nils-herrmann/clean_scirepeval huggingface dataset:
Hidden Markov Model for Process Mining of Parallel Business Processes

One of all the works on process mining is the process discovery which produces a representation of a parallel business process. This representation is called process model and it consists of sequence and parallel control flow patterns. The parallel control flow patterns contain XOR, AND, and OR relations. Hidden Markov Model is rarely used to represent a process model since XOR, AND and OR relations are not visible. In Hidden Markov Model, the control flow patterns are represented by probabilities of state transitions. This research proposes an algorithm consisting in a process discovery based on Hidden Markov Model. This algorithm contains equations and rules: the equations are used to differentiate XOR, AND, and OR relations, while the rules are used to establish the process model utilizing detected control flow patterns. The experiment results show that the proposed algorithm obtain the right control flow patterns in the process model. The paper demonstrates that the fitness of process models obtained by the proposed algorithm are relatively higher respect to those obtained by Heuristics Miner and Time based Heuristics Miner algorithms. This paper also shows that the validity of process models obtained by the proposed algorithm are better than those obtained by other algorithms.
Coupled Hidden Markov Model for Process Mining of Invisible Prime Tasks

Process mining provides process improvement in a variety of application domains. A primary focus of process mining is transferring information from event logs into process model. One of the issues of process mining is dealing with invisible prime tasks. An invisible prime task is an additional task in the process model to assist in showing real processes. However, a few of algorithm solves the issue. This research proposes an algorithm for dealing with invisible prime tasks. The proposed algorithm contains rules and equations utilizing probability of state transition of Coupled Hidden Markov and double time stamped in event logs. The rules and equations are used for determining invisible prime tasks and parallel control flows patterns. In addition to dealing with invisible prime tasks, the experiment results also show that the proposed algorithm obtains right parallel control flow patterns from non complete event logs. This proposed algorithm also decreases usage of the invisible prime task in A# algorithm without reducing the quality of discovered process models. It has proven with the fitness of process models obtained by the proposed algorithm are relatively high as those obtained by A# algorithm.
Analysing the drivers for early contractor involvement adoption by construction clients

The use of a relationship based procurement method is promoted by many authors in the past few years. The construction industry is encouraged to adopt a relational contract in an effort to overcome its perceived problems prevailing in the industry. Despite a number of benefits proposed for the adoption of a relationship based delivery method, the decision to select such a method should be made wisely, and clients should have adequate understanding about the strength and weakness of the method they intend to employ. There are several examples that incorrect selection of a procurement method resulted into value not delivered during the project and the outcomes were below of what it would have achieved by using a traditional type of delivery system. For this reason, this paper focuses on ECI procurement system as one of the relationship based procurement methods. This paper aims at identifying and analysing the particular characteristics of ECI that attract clients to opt for using this method and analysing these drivers in more detail.
Event Detection: Monitoring and Tracking the Dynamics of Social Networks Communities
Venue: 2016 17th IEEE International Conference on Mobile Data Management (MDM)

This paper presents research done towards a robust real time social network text stream event detection system that combines text stream mining and network analysis methods. It presents the current state of the art systems, algorithms, and methodologies to perform event detection in streaming environments: If from the point of view of a natural language processing, text mining, and unsupervised learning the problem of detecting events in unbounded text streams is hard, dealing with dynamic networks with millions of nodes and edges is not also an easy task. Presented contributions and research directions are based on the premise that the precision and accuracy of an event detection algorithm could be improved by considering network properties of the social network when events happen. Network analysis algorithms, specifically algorithms to perform dynamic community detection, community identification and community tracking can be used to extract knowledge from users relations and interactions helping in the task of unveiling and detecting new or unforeseen events.
Alkaline assisted Ni nanocatalysts with largely enhanced low temperature activity toward CO2 methanation

