Miracle-dz/UniFAR-FTUs huggingface dataset:
AIS Electronic

Researchers and practitioners in Information Systems (IS) share an interest in the application of information technologies (IT) to organisational systems. Such technologies today are overwhelmingly digital, with the context of their use being human activity organised into increasingly networked forms. This paper makes sense of these connections via theories of cybernetics, particularly Beer’s Viable System Model. It aims to bring together a disparate body of theory – on networks – to produce a more synthesising, ‘meta’ account, thus helping to explain both the importance of digital technology to network growth, as well as the basis on which network structures can be stable, flexible and effective. It discusses the emergence of network structures across society, noting various forms of networks and the contested nature of the concept. It goes on to discuss the development of digital artefacts and infrastructures. The importance of network stability and flexibility is then analysed, leading to an account of system properties using management cybernetics. It is argued that the notions of self-organisation and self-regulation – key characteristics in viable systems – can be used to understand why network structures have emerged and thrived since the 1990s. It concludes by noting the importance of these ideas for future IS research.
3dCAP-wheat: an open-source comprehensive computational framework 1 precisely quantifies wheat foliar, non-foliar and canopy photosynthesis 2

Canopy 29 photosynthetic tissues. Quantitative roles of non-foliar tissues in canopy 30 photosynthesis remain elusive due to methodology limitations. Here, we develop the 31 first complete canopy photosynthesis model incorporating all above-ground 32 photosynthetic tissues and validate this model on wheat with state-of-the-art gas 33 exchange measurement facilities. The new model precisely predicts wheat canopy gas 34 exchange rates at different growth stages, weather conditions and canopy architectural 35 perturbations. Using the model, we systematically study 1) the contribution of both 36 foliar and non-foliar tissues to wheat canopy photosynthesis; and 2) the responses of 37 wheat canopy photosynthesis to plant physiological and architectural changes. We 38 found that 1) at tillering, heading, and milking stages, non-foliar tissues can contribute 39 ~4, ~32, ~50% of daily gross canopy photosynthesis ( A cgross ; ~2, ~15, ~-13% of daily 40 net canopy photosynthesis, A cnet ) and absorb ~6, ~42, ~60% of total light respectively; 41 2) under favorable condition, increasing spike photosynthetic activity, rather than 42 enlarging spike size or awn size, can enhance canopy photosynthesis; 3) covariation 43 in tissue respiratory rate and photosynthetic rate may be a major factor responsible for 44 less than expected increase in daily A cnet ; and 4) in general, erect leaves, lower spike 45 position, shorter plant height and proper plant densities can benefit daily A cnet . 46 Overall, the model, together with the facilities for quantifying plant architecture and 47 tissue gas exchange, provide an integrated platform to study canopy photosynthesis 48 and support rational design of photosynthetically efficient wheat crops.
Switch-factor based loop RLC modeling for efficient timing analysis

Timing uncertainty caused by inductive and capacitive coupling is one of the major bottlenecks in timing analysis. In this paper, we propose an effective loop RLC modeling technique to efficiently decouple lines with both inductive and capacitive coupling. We generalize the RLC decoupling problem based on the theory of distributed RLC lines and a switch-factor, which is the voltage ratio between two nets. This switch-factor is also known as the Miller factor, and is widely used to model capacitive coupling. The proposed modeling technique can be directly applied to partial RLC netlists extracted using existing parasitic extraction tools without advance knowledge of the return path. The new model captures the impact of neighboring switching activity as it significantly affects the current return path. As demonstrated in our experiments, the new model accurately predicts both upper and lower delay bounds as a function of neighboring switching patterns. Therefore, this approach can be easily implemented into existing timing analysis flows such as max-timing and min-timing analysis. Finally, we apply the new modeling approach to a range of activities across the design process including timing optimization, static timing analysis, high frequency clock design, and data-bus wire planning.
WORKING PAPER

We examine the impact of uncertainty on contingent valuation responses using (1) a survey of Canadian landowners about willingness to accept compensation for converting cropland to forestry and (2) a survey of Swedish residents about willingness to pay for forest conservation. Five approaches from the literature for incorporating respondent uncertainty are used and compared to the traditional RUM model with assumed certainty. The results indicate that incorporating uncertainty has the potential to increase fit, but could introduce additional variance. While some methods for uncertainty are an improvement over traditional approaches, we caution against systematic judgments about the effect of uncertainty on contingent valuation responses.
Enabledness-based Program Abstractions for Behaviour Validation

