Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Using Gameplay Videos for Detecting Issues in Video Games

Context. The game industry is increasingly growing in recent years. Every day, millions of people play video games, not only as a hobby, but also for professional competitions (e.g., e-sports or speed-running) or for making business by entertaining others (e.g., streamers). The latter daily produce a large amount of gameplay videos in which they also comment live what they experience. Since no software and, thus, no video game is perfect, streamers may encounter several problems (such as bugs, glitches, or performance issues). However, it is unlikely that they explicitly report such issues to developers. The identified problems may negatively impact the user's gaming experience and, in turn, can harm the reputation of the game and of the producer. Objective. We aim at proposing and empirically evaluating GELID, an approach for automatically extracting relevant information from gameplay videos by (i) identifying video segments in which streamers experienced anomalies; (ii) categorizing them based on their type and context in which appear (e.g., bugs or glitches appearing in a specific level or scene of the game); and (iii) clustering segments that regard the same specific issue. Method. We will build on top of existing approaches able to identify videos that are relevant for a specific video game. These represent the input of GELID that processes them to achieve the defined objectives. We will experiment GELID on several gameplay videos to understand the extent to which each of its steps is effective.
New semionotiform (Actinopterygii: Neopterygii) from the Late Jurassic of southern Germany

We report on a new semionotiform taxon, Scheenstia zappi gen. et sp. nov., from Schamhaupten in the Late Jurassic limestones of the Franconian and Swabian Alb, southern Germany. Although the taxon is so far represented by a single specimen, excellent preservation allows a detailed description of its skeletal anatomy. Scheenstia zappi is distinguished by the presence of a sensory canal in the supraorbital bones and a saddle-like articular surface in the quadratojugal, both features so far unknown in other semionotiforms. The new taxon is further diagnosed by a unique combination of characters: more than three pairs of extrascapular bones; frontals less than three times longer than their maximal width; semitritorial dentition; four anterior infraorbitals; middle pit line contained in a groove in the dermopterotic and parietal; concave posterior border of the angular, robust bugle-like process of the posttemporal bone; large basal fulcra; eleven fin rays in the lower lobe of the caudal fin (below the lateral line); and a first, scale-like caudal fin ray reduced. Among semionotiforms it most closely resembles Lepidotes, in particular the large tritorial forms of the Late Jurassic and Early Cretaceous of Europe, such as L. mantelli, L. maximus and L. laevis. The peculiar shape of the quadratojugal in Scheenstia zappi resembles the condition in some basal teleosts in which a ventral articular surface of the quadrate probably served in the rotation of the lower jaw.
IDENTIFICATION AND MEASUREMENT OF MINING SUBSIDENCE WITH SAR INTERFEROMETRY: POTENTIALS AND LIMITATIONS

This work presents some conclusions regarding the operational use of SAR Interferometry over one of the biggest in Europe coal-mining field of Upper Silesia in Poland. The Upper Silesian Coal Basin (USCB) covers an area of about 7250 km 2 . Mining activity of Carboniferous hard coal deposits has been carried out here for over 200 years. As a result, the region becomes highly urbanized, industrialized and thus environmentally degraded. At present there are 39 active coalmines in the Polish part of the basin. However, because of restructurization of Polish industry, the significant number of the coalmines is going to be liquidated. Since 1998 the 50 ERS SAR scenes over Upper Silesia have been analyzed and processed. As the result of this study the interferogams of variable baselines (between 0 to 431 m) have been successfully generated using 2-pass, 3-pass and 4-pass approaches. Detailed analysis of these data demonstrates that SAR interferograms contain two types of information: quantitative information concerning the rate of subsidence during a period between repetitive ERS SAR acquisitions and qualitative information regarding the shape and extent of subsided area.
Online Learning in The Manifold of Low-Rank Matrices

