode signals and images but have successful compression of such signals primal to storage and communication technology. But storing and transferring these huge voluminous data could be a tedious job. The digitization of the medical image information is of immense interest to the medical community which can lead to the implementation of e-health, teleradiology, tele-consultation, telemedicine and telematics. Discrete Cosine Transform (DCT) is one of the widely used compression method. Also the Discrete Wavelet Transform (DWT) provides substantial improvements in picture quality due to its multi resolution nature. In this paper a comparison of DCT & DWT in terms of Peak signal-to-noise ratio (PSNR), Mean Square Error (MSE) and overall Compression Ratio to illustrate the effectiveness of this method in Image compression.
Geometrical and Optical Benchmarking of Copper ( II ) Guanidine – Quinoline Complexes : Insights from TD-DFT and Many-Body Perturbation Theory ( Part II )

Oxidative addition of aryl halides to gold(I) complexes are known to be kinetically sluggish. The reasons have so far not been understood. On page 2140, Israel Fernández, Lando P. Wolters, and F. Matthias Bickelhaupt provide the missing insight using the Activation Strain Model (ASM) of chemical reactivity. The relatively high rigidity of gold(I) complexes plays a key role. This rigidity, in combination with the fact that oxidative addition requires bending of the complex, leads to a high catalyst activation strain and thus a high activation energy. Based on this new insight, strategies are developed to achieve lower, more feasible reaction barriers. On page 2146, ground-and excited-state properties of copper(II) charge-transfer systems are investigated from density-functional calculations with particular emphasis on the role of the exchange and correlation functional, the basis set, solvent effects, and the treatment of dispersive interactions. Furthermore, the applicability of TD-DFT to excitations of copper(II) bis(chelate) charge-transfer systems is explored by performing many-body perturbation theory (GW+BSE), independent-particle approximation (IPA) and DSCF calculations for a small model system containing simple guanidine and imine groups. Look for these important papers in upcoming issues Distinguishing between keto-enol and acid-base forms of firefly oxyluciferin through calculation of excited-state equilibrium constants Bo Durbeej et al. Aqueous keto-enol and acid-base excited-state equilibrium constants between six neutral, mono-anionic and di-anionic forms of oxyluciferin, the cofactor responsible for the bioluminescence of firefly luciferase, are for the first time calculated from free energies of a Born-Haber cycle, rather than using the Förster equation. The phenolate-keto-OxyLH– mono-anion is the preferred excited-state form of oxyluciferin in aqueous solution, attributing a potential key role to this species in firefly bioluminescence. A simple algorithm for exploiting space group symmetry in fragment-based molecular crystal calculations not requiring a priori knowledge or implementation of the space group tables is described. It relies on rotating each monomer or dimer fragment to a common frame of reference for straightforward identification of symmetrically equivalent fragments. Exploiting space group symmetry often provides significant computational savings in accurate molecular crystal modeling. [a] Ground-and excited-state properties of copper(II) charge-transfer systems have been investigated starting from density-functional calculations with particular emphasis on the role of (i) the exchange and correlation functional, (ii) the basis set, (iii) solvent effects, and (iv) the treatment of dispersive interactions. Furthermore (v), the applicability of TD-DFT to excita-tions of copper(II) bis(chelate) charge-transfer systems is explored by performing many-body perturbation theory (GW 1 BSE), independent-particle …
Overcoming the myopia of inductive learning

Software defect prediction (SDP) can help optimally allocate software testing resources on fault-prone modules. Typically, local data within a company are used to build classifiers. Unlike such Within-Project Defect Prediction (WPDP), there may exist some cases, e.g., pilot projects, without any collected data from historical projects. Cross-project defect prediction (CPDP) using data from other projects can be employed in such cases. The defect prediction performance may be degraded in the presence of irrelevant or redundant information. To address this issue, various feature selection techniques have been suggested. Until now, there has been no research on identifying effective feature selection techniques for CPDP. We present a comparative framework using feature selection to produce a high performance for CPDP. We compare eight existing feature selection techniques, for three CPDP and one WPDP model, based on feature subset evaluators and feature
Semantic Interpretation of the Web without the Semantic Web: Toward Business-Aware Web Processors

In this paper, we describe a family of systems that we are developing to make systematic use of the Web in support of decision-makers. These systems, which we call business-aware web processors, use semantic representations but do not assume that these representations will come from the Semantic Web. We describe the relationship between our vision and the standard Semantic Web vision. We next present two prototype applications based on the approach that we have been developing to support decision-makers in two different contexts. We then describe the underlying technology platform we have been developing to support this family of applications, and the challenges we are confronting as we advance this research agenda.
Evaluation of Externalities Associated with Rare Earth Exploitation at Bayan Obo