Code artefacts that have non-trivial requirements with respect to the ordering in which their methods or procedures ought to be called are common and appear, for instance, in the form of API implementations and objects. This work addresses the problem of validating if API implementations provide their intended behaviour when descriptions of this behaviour are informal, partial or non-existent. The proposed approach addresses this problem by generating abstract behaviour models which resemble typestates. These models are statically computed and encode all admissible sequences of method calls. The level of abstraction at which such models are constructed has shown to be useful for validating code artefacts and identifying ﬁndings which led to the discovery of bugs, adjustment of the requirements expected by the engineer to the requirements implicit in the code, and the improvement of available documentation.
Enabledness-based Program Abstractions for Behaviour Validation

Code artefacts that have non-trivial requirements with respect to the ordering in which their methods or procedures ought to be called are common and appear, for instance, in the form of API implementations and objects. This work addresses the problem of validating if API implementations provide their intended behaviour when descriptions of this behaviour are informal, partial or non-existent. The proposed approach addresses this problem by generating abstract behaviour models which resemble typestates. These models are statically computed and encode all admissible sequences of method calls. The level of abstraction at which such models are constructed has shown to be useful for validating code artefacts and identifying findings which led to the discovery of bugs, adjustment of the requirements expected by the engineer to the requirements implicit in the code, and the improvement of available documentation.
Detection Method for Pairs of P and S Waves of Deep Low‐Frequency Earthquakes Using a 3‐D Array in the Tokai Area of the Nankai Subduction and Its Application to Hypocenter Determination

We report on a novel method that uses a three‐dimensional (3‐D) array to detect P and S wave pairs of the deep low‐frequency earthquakes (LFEs) occurring along the Nankai subduction zone. In an effort to determine LFE hypocenters precisely we attempt to find their P and S pairs and obtain S‐P times using a 3‐D array (6 km in the horizontal direction) made up 14 seismic stations with deep (600 m at the deepest) borehole seismographs in the Tokai area. During operation we observed remarkable LFE activities on 10–30 November 2010. Using these data, we succeeded in distinguishing between P and S phases in complex LFE seismic waves using an effect of velocity filtering in semblance analysis via the 3‐D array. We also obtained high‐quality propagation parameters (back azimuths and incidence angles) and S‐P times for the LFEs. Referring to these identified P and S phases, after manually reading the arrival times at the 3‐D array and regular network, we could precisely relocate the hypocenters of 15 LFEs. These hypocenters were distributed in a depth range from 26 to 34 km, and approximately followed the plate interface. A comparison of the LFE hypocenter distribution to seismic tomography indicates that the LFEs are distributed in the oceanic crust and mantle wedge with relatively low velocities under an undrained cover with relatively high velocities following the land Moho (land crust bottom). We believe that our detection method will be useful in the automated detection and preliminary hypocenter determination of LFEs.
Probabilistic Snow Cover and Ensemble Streamflow Estimations in the Upper Euphrates Basin

Abstract Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin. Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001-2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013-2015 where the estimated runoff values indicate good consistency (NSE: 0.47-0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas.
Information extraction and integration for web databases

A large number off the Web pages returned by filling in search forms are not indexable by most search engines today since they are dynamically generated by querying a back-end (relational or object-relational) database. Referred to as Web databases, such Web sites usually contain complex data objects with nested structures in their Web pages. In this thesis, we address a variety of problems related to retrieving information from Web databases. To extract structured data embedded in template-generated pages from Web databases, we first develop an algorithm to automatically identify the data-rich sections in the page and then propose an innovative approach to automatically induce regular-expression wrappers from them. To understand the semantics of both the query interfaces and the extracted data from various Web databases and integrate them, we propose a combined schema model to describe differentiated schemas in a Web database (global, interface and result schema). We then address two significant schema-matching problems for Web databases, intra-site schema matching and inter-site schema matching, and investigate an instance-based method using domain-specific query probing to solve the two problems at the same time.
The role of dopaminergic medication, lipid, and endocannabinoid pathway alterations in idiopathic and PRKN/PINK1-mediated Parkinson's disease - a large-scale targeted metabolomics study