When learning models that are represented in matrix forms, enforcing a low-rank constraint can dramatically improve the memory and run time complexity, while providing a natural regularization of the model. However, naive approaches for minimizing functions over the set of low-rank matrices are either prohibitively time consuming (repeated singular value decomposition of the matrix) or numerically unstable (optimizing a factored representation of the low rank matrix). We build on recent advances in optimization over manifolds, and describe an iterative online learning procedure, consisting of a gradient step, followed by a second-order retraction back to the manifold. While the ideal retraction is hard to compute, and so is the projection operator that approximates it, we describe another second-order retraction that can be computed efficiently, with run time and memory complexity of O ((n + m)k) for a rank-k matrix of dimension m x n, given rank-one gradients. We use this algorithm, LORETA, to learn a matrix-form similarity measure over pairs of documents represented as high dimensional vectors. LORETA improves the mean average precision over a passive- aggressive approach in a factorized model, and also improves over a full model trained over pre-selected features using the same memory requirements. LORETA also showed consistent improvement over standard methods in a large (1600 classes) multi-label image classification task.
LifeCLEF Bird Identication Task 2014

The LifeCLEF bird identiﬁcation task provides a testbed for a system-oriented evaluation of 501 bird species identiﬁcation. The main originality of this data is that it was speciﬁcally built through a citizen science initiative conducted by Xeno-Canto, an international social network of amateur and expert ornithologists. This makes the task closer to the conditions of a real-world application than previous, similar initiatives. This overview presents the resources and the assessments of the task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of ten groups from seven countries and with a total of twenty-nine runs submitted, involving distinct and original methods, this ﬁrst year task conﬁrms the interest of the audio retrieval community for biodiversity and ornithology, and highlights further challenging studies in bird identiﬁcation.
Analyzing the role of service sector on productivity growth across European regions

Service industries play a core role in advanced economies, both from a quantitative a strategic point of view. Traditionally, productivity has been introduced as explaining factor of tertiarization processes in developed economies, while it has been simultaneously assessed that services display lower productivity levels and growth rates than other economic industries. Such a statement is supported initially on the personal nature of many service activities, which makes it difficult to substitute the work for capital and the introduction of technical progress. Nevertheless in recent years many papers and authors have refuted or limited this conventional thesis. This paper focuses on the impact of tertiarization on overall productivity growth at regional level. It departs from the analysis of a sample of regions belonging to 16 European countries (EU-15 except Luxembourg, plus Norway and Switzerland) to show the relationship between structural changes, tertiarization and productivity growth at this level. Data has been extracted from Regional Databases elaborated by Cambridge Econometrics and OECD. The main result is that several service industries have shown dynamic productivity growth rates, contributing more than expected to productivity growth. Lately, a data panel model highlights some additional aspects disaggregating by market and non market services.
Simulation study of IEEE 802.15.4 LR-WPAN for industrial applications

The IEEE 802.15. 4 protocol has become the primary solution for many Low-Rate Wireless Personal Area Network (LR-WPAN) applications. This is especially the case for industrial sensor network applications such as automation control. We contribute to the better understanding of the protocol behavior by presenting a set of results of simulation experiments. Our results outline the capabilities of this protocol in the selected scenarios but also the limitations. In particular, we investigated the dependency of the protocol on protocol-inherent parameters such as the beacon order and the superframe order but also to different traffic load. Our results can be used for planning and deploying IEEE 802.15. 4 based sensor networks with specific performance demands. We put a special focus on application scenarios in industrial sensor network applications. The primary requirements are reduced end-to-end latency and energy consumption. Our studies are based on our new implementation of IEEE 802.15. 4 developed for the simulation framework OMNeT++. Copyright c © 2010 John Wiley & Sons, Ltd.
Statistical Sparse Channel Modeling for Measured and Simulated Wireless Temporal Channels