The CO2 methanation reaction is a promising approach for the chemical transformation of carbon dioxide into useful fuels or products. The key challenge at present relies on the design and exploration of non noble metal catalysts so as to achieve high activity at a low reaction temperature. In this work, we have obtained alkaline assisted Ni nanocatalysts supported on Mg/Al mixed metal oxides (denoted as Nix/Mg2 xAl MMO) derived from Ni Mg Al hydrotalcite precursors. The catalytic performance toward CO2 methanation was studied in detail, and the best low temperature reaction activity was obtained over Ni/MgAl MMO (CO2 conversion: 97.9% selectivity: 97.5% 250 degC) By establishing the correlation between the catalytic performance and the alkaline site structure, it is found that the Ni nanoparticles and MgO base sites at the interface serve as dual active centers to cooperatively catalyze CO2 methanation, resulting in low temperature reaction activity. Moreover, in situ diffuse reflectance Fourier transform infrared spectroscopy (in situ DRIFTS) demonstrates that MgO acts as the active site for CO2 activation to give carbonate/hydrocarbonate species, while Ni provides H species for further hydrogenation of intermediates. Therefore, this work rationalizes the significant influence of alkaline assisted Ni nanoparticles on CO2 methanation, which provides a promising heterogeneous catalyst for this reaction.
Sensorimotor Transformations Underlying Variability in Song Intensity during Drosophila Courtship
Venue: Neuron

Diverse animal species, from insects to humans, utilize acoustic signals for communication. Studies of the neural basis for song or speech production have focused almost exclusively on the generation of spectral and temporal patterns, but animals can also adjust acoustic signal intensity when communicating. For example, humans naturally regulate the loudness of speech in accord with a visual estimate of receiver distance. The underlying mechanisms for this ability remain uncharacterized in any system. Here, we show that Drosophila males modulate courtship song amplitude with female distance, and we investigate each stage of the sensorimotor transformation underlying this behavior, from the detection of particular visual stimulus features and the timescales of sensory processing to the modulation of neural and muscle activity that generates song. Our results demonstrate an unanticipated level of control in insect acoustic communication and uncover novel computations and mechanisms underlying the regulation of acoustic signal intensity.
A decentralized vehicle re routing approach using vehicular ad hoc networks
Venue: 2016 Sixteenth International Conference on Advances in ICT for Emerging Regions (ICTer)

Sustainable economic growth and appreciable living standard in a country heavily depend on the reliability and efficiency of its transport infrastructure. One possible way of enhancing the travel experience of commuters is by using intelligent applications in vehicles that communicate through wireless networks. Envisioning these applications to new heights can be achieved with the recent advancements in wireless communication technologies. Vehicular ad hoc networks (VANETs) are a special type of mobile ad hoc networks (MANETs) which can be used to define intelligent interfaces for vehicle to vehicle (V2V) or vehicle to infrastructure (V2I) communication requirements. In this paper, we propose a vehicle rerouting approach for accident situations through VANET scenario simulations. For this research, we have used OMNeT+ network simulator to simulate the mobile network involved and SUMO microscopic traffic simulator to simulate vehicular movements in parallel and Veins framework as a bridging interface between OMNeT+ and SUMO. We have validated our solution with two heterogeneous metropolitan areas with significant structural dissimilarities located in the cities of Kandy and Colombo in Sri Lanka. Our solution achieved lesser values for waiting time and the trip duration of vehicles and qualitatively improving the traffic flow when comparing against the absence of rerouting component.
Proto cooperation: group hunting sailfish improve hunting success by alternating attacks on grouping prey
Venue: Proceedings of the Royal Society B: Biological Sciences

We present evidence of a novel form of group hunting. Individual sailfish (Istiophorus platypterus) alternate attacks with other group members on their schooling prey (Sardinella aurita) While only 24% of attacks result in prey capture, multiple prey are injured in 95% of attacks, resulting in an increase of injured fish in the school with the number of attacks. How quickly prey are captured is positively correlated with the level of injury of the school, suggesting that hunters can benefit from other conspecifics' attacks on the prey. To explore this, we built a mathematical model capturing the dynamics of the hunt. We show that group hunting provides major efficiency gains (prey caught per unit time) for individuals in groups of up to 70 members. We also demonstrate that a free riding strategy, where some individuals wait until the prey are sufficiently injured before attacking, is only beneficial if the cost of attacking is high, and only then when waiting times are short. Our findings provide evidence that cooperative benefits can be realized through the facilitative effects of individuals' hunting actions without spatial coordination of attacks. Such 'proto cooperation' may be the pre cursor to more complex group hunting strategies.
Alternative transit oriented development evaluation in sustainable built environment planning