Rare earth elements (REEs) are a kind of new materials which have excellent optical, electrical and magnetic properties, and they play an important role in the development of high technology and green energy industries. With abundant reserves and a wide range of REE type, rare earth industry has a rapid development in China in recent years. However, environmental issues associated with REE exploitation have severely restricted the sustainable development of rare earth industry in China. At present, literatures on the externalities of REE exploitation are very limited, especially in China. This paper builds an evaluation model based on life cycle evaluation to estimate the external costs of REE exploitation at Bayan Obo. The results show that the external costs for producing one metric tonne of rare earth oxides (REO) in Bayan Obo was CNY 34739 in 2013, the external costs of waste gas, waste water, radioactive substance, REE resource depletion, and land occupation are CNY 14945, 12515, 1400, 3199, and 2680, respectively. Waste gas and water constitute about 79% of the total external costs. The internalization of the external costs would reduce the financial profit of Northern Rare Earth (Group) by 18%. This study has taken into account only those externalities whose market values can be estimated, and therefore the external costs of REE exploitation in Bayan Obo is likely to be underestimated. The results fill the gap in literature and provide further understanding on the external cost of REE exploitation.
Waveform-based Gradient method for estimating hypocenter mechanism before observing aftershocks

The location of the hypocenter of an earthquake as well as the determination of the source parameters have shown some limitations in the past. The actual studies often neglect the tailing of the waveform to concentrate on the first waves arrivals and the inversion methods often need a precise distribution of aftershocks to locate the fault plane. Using former models of fault slip propagation, we produce synthetic waveforms related to different fault geometries. The inversion method will be adapted to analyze the total waveform and, using a higher number of seismograms, will give back the source parameters of the studied earthquake. The different geometries of slip models give back precise waveforms and the flexibility of the code should be an advantage to future inversion processes of earthquake location. The improvements of the fault models and the inversion method are discussed through this paper.
Power Aware Routing Protocols in Mobile Adhoc Networks-Survey

A Mobile Ad-hoc Network (MANET) is a self configuring network composed of mobile nodes without any fixed infrastructure. A very important and necessary issue for mobile ad-hoc networks is to find the route between source and destination that is a major technical challenge due to the dynamic topology of the network. Routing protocols for MANETs could be differing depending on the application and network architecture. This paper presents a survey on energy efficient routing protocols for wireless Ad-Hoc networks. Survey focus on recent development and modifications in this widely used field. This discussion is centered on proposed power saving algorithms. Besides it we will discuss about the conventional protocols and also see how these are modified to make these protocols energy efficient.
National Institute of Informatics, Japan at TRECVID 2012

This paper reports our experiments for four TRECVID 2012 tasks: instance search, semantic indexing, multi- media event detection, and known-item search. For the instance search task, we use the same approach as the last year's system with some modifications in quantization and fusion of query representations. The experiments show improved performance of this year's system compared to the last year's system. For the se- mantic indexing task and the multimedia event detection task, we report the experiments using NII-KAORI-SECODE framework. Our best run for the semantic indexing task using local features achieve 20.7% (MAP), ranked 6/15 groups. Especially, the run using only one local feature achieves 18.9% (MAP). As for the multimedia event detection task, we only use global features to serve as a baseline method for comparison with other complicated systems using local features and multi-modal features. I. INSTANCE SEARCH
Optimization Coaching for Fork / Join Applications on the Java Virtual Machine Extended abstract

In the multicore era, developers are increasingly writing parallel applications to leverage the available computing resources and to achieve speedups. Still, developing and tuning parallel applications to exploit the hardware resources remains a major challenge. We tackle this issue for fork/join applications running in a single Java Virtual Machine (JVM) on a shared-memory multicore. Developing fork/join applications is often challenging since failing in balancing the tradeoff between maximizing parallelism and minimizing overheads, along with maximizing locality and minimizing contention, may lead to applications suffering from several performance problems (e.g., excessive object creation/reclaiming, load imbalance, inappropriate synchronization). In contrast to the manual experimentation commonly required to tune fork/join parallelism on the JVM, we propose coaching developers towards optimizing fork/join applications by automatically diagnosing performance issues on such applications and further suggest concrete code modifications to fix them.
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods 1 Appendix : Additional Experiments

2gkx0 + v max, whereg is the universal constant of gravity, k = 0.0305 is the coefficient of friction between the ball and the ground , and vmax is the maximum velocity allowed at the border of the hole in or der to make the ball to enter the hole and not to overcome it. Assuming that the ball has a diame ter of 4.5cm and that the hole has a diameter of7.5cm, vmax is equal to110.7cm/s. At the beginning of each trial the ball is placed at random, between 2000cm and0cm far from the hole. The initial velocity is limited within the interval[0; 500]cm/s. When the ball enters the hole the episode ends with reward 0. If v0 > v 0 , the ball is lost and the episode ends with reward −10. Finally, if v0 < v 0 the episode goes on and the agent can try another hit with reward −1. The state variable x is discretized into ten, 200cm wide intervals. Such discretization has been chosen so that, for each interval, there is only one value of velocity that makes the ball to enter the hole, independentl y from the actual position in the interval.
ATTITUDINAL BELIEF ON ADOPTION OF EMBA PROGRAM IN MALAYSIA

