Miracle-dz/UniFAR-FTUs huggingface dataset:
Gestures without Libraries , Toolkits or Training : A $ 1 Recognizer for User Interface Prototypes

Although mobile, tablet, large display, and tabletop computers increasingly present opportunities for using pen, finger, and wand gestures in user interfaces, implementing gesture recognition largely has been the privilege of pattern matching experts, not user interface prototypers. Although some user interface libraries and toolkits offer gesture recognizers, such infrastructure is often unavailable in design-oriented environments like Flash, scripting environments like JavaScript, or brand new off-desktop prototyping environments. To enable novice programmers to incorporate gestures into their UI prototypes, we present a “$1 recognizer” that is easy, cheap, and usable almost anywhere in about 100 lines of code. In a study comparing our $1 recognizer, Dynamic Time Warping, and the Rubine classifier on user-supplied gestures, we found that $1 obtains over 97% accuracy with only 1 loaded template and 99% accuracy with 3+ loaded templates. These results were nearly identical to DTW and superior to Rubine. In addition, we found that medium-speed gestures, in which users balanced speed and accuracy, were recognized better than slow or fast gestures for all three recognizers. We also discuss the effect that the number of templates or training examples has on recognition, the score falloff along recognizers’ N-best lists, and results for individual gestures. We include detailed pseudocode of the $1 recognizer to aid development, inspection, extension, and testing. ACM Categories & Subject Descriptors: H5.2. [Information interfaces and presentation]: User interfaces – Input devices and strategies. I5.2. [Pattern recognition]: Design methodology – Classifier design and evaluation. I5.5. [Pattern recognition]: Implementation – Interactive systems. General Terms: Algorithms, Design, Experimentation, Human Factors.
Fusion of data- and model-driven discovery Question addressed: Convergence of data- and model-driven discovery

Scientiﬁc thesis. Scientiﬁc discovery has been spearheaded by experimental data (data analysis) and numerical simulations for almost seven decades, typically through a sequential process that decouples the data and model. This approach can be slow, however, and reconciling observational and simulation data tends to become intractable for large-scale complex systems as inevitable divergence occurs. The amount of available observational data, modeling sophistication, and computational resources in the DOE scientiﬁc ecosystem now creates the perfect opportunity to explore an integrated approach in order to accelerate scientiﬁc discovery. In this approach observational and simulation data are continuously integrated. This entails a challenging process but not completely new patterns. Similar strategies include solving inverse problems [7], optimal control [6, 5], or data assimilation [1] that fall under the wide umbrella of uncertainty quantiﬁcation (UQ) [12]. In some sense UQ covers this aspect. However, UQ is generally viewed as a stand-alone activity, detached from, say, ﬂuid dynamics or materials science. An integrated “simulation and data” approach prompts a continuous interaction of application scientists, applied mathematicians, statisticians, and computational scientists at foundational, algorithmic, and hardware and software levels.
TRECVID 2012 - An Overview of the Goals, Tasks, Data, Evaluation Mechanisms and Metrics

The TREC Video Retrieval Evaluation (TRECVID) 2012 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in content-based exploitation of digital video via open, metrics-based evaluation. Over the last ten years this effort has yielded a better understanding of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. TRECVID is funded by the NIST and other US government agencies. Many organizations and individuals worldwide contribute significant time and effort.
Maia: A Language for Mandatory Integrity Controls of Structured Data

The integrity of systems files is necessary for the secure functioning of an operating system. Integrity is not generally discussed in terms of complete computer systems. Instead, integrity issues tend to be either tightly coupled to a particular domain (e.g. database constraints), or else so broad as to be useless except after the fact (e.g. backups). Often, file integrity is determined by who modifies the file or by a checksum. This paper focuses on a general model of the internal integrity of a file. Even if a file is modified by a subject with trust or has a valid checksum, it may not meet the specification of a valid file. An example would be a password file with no user assigned a user id of 0. In this paper, we describe a language called Maia that provides a means to specify what the contents of a valid file should be. Maia can be used to specify the format and valid properties of system configuration files, PNG files and others. We give a structural operational semantics of Maia and discuss an initial implementation within a mandatory integrity system.
Learning Functionally Decomposed Hierarchies for Continuous Navigation Tasks

