Miracle-dz/UniFAR-FTUs huggingface dataset:
Rainfall partitioning varies across a forest age chronosequence in the southern Appalachian Mountains

Evaporation of precipitation from plant surfaces, or interception, is a major component of the global water budget. Interception has been measured and/or modelled across a wide variety of forest types; however, most studies have focused on mature, second‐growth forests, and few studies have examined interception processes across forest age classes. We present data on two components of interception, total canopy interception (Ei) and litter interception—that is, Oi + Oe horizon layers—(Eff), across a forest age chronosequence, from 2 years since harvest to old growth. We used precipitation, throughfall, and stemflow collectors to measure total rainfall (P) and estimate Ei; and collected litter biomass and modelled litter wetting and drying to estimate evaporative loss from litter. Canopy Ei, P minus throughfall, increased rapidly with forest age and then levelled off to a maximum of 21% of P in an old‐growth site. Stemflow also varied across stands, with the highest stemflow (~8% of P) observed in a 12‐year‐old stand with high stem density. Modelled Eff was 4–6% of P and did not vary across sites. Total stand‐level interception losses (Ei + Eff) were best predicted by stand age (R2 = 0.77) rather than structural parameters such as basal area (R2 = 0.49) or leaf area (R2 < 0.01). Forest age appears to be an important driver of interception losses from forested mountain watersheds even when stand‐level structural variables are similar. These results will contribute to our understanding of water budgets across the broader matrix of forest ages that characterize the modern forest landscape.
Eye-movements as an input in human computer interaction: exploiting natural behaviour

Although techniques of man-machine interaction are becoming more and more sophisticated and resemble natural communication in an increasing way, there is one interaction modality that is nearly entirely neglected in recent developments-hardly any system exploits the user's eye movements for man-machine interaction. This is due to the fact that, in order to use eye movements in man-machine interaction, people have to learn artificial eye movements or use extra input devices to specify the intent of the accompanying eye movement, In the research group M4I of the 'Virtual Knowledge Plant', the authors try to avoid this problem by analysing and integrating the information of all communication channels used in natural communication, i.e. hand and arm gestures, natural language and head and eye movements.
Characterization of bottom sediment resuspension events observed in a micro-tidal bay

Abstract. In this study we investigate the variability in near-bottom turbidity in Alfacs Bay (in the northwestern Mediterranean Sea). The bay is characterized by a micro-tidal environment and seiching activity that may lead to flow velocities of more than 50 cm s−1. A set of current meters and optical sensors were mounted near the sea bottom to acquire synchronous hydrodynamic and optical information from the water column. The time-series observations showed an evident relation between seiche activity and sediment resuspension events. The observations of turbidity peaks are consistent with the node–antinode location of the fundamental and first resonance periods of the bay. The implementation of a coupled wave–current numerical model shows strong spatial variability of the potential resuspension locations. Strong wind events are also a mechanism responsible for the resuspension of fine sediment within the bay. This is confirmed by suspended sediment concentration maps derived from Sentinel-2 satellite imagery. We suggest that the sequence of resuspension events plays an important role in the suspended sediment concentration, meaning that the occurrence of sediment resuspension events may increase the suspended sediment in subsequent events. The suspended sediment events likely affect the ecological status of the bay and the sedimentary process over a long-term period.
Seasonality of archaeal lipid flux and GDGT-based thermometry in sinking particles of high-latitude oceans: Fram Strait (79° N) and Antarctic Polar Front (50° S)