Time-domain wireless channels are generally modeled by Tapped Delay Line (TDL) model and its variants. These models are not effective for channel representation and estimation when the number of multipath taps is large. Compressive sensing (CS) provides a powerful tool for sparse channel modeling and estimation. Most of the research has been focusing on sparse channel estimation, while sparse channel modeling (SCM) is rarely considered for centimetre-wave channels. In this paper, we investigate statistical sparse channel modeling, using both measured and simulated channels over a frequency range of 6 to 8.5 GHz. We first introduce the triple equilibrium principle to explore the trade-off between sparsity, modeling accuracy, and algorithm complexity in SCM, and provide a methodology for characterizing the sparsity of time-domain channels using single-measurement-vector compressive sensing algorithms. Using mainly the selected wavelet dictionary and various CS reconstruction (aka recovery) algorithms, we then present comprehensive statistical sparse channel models, including channel sparsity, magnitude decaying profile, sparse coefficient distribution and atomic index distribution. Connections between the parameters of conventional TDL and sparse channel models are mathematically established. We also propose three methods for generating simulated channels from the developed sparse channel models, which validates their effectiveness.
Uplink Grant-Free NOMA With Sinusoidal Spreading Sequences

Grant-access based legacy networks are unable to deliver Uplink (UL) dominated sporadic transmission of short packets with low signalling overhead, which are the requirements of Massive Machine Type Communication (mMTC). Hence, grant-free Non-Orthogonal Multiple Access (NOMA) techniques are more suited for mMTC. Due to the inherent sparsity in the user activity pattern in an mMTC system, the existing literature revolves around Compressive Sensing based Multi User Detection (CS-MUD) algorithms, which employ random or Zadoff-Chu spreading sequences for NOMA. In this paper we explore the utility of sinusoidal spreading sequences, which allow some non-iterative algorithms to be employed in the context of active user detection, channel estimation and data detection in a UL grant-free mMTC system. These algorithms do not need prior knowledge about the user behaviour statistics, noise statistics, and the level of sparsity in the user activity, which might be difficult to obtain at the Base Station (BS). We present a comprehensive performance and complexity analysis to assess the feasibility of our proposal. Extensive numerical trials demonstrate the utility of sinusoidal codes for mMTC.
Coproducts of Ideal Monads

The question of how to combine monads arises naturally in many areas with much recent interest focusing on the coproduct of two monads. In general, the coproduct of arbitrary monads does not always exist. Although a rather general construction was given by Kelly [Bull. Austral. Math. Soc. 22 (1980) 1–83], its generality is reflected in its complexity which limits the applicability of this construction. Following our own research [C. Luth and N. Ghani, Lect. Notes Artif. Intell. 2309 (2002) 18–32], and that of Hyland, Plotkin and Power [IFIP Conf. Proc. 223 (2002) 474–484], we are looking for specific situations when simpler constructions are available. This paper uses fixed points to give a simple construction of the coproduct of two ideal monads .
Light‐toned strata and inverted channels adjacent to Juventae and Ganges chasmata, Mars

Light‐toned layered deposits on the plains adjacent to Juventae and Ganges Chasmata have been identified and analyzed with several instruments onboard the Mars Reconnaissance Orbiter, including HiRISE, CTX, and CRISM. Beds exhibit variations in brightness, color, polygonal fracturing, and erosional properties that are not seen in light‐toned layered deposits within the chasmata. At both Juventae and Ganges, the light‐toned layered deposits along the plains have associated features we interpret as fluvial, including sinuous ridges (inverted channels) that exhibit light‐toned layering and an extensive valley system for the Ganges deposit. The strong correlation between the inverted channels and light‐toned layered deposits suggests an association with fluvial‐lacustrine processes, although pyroclastic and eolian activity may also be involved in their emplacement. The identification of potential fluvial‐lacustrine layered deposits and associated valley networks suggests surface water flow in the Valles Marineris region that occurred for sustained periods during the Hesperian (3.7–3.0 Gyr).
Copper–Gold Skarn Mineralization at the Karavansalija Ore Zone, Rogozna Mountain, Southwestern Serbia