Solving long-horizon sequential decision making tasks in environments with sparse rewards is a longstanding problem in reinforcement learning (RL) research. Hierarchical Reinforcement Learning (HRL) has held the promise to enhance the capabilities of RL agents via operation on different levels of temporal abstraction. Despite the success of recent works in dealing with inherent nonstationarity and sample complexity, it remains difficult to generalize to unseen environments and to transfer different layers of the policy to other agents. In this paper, we propose a novel HRL architecture, Hierarchical Decompositional Reinforcement Learning (HiDe), which allows decomposition of the hierarchical layers into independent subtasks, yet allows for joint training of all layers in end-to-end manner. The main insight is to combine a control policy on a lower level with an image-based planning policy on a higher level. We evaluate our method on various complex continuous control tasks for navigation, demonstrating that generalization across environments and transfer of higher level policies can be achieved. See videos https://sites.google. com/view/hide-rl.
3 Metamodelling State of the Art and Research Challenges

This chapter discusses the current state of the art, and emerging research challenges, for metamodelling. In the state-of-the-art review on metamodelling, we review approaches, abstractions, and tools for metamodelling, evaluate them with respect to their expressivity, investigate what role(s) metamodels may play at run-time and how semantics can be assigned to metamodels and the domain-specific modeling languages they could define. In the emerging challenges section on metamodelling we highlight research issues regarding the management of complexity, consistency, and evolution of metamodels, and how the semantics of metamodels impacts each of these. 3.1 Metamodelling: State of the Art Models are powerful tools to express the structure, behavior, and other properties in mathematics, each of the hard sciences and in all areas of engineering. While models are very common, an explicit definition of a modelling language and an explicit manipulation of its models is tightly connected to computer based tools. Additional power can be gained by explicit definition and computer based manipulation of models e.g. in CAD, control engineering, algebraic mathematics and of course computer science. To be able to manipulate models, their language needs to be specified as model of these models—metamodels. In this section, we describe the state of the art for metamodelling, including the metamodelling of data structures, as well as the metamodelling of languages systems where appropriate. 3.1. 1 Concepts in Metamodelling Metamodelling (literally, “beyond Modelling”) is the Modelling of models. In their most common use, metamodels describe the permitted structure to which models must adhere [1]; although out of the scope of this chapter, meta-metamodels formally describe metamodels, as they define the core abstractions H. Giese et al. (Eds.): MBEERTS, LNCS 6100, pp. 57–76, 2010. Springer-Verlag Berlin Heidelberg 2010 www.se-rwth.de/publications 58 J. Sprinkle et al. permitted in metamodelling. In fact, some metamodelling languages are selfdescriptive [2, 3]. A metamodel therefore describes the syntax of the models [4]. Through various extension mechanisms and additional rules with this representation of the syntax of models metamodels can also help to define the semantics of models, as we discuss later. The layered approach to modelling (through metamodelling) is depicted in Figure 3.1. Model Metamodel Meta-metamodel Semantic Artifacts (e.g., code, simulation) defines
Applications and physicochemical characterization of nanomaterials in environmental, health, and safety studies