Alterations in many metabolites and biochemical pathways have been described in Parkinson's Disease (PD). However, only a small fraction of these have been replicated in independent studies. As almost every PD patient is treated with dopaminergic medication, it is challenging to discriminate between disease- and drug-related effects, especially in relation to dopamine metabolism. We conducted a large-scale metabolomic study in plasma from 140 idiopathic (IPD), 19 PRKN/PINK1-linked PD patients, and 64 healthy controls to disentangle disease-related metabolite alterations from drug-related effects. We distinguished between L-Dopa and non-L-Dopa treated PD patients to uncover nuanced metabolic changes associated with different therapies. We demonstrate that L-Dopa treatment uniquely influences the metabolome, with methyldopa and methoxytyramine, both L-Dopa breakdown products, elevated in L-Dopa-treated IPD and PRKN/PINK-linked PD patients. These alterations were not seen in untreated IPD patients and those on agonist treatment only. Polyamine metabolism alterations, notably elevation of putrescine and ornithine, were partly caused by L-Dopa treatment but also found in non-L-Dopa treated PD patients. In non-L-Dopa-treated patients, endocannabinoid metabolites were lowered and associated with disease duration. We observed lipid metabolism alterations, highlighting potential crosslinks with alpha-synuclein and providing insights into pathophysiological mechanisms. All PRKN/PINK1-linked PD patients received L-Dopa treatment. However, our data potentially support the well-established role of oxidative damage in these subtypes of PD. In conclusion, our study emphasizes the significant impact of L-Dopa treatment on the metabolome, which might be of relevance not only for metabolomics studies but also for PD biomarker research in general. Finally, our study highlights potential biomarkers and pathways crucial for understanding the disease mechanisms of PD.
Flows and Practices: The Politics of Integrated Water Resources Management in Eastern and Southern Africa

For the past two decades, Integrated Water Resources Management (IWRM) has been the dominant paradigm in water resources. This book explores how ideas of IWRM are being translated and adapted in Mozambique, South Africa, Tanzania, Uganda and Zimbabwe. Grounded in social science theory and research, it highlights the importance of politics, history and culture in shaping water management practices and reform, and demonstrates how Africa has clearly been a laboratory for IWRM. While a new cadre of professionals made IWRM their mission, we show that poor women and men may not have always benefitted. In some cases IWRM has also offered a distraction from more critical issues such as water and land grabs, privatisation, the negative impacts of water permits, and a range of institutional ambiguities that prevent water allocations to small and poor water users. By critically examining the interpretations and challenges of IWRM, the book contributes to improving water policies and practices and making them more locally appropriate in Africa and beyond.
The Open University at TREC 2006 Enterprise Track ExpertSearch Task Conference or Workshop Item

The Multimedia and Information Systems group at the Knowledge Media Institute of the Open University participated in the Expert Search task of the Enterprise Track in TREC 2006. We have proposed to address three main innovative points in a two-stage language model, which consists of a document relevance model and a cooccurrence model, in order to improve the performance of expert search. The three innovative points are based on characteristics of documents. First, document authority in terms of their PageRanks is considered in the document relevance model. Second, document internal structure is taken into account in the co-occurrence model. Third, we consider multiple levels of associations between experts and query terms in the co-occurrence model. Our experiments on the TREC2006 Expert Search task show that addressing the above three points has led to improved effectiveness of expert search on the W3C dataset.
Retrieving Diverse Social Images at MediaEval 2016: Challenge, Dataset and Evaluation

This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the Media-Eval 2016 Benchmarking Initiative for Multimedia Evaluation. The task addresses the problem of result diversi(cid:12)cation in the context of social photo retrieval where images, meta-data, text information, user tagging pro(cid:12)les and content and text models are available for processing. We present the task challenges, the proposed data set and ground truth, the required participant runs and the evaluation metrics.
Retrieving Diverse Social Images at MediaEval 2017: Challenges, Dataset and Evaluation

This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2017 Benchmarking Initiative for Multimedia Evaluation. The task addresses the challenge of visual diversification of image retrieval results, where images, metadata, user tagging profiles, and content and text models are available for processing. We present the task challenges, the employed dataset and ground truth information, the required runs, and the considered evaluation metrics.
A conceptual approach to an open hospital information system

A concept for an open hospital Information System integrating heterogeneous components is proposed. The approach is object-oriented, but is not built directly upon object-oriented database management Systems. Basic ideas are a Software bus, Workflow management with extended transaction concepts, and integrated knowledge-based modules. From the application perspective, conventional and problem-oriented views, support of complex medical and organizational pro-cesses including scheduling, and integrated clinical guidelines are important features.
SJSU ScholarWorks

Natural Language Processing (NLP) requires the computational modelling of the complex relationships of the syntax and semantics of a language. While traditional machine learning methods are used to solve NLP problems, they cannot imitate the human ability for language comprehension. With the growth in deep learning, these complexities within NLP are easier to model, and be used to build many computer applications. A particular example of this is a chatbot, where a human user has a conversation with a computer program, that generates responses based on the user’s input. In this project, we study the methods used in building chatbots, what they lack and what can be improved.
The Associative PDA : An organic user interface for mobile personal information management