Education has been the main focus of Malaysia. Way back before independent from the colonial, a group of elite Malays stressed the importance of education. Up to present moment, the nation is still considering education to be placed as the primary concern of the elected government. Education has been perceived as allocating a vital role in the development of Malaysia. Thus the nation’s socio-politics and economy will grow in harmony as the population is educated.
A Shared Vision for Digital Transformation: Codification of The Operating Model Canvas Approach

Digital transformations are essential for organisations to stay competitive in modern economy. A digital transformation demands the business and IT departments of an organisation to be aligned and have a shared vision on the organisation’s future. To aid the generation of a shared vision as a basis for digital transformation, we propose the Operating Model Canvas (OMC) Approach. Its result is the OMC, a model that visualises the organisation’s value propositions, primary and supporting business activities, channels, and actors. We have performed a retrospective case study to codify the process and deliverables of the OMC Approach, to define its scientific fundamentals, and demonstrate its results. We found that the OMC provides a shared language for business and IT departments and subsequently generates them a shared vision. The key elements for generating a shared vision during the approach are the usage of existing client documentation and the active client participation throughout the entire process. We think the OMC can therefore be a solid starting point for a digital transformation project. The scientific contribution of this paper is to add to the theory of digital transformation design by codifying the OMC Approach.
Is a comparison of results meaningful from the inexact replications of computational experiments ? ( ELECTRONIC SUPPLEMENTARY MATERIAL )

While performing statistical tests [7] the first question is which statistical test, parametric or non-parametric, is suitable. It is well known that parametric tests have much more power (probability that a statistical test will correctly reject a false null hypothesis, or a probability of avoiding a Type II error) than a non-parametric test. Hence, we should use parametric tests whenever allowed. Conditions for parametric statistical tests are independence, normality, and homoscedasticity [7]. Since we do not have access to raw data of the experiments performed by Waghmare in [8] we can only check normality (e.g., by Kolmogorov-Smirnov test [7]) of our own raw data and make a
Iterative Turbo Channel Estimation for OFDM System over Rapid Dispersive Fading Channel

Coherent OFDM detection requires accurate channel state information (CSI). Mobile radio channels are both time and frequency dispersive, especially at high vehicular speeds, which makes channel estimation a challenging problem in system design. Conventional preamble-based and pilot-aided channel estimation require numerous reference signals, which significantly compromises the system throughput. This paper proposes a novel low complexity iterative turbo channel estimation technique which makes use of preamble, pilots and soft decoded data information in an iterative fashion to improve the system performance over the time and frequency selective fading channel while maintaining the system throughput. The numerical and analytical results show that the proposed technique can approach the performance of systems with perfect CSI with much fewer preamble and pilots symbols compared to existing channel estimation methods.
Discriminative Cluster Analysis

learn paradigms approaches human learning abilities The of is the central features of human intelligence, important ingredient in traditional Artificial Intelligence (AI) and emerging Cognitive Learning (ML) draws upon from a diverse set of disciplines, including AI, Probability and Statistics, Computational Complexity, Information Theory, Psychology and Neurobiology, Control Theory and Philosophy. ML involves broad topics including Fuzzy Logic, Neural Networks (NNs), Evolutionary Algorithms (EAs), Probability and Statistics, Decision Trees, etc. Real-world applications of ML are widespread such as Pattern Recognition, Data Mining, Gaming, Bio-science, Telecommunications, Control and Robotics applications. This books reports the latest developments and futuristic trends in ML.
Assessing the Complexity of Dynamics in Enterprise Architecture Planning – Lessons from Chaos Theory

Enterprise Architecture (EA) models capture the fundamental elements of organizations and their relationships to serve documentation, analysis and planning purposes. As the elements and their relationships change over time, EA planning becomes increasingly complex. An analysis of existing methods shows that the complexity of dynamics is not sufficiently addressed. We argue that a sophisticated understanding of the complexity matter is prerequisite for EA planning method construction. As Chaos Theory (CT) is deployed in natural and social sciences—as well as in different contexts of IS research—to describe and understand the behavior of complex systems over time, we use properties of CT to assess the complexity of dynamics in EA planning and to derive requirements for EA planning methods. Our findings emphasize the importance of initial conditions of the architecture for EA planning and the need to harmonize planning granularities in order to achieve predictable results.
Annotation Scheme for Information Status in Dialogue

Our aim is to annotate some of (or excerpts of some of) the Switchboard dialogues for (co-)reference and information structure. Information structure at this stage does not include pitch accents and nothing about them is included in this document as of now. Information status at the moment is defined via three categories: old, mediated, new (see Section 5). We will annotate information status of entities based on previous mentions in the dialogue and on inferrability.