As commercially manufactured nanomaterials become more commonplace, they have the potential to enter ecological and biological environments during their lifecycle of production, distribution, use or disposal. Despite rapid advances in the production and application of nanomaterials, little is known about how they may interact with the environment or affect human health. This research investigates an environmental application of nanomaterials and characterizes physicochemical properties of commonly manufactured nanomaterials in environmental, health, and safety studies. Characterization of nanomaterials for applications and environmental health and safety studies is essential in order to understand how physicochemical properties correlate with chemical, ecological, or biological response or lack of response. Full characterization includes determining the bulk (shape, size, phase, electronic structure and crystallinity) and surface (surface area, arrangement of surface atoms, surface electronic structure, surface composition and functionality) properties of nanomaterials. This work investigates the selective catalytic reduction (SCR) of NO2 to N2 and O2 with ammonia on nanocrystalline NaY, Aldrich NaY and nanocrystalline CuY using in situ Fourier transform infrared (FTIR) spectroscopy. The kinetics of SCR were 30% faster on nanocrystalline NaY compared to commercial NaY due to an increase in external surface area and external surface reactivity. Nanocrystalline CuY showed an additional increase in the rate of SCR as well as distinct NO2 and NH3 adsorption sites associated with the copper cation. These superior de-NOx materials could contribute to a cleaner environment.
Dietary macroalgae Chaetomorpha linum supplementation improves morphology of small intestine and pectoral muscle, growth performance, and meat quality of broilers

Background and Aim: Over the last decades, the poultry industry has experienced steady growth. Although the industry is gradually expanding in Indonesia, poultry feed production has always been expensive. There is a need to study alternative ingredients to obtain affordable feed from natural resources. Chaetomorpha linum (CL) is an abundant macroalgae available throughout the year in Indonesia. This study aimed to determine the effect of CL on the histological structure of the small intestine, pectoralis muscle, growth performance, and meat quality of broilers. Materials and Methods: This study used 300-day-old chick (DOC) male broilers that were reared until they were 21 days old. This study used a completely randomized design with four treatment groups and five replications, and each replication group contained 15 DOC individuals. The treatment groups consisted of Control (CON), CON basal feed (BF), CL1 (0.75%/kg BF), CL2 (1.5%/kg BF), and CL3 (3%/kg BF) groups. The histological structure of the small intestine, pectoralis muscle, growth performance, and meat quality of the broiler was examined. Results: Small intestine and pectoral muscle histomorphology, growth performance, and meat quality were significantly improved in the CL2 (1.5%) and CL3 (3%) groups compared with the CL1 (0.75%) and CON groups. Conclusion: Dietary CL supplementation ameliorates small intestine and pectoral muscle histomorphology, growth performance, and meat quality of broilers. Keywords: Chaetomorpha linum, growth performance, pectoral muscle, small intestine, water-holding capacity.
Integration of upward GPR and water content reflectometry to monitor snow properties

We adopt upward ground-penetrating radar (up-GPR) and water content reflectometry sensors to monitor the seasonal behaviour of snow density. Upward ground-penetrating radar permitted to observe at a single fixed station the time-lapse response of the electromagnetic signal at the main frequency of 1500 MHz, with the antenna radiating upward from the soil toward the snow surface. Measurements have been performed in a test site on Italian Alps (at an elevation of about 2100 m above sea level) during the 2014–2015 winter season at an interval of 30 minutes. The data processing of radar data involved the travel-time picking and the conversion into snow depth and density. Water content reflectometry measurements have been useful in order to calibrate the radar response and retrieve information on the presence of liquid water content. The integration of upward ground-penetrating radar and water content reflectometry technology allows us to infer snow high and layering, snow density changes during the winter season, and a preliminary estimate of the liquid water content. For snow in dry condition, we are able to estimate density values through mixing rules or polynomial formula. Snow density varies during the season in a range between 250 kg/m3 and 450 kg/m3; the results are in good agreement with the results of the ground truth. For snow in wet condition, the residuals of the electrical permittivity, after a trend removal on the original water content reflectometry data, permitted to estimate liquid water content in the range between 3% and 5%, during some periods of the winter season, according to warmer climate condition. Snow layering and densification processes are monitored by the response of upward groundpenetrating radar: fast phenomena such as wetting front infiltration can be also pointed out even if they appear challenging if other observations are not available (e.g., monitoring with water content reflectometry).
Practical modelling of tidal propagation under fluvial interaction in the Mekong Delta