Karavansalija ore zone is situated in the Serbian part of the Serbo‐Macedonian magmatic and metallogenic belt. The Cu–Au mineralization is hosted mainly by garnet–pyroxene–epidote skarns and shifts to lesser presence towards the nearby quartz–epidotized rocks and the overlying volcanic tuffs. Within the epidosites the sulfide mineralogy is represented by disseminated cobalt‐nickel sulfides from the gersdorfite‐krutovite mineral series and cobaltite, and pyrite–marcasite–chalcopyrite–base metal aggregates. The skarn sulfide mineralization is characterized by chalcopyrite, pyrite, pyrrhotite, bismuth‐phases (bismuthinite and cosalite), arsenopyrite, gersdorffite, and sphalerite. The sulfides can be observed in several types of massive aggregates, depending on the predominant sulfide phases: pyrrhotite‐chalcopyrite aggregates with lesser amount of arsenopyrite and traces of sphalerite, arsenopyrite–bismuthinite–cosalite aggregates with subordinate sphalerite and sphalerite veins with bismuthinite, pyrite and arsenopyrite. In the overlying volcanoclastics, the studied sulfide mineralization is represented mainly by arsenopyrite aggregates with subordinate amounts of pyrite and chalcopyrite. Gold is present rarely as visible aggregate of native gold and also as invisible element included in arsenopyrite. The fluid inclusion microthermometry data suggest homogenization temperature in the range of roughly 150–400°C. Salinities vary in the ranges of 0.5–8.5 wt% NaCl eq for two‐phase low density fluid inclusions and 15–41 wt% NaCl eq for two‐phase high‐salinity and three‐phase high‐salinity fluid inclusions. The broad range of salinity values and the different types of fluid inclusions co‐existing in the same crystals suggest that at least two fluids with different salinities contributed to the formation of the Cu–Au mineralization. Geothermometry, based on EPMA data of arsenopyrite co‐existing with pyrite and pyrrhotite, suggests a temperature range of 240–360°C for the formation of the arsenopyrite, which overlaps well with the data for the formation temperature obtained through fluid inclusion microthermometry. The sulfur isotope data on arsenopyrite, chalcopyrite, pyrite and marcasite from the different sulfide assemblages (ranging from 0.4‰ to +3.9‰ δ34SCDT with average of 2.29 δ34SCDT and standard deviation of 1.34 δ34SCDT) indicates a magmatic source of sulfur for all of the investigated phases. The narrow range of the data points to a common source for all of the investigated sulfides, regardless of the host rock and the paragenesis. The sulfur isotope data shows good overlap with that from nearby base‐metal deposits; therefore the Cu–Au mineralization and the emblematic base‐metal sulfide mineralization from this metallogenic belt likely share same fluid source.
SRPT Scheduling Discipline in Many-Server Queues with Impatient Customers

The shortest-remaining-processing-time (SRPT) scheduling policy has been extensively studied, for more than 50 years, in single-server queues with infinitely patient jobs. Yet, much less is known about its performance in multiserver queues. In this paper, we present the first theoretical analysis of SRPT in multiserver queues with abandonment. In particular, we consider the [Formula: see text] queue and demonstrate that, in the many-sever overloaded regime, performance in the SRPT queue is equivalent, asymptotically in steady state, to a preemptive two-class priority queue where customers with short service times (below a threshold) are served without wait, and customers with long service times (above a threshold) eventually abandon without service. We prove that the SRPT discipline maximizes, asymptotically, the system throughput, among all scheduling disciplines. We also compare the performance of the SRPT policy to blind policies and study the effects of the patience-time and service-time distributions. This paper was accepted by Baris Ata, stochastic models & simulation.
A new sparse image representation algorithm applied to facial expression recognition

In this paper, we present a novel algorithm for learning facial expressions in a supervised manner. This algorithm is derived from the local non-negative matrix factorization (LNMF) algorithm, which is an extension of non-negative matrix factorization (NMF) method. We call this newly proposed algorithm discriminant non-negative matrix factorization (DNMF). Given an image database, all these three algorithms decompose the database into basis images and their corresponding coefficients. This decomposition is computed differently for each method. The decomposition results are applied on facial images for the recognition of the six basic facial expressions. We found that our algorithm shows superior performance by achieving a higher recognition rate, when compared to NMF and LNMF
Distributed System Fuzzing