In this paper, we describe the ongoing design process of the Associative PDA, a ubiquitous device for personal information management (PIM) in an associative network. We present the results of a contextual study, we have conducted, indicating several problems of current PIM systems, and then explain why the Associative PDA can avoid them. Finally, we give a brief outlook of our design ideas and future work.
Korean national Program expedition confirms rich gas hydrate deposit in the Ulleung Basin, East Sea

November 2007 marked the successful completion of South Korea’s first large-scale gas hydrate exploration and drilling expedition in the East Sea: Ulleung Basin Gas Hydrate Expedition 1 (UBGH1), which successfully explored and recovered gas-hydrate-bearing sediments at three different locations in the Ulleung Basin. Expedition UBGH1 sailed 57 days in two legs aboard the multipurpose offshore support vessel REM Etive, which had been converted to a drilling ship by Fugro Seacore using the heavecompensated R100 portable drill rig (Figure 1). The Korea National Oil Corporation (KNOC) and Korea Gas Corporation (KOGAS) contracted Fugro to supply drilling, wireline logging, coring and associated services for Expedition UBGH1, while other companies including Schlumberger and Geotek provided Logging While Drilling (LWD) and core analysis services respectively. Technical decisions directing the scientific aspects of the work were made by the Korea Gas Hydrate R&D Organization and the Korea Institute of Geoscience and Mineral Resources (KIGAM).
Analysis of Power and Stability of 7T SRAM Cell

This paper addresses a novel seven transistor (7T) CMOS SRAM cell design to enhance the stability, reduce dynamic power, leakage power and area in various applications. The designed cell has an inbuilt mechanism for charge sharing, by which power has been saved for write operation. The proposed 7T SRAM cell uses charging/ discharging single Bit Line (BL) mechanism, which results in reduction in the dynamic power consumption. In this work the stability has been studied and calculated by N-curve method. The measured results have reduced 10.88% and 47.18% of leakage and dynamic power respectively. Moreover the area is reduced by 12.15%. Keywords— Dynamic power, leakage power, stability, N-curve, static voltage noise margin, static current noise margin, write trip voltage, write trip current
Obituary: Peter Knijnenburg (1961–2007)

With Peter Knijnenburg’s passing away earlier this year we lost a great scientist, colleague and friend. Peter made significant contributions in many areas and is probably best known for his work on iterative compilation where he showed creative insight many years before the subject became mainstream. Peter was unusual in that he was highly versatile in his thinking and approach. This is probably best illustrated by his ability to move from physics to the ‘theory of theories’—category theory and then on to linear algebraic program frameworks, iterative compilation and SMT quality of service. He was a highly prolific researcher publishing many papers in his short academic life and working with over 90 different co-authors. He possessed exceptional analytical skills and was able to succinctly communicate his research contributions. He was generous with his time and ideas. For many Peter Knijnenburg will be remembered for his warm hospitality when hosting the CPC workshop in Amsterdam 2003. Peter’s passing is a great loss to the research community. He is sadly missed and will always be remembered with affection by his colleagues.
Accurate and Efficient Indoor Location by Dynamic Warping in Sequence-Type Radio-map

An efficient way to overcome the calibration challenge and RSS dynamics in radio-map-based indoor localization is to collect radio signal strength (RSS) along indoor paths and conduct localization by sequence matching. But such sequence-based indoor localization suffers problems including indoor path combinational explosion, random RSS miss-of-detection during user movement, and user moving speed disparity in online and offline phases. To address these problems, this paper proposes an undirected graph model, called WarpMap to efficiently calibrate and store the sequence-type radio-map. It reduces RSS sequence signature storage complexity from O(2N) to O(N) where N is the number of path crosses. An efficient on-line candidate path extraction algorithm is developed in it to find a set of the most possible candidate paths for matching with the on-line collected RSS sequence. Then, to determine the user's exact location, a sub-sequence dynamic time warping (SDTW) algorithm is proposed, which matches the online collected RSS sequence with the sequential RSS signatures of the candidate paths. We show the SDTW algorithm is highly efficient and adaptive, which localizes user without backtracking of warping path. Extensive experiments in office environments verified the efficiency and accuracy of WarpMap, which can be calibrated within thirty minutes by one person for 1100m2 area and provides overall nearly 20% accuracy improvements than the state-of-the-art of radio-map method.