ABSTRACT Estuarine/river engineers often encounter a problem that it is hard to specify an upstream boundary of a delta in the numerical modeling because of lack of good quality discharge data. This paper proposes a practical procedure to simulate tidal propagation and damping over a river stretch using a commonly used shallow-water equation model without imposing an upstream discharge boundary. The interaction between tides and river flows could be easily evaluated by applying seasonally-varying Manning’s n friction values. The Hau River, one of the main streams of the Mekong River, is studied by analyzing water levels measured at three different locations in the estuary. The nearly straight-line geometry of the Hau River allows us to neglect flood plain sinuosity, making it possible to extract tidal damping induced purely by fluvial influence. A series of analyses, including spectrum analysis and hydrodynamic simulation, suggests that tidal damping in the estuary of the Mekong Delta can be readily reproduced using the numerical model with Manning’s n values of 0.025–0.032 [s m−1/3] for the flood season and 0.018–0.025 for the dry season. The present study demonstrates that changes in Manning’s n value according to river flow conditions result in more reliable estimations than simply using a constant value throughout the year. The proposed procedure will be of great benefit not only for tidal modeling but also river and urban flood simulations, saline intrusion modeling and sea-level rise projections in the estuary of the Mekong River.
Leveraging Neurospora crassa Fungus and Carboxypeptidase A1 Enzyme to Illuminate Microscale Biodiversity Changes in Response to Global Shifts

The profound impacts of global changes on biodiversity necessitate a more comprehensive documentation, particularly at the microscale level. To achieve precise and rapid insights into this unique diversity, the choice of an ideal species candidate is crucial. Neurospora crassa, a well-established organism in the field of biology, emerges as a promising candidate for this purpose. In our study, we explore the potential of the Carboxypeptidase A1 (CPA1) enzyme as a valuable tool for profiling global diversity. Our investigation has revealed that CPA1 possesses distinctive characteristics, notably its conserved solvent accessibility. This unique feature makes CPA1 an invaluable asset for microscale studies of global changes. The insights presented in our study serve as a practical blueprint, showcasing the application of structural biology in understanding diversity and global changes within microscale environments.
Evidence of New Particle Formation Within Etna and Stromboli Volcanic Plumes and Its Parameterization From Airborne In Situ Measurements

Volcanic emissions can significantly affect the Earth's radiation budget by emitting aerosol particles and gas‐phase species that can result in the new particle formation (NPF). These particles can scatter solar radiation or modify cloud properties, with consequences on health, weather, and climate. To our knowledge, this is the first dedicated study detailing how gas‐phase precursors emitted from volcanic plumes can influence the NPF. A series of airborne measurements were performed around the Etna and Stromboli volcanoes within the framework of the CLerVolc and STRAP projects. The ATR‐42 aircraft was equipped with a range of instrumentation allowing the measurement of particle number concentration in diameter range above 2.5 nm and gaseous species to investigate the aerosol dynamics and the processes governing the NPF and their growth within the volcanic plumes. We demonstrate that NPF occurs within the volcanic plumes in the free troposphere (FT) and boundary layer (BL). Typically, the NPF events were more pronounced in the FT, where the condensational sink was up to two orders of magnitude smaller and the temperature was ~20 °C lower than in the BL. Within the passive volcanic plume, the concentration of sulfur dioxide, sulfuric acid, and N2.5 were as high as 92 ppbV, 5.65 × 108 and 2.4 × 105 cm−3, respectively. Using these measurements, we propose a new parameterization for NPF rate (J2.5) within the passive volcanic plume in the FT. These results can be incorporated into mesoscale models to better assess the impact of the particle formed by natural processes, that is, volcanic plumes, on climate.
Magnetic Ordering in Layered Magnets

We study the influence of gradients in the inherent ordering temperature of coupled layered magnets on the overall magnetic ordering. The gradients were accomplished by growing Fe(001) layers with thicknesses ranging from two to three monolayers, all separated by seven monolayers of V(001). Two types of gradient superstructures were grown: one with the highest and one with the lowest inherent ordering temperature in the center of the samples. The superstructure with the thinnest outermost Fe layers exhibits lower ordering temperature, demonstrating the importance of the sequence of the layers. Both these structures order at temperatures significantly lower than a superlattice with a constant thickness of the Fe layers (three monolayers). The results highlight the intricate collective aspects of the magnetic ordering in layered magnets, which are not captured by current models in magnetism research.
Environmental and Demographic Effects on Vector Borne Disease Incidence: Welfare Role on DHF Reduction