Following the increase in urban population density and house prices in the 1970s, urban residents began searching for satisfactory living environments. With the construction of highways and advancements in motor vehicle technology, urban development began extending to suburban regions, a phenomenon which is referred to as urban sprawl. The negative external effects caused by urban sprawl, including inefficient land use and pollution, highlight several problems such as the disjunction between urban land use and transportation. To achieve sustainable transportation and resolve the aforementioned problems, we established the transit oriented development (TOD) evaluation criteria and formulated the TOD site selection standard, which fulfills the principle of sustainable transportation. Thus, a solution to problems related to urban sprawl is proposed, which may serve as a reference for planning units in devising relevant processes. The fuzzy Delphi method was adopted to select TOD evaluation criteria satisfying the principle of sustainable transportation, and the fuzzy analytic network process (FANP) was applied to determine the weights of relevant planning criteria. The results show that all nine TOD evaluation criteria for sustainable transportation were supported by an expert consensus in the first phase of the study, indicating that all of the selected criteria were critical in the TOD evaluation. In the second phase, according to the weighted evaluation criteria, the environmental carrying capacity in high density development was the most crucial evaluation criterion, whereas the least critical criterion was equality in residence accessibility. Finally, through the use of a geographical information system, the performance of each station on the Ankeng Line of the New Taipei City mass rapid transit (MRT) system was evaluated according to the TOD evaluation criteria. Combining the evaluation with the weighted sums of the FANP revealed that Xinhe Elementary School MRT station was the optimal station for TOD. Accordingly, built environment planning should be undertaken to develop the urban area surrounding this station. The findings of this study may provide a reference for planning units in undertaking future TOD projects under the principle of sustainable transportation.
Combined Segmentation and Recognition of Online Handwritten Diagrams with High Order Markov Random Field
Venue: 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)

The recognition of online handwritten flowcharts is studied in this work. They are considered as a 2D language with two kinds of primitives: symbols and structural relationships. Three main steps are involved to process this data. They concern i) symbol hypothesis generation, ii) symbol recognition and iii) layout interpretation using grammar description to structure information at the document level. We propose to build a high order Markov random field on stroke level to cope with segmentation and recognition simultaneously. The potential function in our Markov random field is log linear, and we trained it using max margin method. We tested our method on two public handwritten diagram datasets and experiments show that our symbol recognition method's performance has reached state of the art.
Zircons traced from the 700 500 Ma Transgondwanan Supermountains and the Gamburtsev Subglacial Mountains to the Ordovician Lachlan Orogen, Cretaceous Ceduna Delta, and modern Channel Country, central southern Australia

We test the hypothesis that the Transgondwanan Supermountains at the collision of East and West Gondwanaland were the provenance of a vast turbiditic fan that stretched alongside the East Gondwanaland margin to eastern Australia which, in turn, became the provenance of sediment shed into interior Australia to the Cretaceous Ceduna Delta in central southern Australia and the modern Channel Country of central Australia. We employ an integrated analysis (U Pb, Lu Hf isotopes and trace elements) of detrital zircons in the Ceduna Delta and Channel Country. The main properties of the detrital zircons are U Pb ages of 700 500 Ma (model ages TDMC 2.5 1.0 Ga; eHf +10 to 20) and 1300 1000 Ma ages (TDMC 2.7 1.3 Ga; eHf +4 to 17) in hosts of mafic granitoids with alkaline affinity. Zircons with these properties can be traced back through the drainage/paleo slope to the intermediate provenances of the Ordovician turbidites and S type granitoids of the Lachlan Orogen, then up paleoslope to the primary or secondary provenance of the ancestral Gamburtsev Subglacial Mountains, and finally to the primary provenance of the Transgondwanan Supermountains atop the 700 500 Ma East African Antarctic Orogen. Another primary provenance, the 140 95 Ma Whitsunday Volcanic Province/New Caledonia arc in northeastern Australia, also shed sediment across Australia to the Ceduna Delta. We suggest that the primary sediment from the 700 500 Ma East African Antarctic Orogen and the ancestral Gamburtsev Subglacial Mountains was shed into a deep sea super fan to (1) Ordovician turbidites in southeast Australia, recycled by melting of the turbidites to (2) 450 Ma S type granites in the Lachlan Orogen, and (3) finally deposited, together with volcanogenic sediment from northeast Australia, in the Ceduna Delta. Zircons in the Channel Country and the Ceduna Delta have essentially the same properties, and indicate that the northeastern Australian provenance was largely unchanged over the past 100 Ma.
On Discrimination Discovery Using Causal Networks
Venue: SBP BRiMS