Grey-box fuzzing is the lightweight approach of choice for finding bugs in sequential programs. It provides a balance between efficiency and effectiveness by conducting a biased random search over the domain of program inputs using a feedback function from observed test executions. For distributed system testing, however, the state-of-practice is represented today by only black-box tools that do not attempt to infer and exploit any knowledge of the system’s past behaviours to guide the search for bugs. In this work, we present Mallory: the first framework for grey-box fuzz-testing of distributed systems. Unlike popular black-box distributed system fuzzers, such as Jepsen, that search for bugs by randomly injecting network partitions and node faults or by following human-defined schedules, Mallory is adaptive . It exercises a novel metric to learn how to maximize the number of observed system behaviors by choosing different sequences of faults, thus increasing the likelihood of finding new bugs. The key enablers for our approach are the new ideas of timeline-driven testing and timeline abstraction that provide the feedback function guiding a biased random search for failures. Mallory dynamically constructs Lamport timelines of the system behaviour, abstracts these timelines into happens-before summaries , and introduces faults guided by its real-time observation of the summaries. We have evaluated Mallory on a diverse set of widely-used industrial distributed systems. Compared to the start-of-the-art black-box fuzzer Jepsen, Mallory explores 54.27% more distinct states within 24 hours while achieving a speed-up of 2.24 × . At the same time, Mallory finds bugs 1.87 × faster, thereby finding more bugs within the given time budget. Mallory discovered 22 zero-day bugs (of which 18 were confirmed by developers), including 10 new vulnerabilities, in rigorously-tested distributed systems such as Braft, Dqlite and Redis. 6 new CVEs have been assigned.
Improving knowledge management processes: A hybrid positive approach

Purpose – The paper aims to identify and discuss barriers and facilitators to four processes implied in knowledge management (KM; acquisition, creation, sharing, and transfer). Technological, socio‐organizational, and individual barriers and facilitators are considered.Design/methodology/approach – A literature review was carried out. Four databases (ISI Web of Science, EBSCO, Emerald, and ProQuest) were used for identifying relevant papers. The search covered the time period between January 1985 and August 2010.Findings – Factors affecting the four KM processes involve some form of social capital and the interaction between technology and users' needs and activities. In addition to technology and social capital variables, other factors such as leadership, performance‐oriented culture, training and development practices, and T‐shaped skills emerged as relevant for KM processes. The authors conclude that KM thrives in positive organizational contexts and fails when the infrastructure establishing positive .
Litter decomposition dynamics associated with cashew nut plantation in coastal habitat of Orissa, India

Being a key process in nutrient and carbon cycling in coastal ecosystems, decomposition of litter in coastal sand dunes of Orissa was studied in relation to abiotic and biotic factors. Microbial isolation was performed using standard procedures and decomposition of leaf litter was studied using litter bag technique. Higher microbial populations were encountered in soil with cashew plantations compared to barren sand dunes, corresponding with the fluctuation of prevailing temperature and moisture. Micro-fungi of both soils showed a positive correlation with soil moisture but were negatively correlated with soil temperature. A total of 129 species of fungi belonging to 68 genera were enumerated of which sand dune with cashew plantation had a share of 45 genera, 114 spp. and barren sand dune contributed 51 genera and 112 spp. Sand dune without vegetation revealed 32 restricted spp. while Anacardium plantation soil revealed 34 spp. Trichoderma,Aspergillus and Penicillium are predominant occurrence and have been found to be effective decomposers in the present study. Rates of litter loss and carbon dioxide output followed the same trends as the fungal numbers. Shannon- Wiener index and richness were higher in soil with Anacardium plantation than the barren sand dune. Maximum fungal population density was observed in the rainy season followed by winter and summer months. The rate of decomposition was controlled by rainfall, soil temperature, soil moisture, relative humidity and fungal count of soil. This research will help in monitoring the isolation, successful introduction and management of decomposing fungi and their importance in ecosystem service could be a valuable tool for understanding the long term effects of changes in soil condition of the forest floors in coastal sand dunes of Orissa, India. Key words: Decomposition rate, diversity indices, fungi, abiotic factors, soil respiration.