Many regions in developing countries are transitioning to an industrial economic model, accompanied by rapid population growth, which from one side is a welfare driver (WLF) and on the other side is a demographic pressure, especially a health problem such as vector-borne disease. The problem climaxes when this transition is always accompanied by environmental degradation (ENV), which begins with deforestation. Objective: [1] Determine the direct influence of: [1a] Demographic on DHF incidence, [1b] Demographic on Welfare improvement, [1c] Welfare on DHF incidence, [1d] Environment improvement on DHF incidence, [1e] Environment improvement on performance Welfare; and [2] The indirect influence of Welfare in mediating [2a] Demographic pressure and [2b] Environment improvement on DHF incidence. Research Method: Lampung Province was used as the research locus. Forest Resources Inventory Laboratory of Lampung University as a place for analysis. Postulate SEM (Structural Equation Model) was employed at a 95% confidence level. The endogenous variable was vector-borne disease (reflected by DHF incidence). The two exogenous variables were DMG (reflected by population density and the proportion of age of productive, industrial, and service workers) and ENV (reflected by maximum & minimum air temperature, forested areas, and other land uses). The mediating variable is WLF (reflected by poverty and HDI). Findings: [1] Directly, with a significant effect: [1a] DMG pressure increases DHF (P=0.000) and [1.b] WLF (P=0.000); [1.c] Environment improvement increases welfare (P=0.000) while [1d] reduces DHF; and [1.e] WLF improvement can reduce DHF (P=0.010) and [2] The role of WLF improvement [2a] can significantly reduce the incidence of DHF due to demographic pressure (P=0.007) while also [2b] amplifying environmental improvement in reducing DHF significantly (P=0.023). Novelty:To reduce DHF incidence, Welfare improvement can reverse the negative effects of Demographic pressure as well as act as an amplifier for the role of environmental improvement. Doi: 10.28991/HEF-2024-05-01-03 Full Text: PDF
Nutritional, functional and sensory evaluation of flaxseed-enriched cupcakes

Purpose: Snacking is quite a common preference in this busy world. Increasing the availability of healthier snack alternatives might help consumers view snacks as foods that support health. Design/Methodology/Approach: The current experimental study aimed to determine the nutritional, functional and sensory properties of home-baked cupcakes encouraged with six variants with indigenous flaxseed flour (FF) and flaxseed oil (FO) in 10, 15 and 30% of batter substitution. A one-way ANOVA, least significant difference and Pearson’s correlation were applied using IBM SPSS version 21.0. Findings: Proximate analysis indicated an increase in ash, fiber and protein contents as compared to the standard formulation. The highest ash (1.91±0.26%), fiber (1.09±0.01%) and protein contents (3.08±0.30%) were observed in the sample FF30 (30% flaxseed flour). The cupcakes with 30% flaxseed oil had a significantly greater fat content (35.91±0.55%) and hence a total calorie value of 221.00±3.17%. Antioxidant activity and phenol content of fortified cupcakes ranged from 32.88–76.02% and 22–80 mgGAE/100 gms respectively. The sensory evaluation proved FF15 and FO30 to be the most acceptable recipes. Conclusion: Minor recipe alterations to snacks may yield large and long-term health benefits especially promoting immunity and reducing the risk of inflammatory chronic illnesses. Flaxseed oil might be used in snacks substituting for other vegetable oils to enhance the essential fatty acid content without compromising its acceptability. New formulations could therefore be tested to develop foods fortified with higher proportions of functional and nutritious ingredients especially given the ever-increasing prevalence of chronic illnesses.
Pencil beam scanning proton therapy: the significance of secondary particles

xiii Acknowledgements . xvii Contribution of Collaborators . xix Publication List . xx Conference Presentations . xxi Invited Talks . xxiii List of Abbreviations . xxiv