Discrimination discovery is an increasingly important task in the data mining field. The purpose of discrimination discovery is to unveil discriminatory practices on the protective attribute (e.g. gender) by analyzing the dataset of historical decision records. Different types of discrimination have been proposed in the literature. We aim to develop a framework that is able to deal with all types of discrimination. We make use of the causal networks, which effectively captures the existence of discrimination patterns and can provide quantitative evidence of discrimination in decision making. In this paper, we first propose a categorization for various discrimination. Then, we present our preliminary results on four types of discrimination, namely system level direct discrimination, the system level indirect discrimination, group level discrimination, and individual level discrimination. We have conducted empirical assessments on real datasets. The results show great efficacy of our approach.
SAR ATR by a combination of convolutional neural network and support vector machines
Venue: IEEE Transactions on Aerospace and Electronic Systems

A combination of a convolutional neural network, which belongs to the deep learning research field, and support vector machines is presented as an efficient automatic target recognition system. Additional training methods that incorporate prior knowledge to the classifier and further improve its robustness against imaging errors and target variations are also presented. These methods generate artificial training data by elastic distortion and affine transformations that represent typical examples of image errors, like a changing range scale dependent on the depression angle or an incorrectly estimated aspect angle. With these examples presented to the classifier during the training, the system should become invariant against these variations and thus more robust. For the classification, the spotlight synthetic aperture radar images of the moving and stationary target acquisition and recognition database are used. Results are shown for the ten class database with a forced decision classification as well as with rejection class.
Cellular Ontogeny and Hierarchy Influence the Reprogramming Efficiency of Human B Cells into Induced Pluripotent Stem Cells
Venue: Stem cells

Although B cells have been shown to be refractory to reprogramming into pluripotency, induced pluripotent stem cells (iPSCs) have been very recently generated, at very low efficiency, from human cord blood (CB) and peripheral blood (PB) derived CD19+CD20 B cells using nonintegrative tetracistronic OSKM expressing Sendai Virus (SeV) Here, we addressed whether cell ontogeny and hierarchy influence the reprogramming efficiency of the B cell compartment. We demonstrate that human fetal liver (FL) derived CD19 B cells are 110 fold easier to reprogram into iPSCs than those from CB/PB. Similarly, FL derived CD34+CD19 B progenitors are reprogrammed much easier than mature B cells (0.46% vs. 0.11% All FL B cell iPSCs carry complete VDJH rearrangements while 55% and 45% of the FL B progenitor iPSCs carry incomplete and complete VDJH rearrangements, respectively, reflecting the reprogramming of developmentally different B progenitors (pro B vs. pre B) within a continuous differentiation process. Finally, our data suggest that successful B cell reprogramming relies on active cell proliferation, and it is MYC dependent as identical nonintegrative polycistronic SeV lacking MYC (OSKL or OSKLN) fail to reprogram B cells. The ability to efficiently reprogram human fetal primary B cells and B precursors offers an unprecedented opportunity for studying developmental B lymphopoiesis and modeling B cell malignances. Stem Cells 2016;34:581 587
Complexity theory and financial regulation
Venue: Science

Economic policy needs interdisciplinary network analysis and behavioral modeling Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial markets. Concepts, such as tipping points, networks, contagion, feedback, and resilience have entered the financial and regulatory lexicon, but actual use of complexity models and results remains at an early stage. Recent insights and techniques offer potential for better monitoring and management of highly interconnected economic and financial systems and, thus, may help anticipate and manage future crises.
Complexity and Economic Policy: A Paradigm Shift or a Change in Perspective? A Review Essay on David Colander and Roland Kupers's Complexity and the Art of Public Policy

In their recent book, Colander and Kupers (2014) argue that viewing the economy as a complex adaptive system should change the way in which we make economic policy. This would necessitate a paradigm shift. Economics has, over time, tried to produce a coherent model to underpin the dominant laissez faire liberal approach. But we have never proved, in that model, that left to their own devices, the participants in an economy will self organize into a satisfactory state. This is an assumption. Complex interactive systems with direct interaction between heterogeneous agents may show no tendency to self equilibrate and will undergo endogenous crises. Economists should concentrate on the emergence of certain patterns. Colander and Kupers suggest that we may be able to nudge the system into "good" basins of attraction. A more radical view is that there are no fixed basins of attraction; these change with the evolution of the system and it is illusory to believe that we can choose good basins. We may be able to recognize and influence the emergence of certain states of the economy, but we are far from Leon Walras's dream of economics as a science like astrophysics.