Abstract. The relative abundance of individual archaeal membrane lipids, namely of glycerol dialkyl glycerol tetraethers (GDGTs) with different numbers of cyclopentane rings, varies with temperature, which enables their use as a paleotemperature proxy index. The first GDGT-based index in marine sediments called TEX86 is believed to reflect mean annual sea surface temperature (maSST). The TEX86L is an alternative temperature proxy for “low-temperature” regions (<15 ∘C), where the original TEX86 proxy calibration shows a larger scatter. However, TEX86L-derived temperatures still display anomalous estimates in polar regions. In order to elucidate the potential cause of the disagreement between the TEX86L estimate and SST, we analyzed GDGT fluxes and TEX86L-derived temperatures in sinking particles collected with time-series sediment traps in high-northern- and high-southern-latitude regions. At 1296 m depth in the eastern Fram Strait (79∘ N), a combination of various transporting mechanisms for GDGTs might result in seasonally different sinking velocities for particles carrying these lipids, resulting in strong variability in the TEX86L signal. The similarity of flux-weighted TEX86L temperatures from sinking particles and surface sediments implies an export of GDGTs without alteration in the Fram Strait. The estimated temperatures correspond to temperatures in water depths of 30–80 m, where nitrification might occur, indicating the favorable depth habitat of Thaumarchaeota. In the Antarctic Polar Front of the Atlantic sector (50∘ S), TEX86L-derived temperatures displayed warm and cold biases compared to satellite-derived SSTs at 614 m depth, and its flux-weighted mean signal differs from the deep signal at 3196 m. TEX86L-derived temperatures at 3196 m depth and the surface sediment showed up to 7 ∘C warmer temperatures relative to satellite-derived SST. Such a warm anomaly might be caused by GDGT contributions from Euryarchaeota, which are known to dominate archaeal communities in the circumpolar deep water of the Antarctic Polar Front. The other reason might be that a linear calibration is not appropriate for this frontal region. Of the newly suggested SST proxies based on hydroxylated GDGTs (OH-GDGTs), only those with OH-GDGT–0 and crenarchaeol or the ring index (RI) of OH-GDGTs yield realistic temperature estimates in our study regions, suggesting that OH-GDGTs could be applied as a potential temperature proxy in high-latitude oceans.
Super-resolution reconstruction algorithm based on adaptive convolution kernel size selection

Restricted by the detector technology and optical diffraction limit, the spatial resolution of infrared imaging system is difficult to achieve significant improvement. Super-Resolution (SR) reconstruction algorithm is an effective way to solve this problem. Among them, the SR algorithm based on multichannel blind deconvolution (MBD) estimates the convolution kernel only by low resolution observation images, according to the appropriate regularization constraints introduced by a priori assumption, to realize the high resolution image restoration. The algorithm has been shown effective when each channel is prime. In this paper, we use the significant edges to estimate the convolution kernel and introduce an adaptive convolution kernel size selection mechanism, according to the uncertainty of the convolution kernel size in MBD processing. To reduce the interference of noise, we amend the convolution kernel in an iterative process, and finally restore a clear image. Experimental results show that the algorithm can meet the convergence requirement of the convolution kernel estimation.
Algal Culturing Techniques

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An improved watershed algorithm for image segmentation

Watershed transform is a key operator in image segmentation algorithms. However, the computation load of watershed transform is too large for real-time applications. Previously published watershed segmentation algorithms required at least three global synchronization points: minima detection, labelling and flooding. This paper presented an algorithm of watershed transformation based on opening-closing operation and distance transform. It improved the classical watershed segmentation algorithm based on distance transform, overcoming over segmentation. The experiment result demonstrated that this method for segmentation inherits the advantage of watershed algorithm based on distance transform that it successfully segment out each dowel in the image bringing convenience to computer vision and auto-counting of dowels. It also overcame over-segmentation existed in traditional watershed segmentation preserving the original edges of each dowel in the image completely. This algorithm can be combined with any image segmentation algorithm to give more precise segmentation results. An example is also shown by combining a background registration and changedetection-based segmentation algorithm with Watershed. This new video segmentation algorithm can give accurate object masks with acceptable computation complexity.
Learning Theory and Algorithms for Auctioning and Adaptation Problems

A common assumption in machine learning is that training and testing data are i.i. d. realizations from the same distribution. However, this assumption is often violated in practice: for instance test and training distributions can be related but different such as when training a face recognition system on a carefully curated data set which will be deployed in the real world. As a different example, consider training a spam classifier when the type of emails considered spam changes as a function of time. The first problem described above is known as domain adaptation and the second one is called learning under drifting distributions. The first part of this thesis presents theory and algorithms for these problems. For domain adaptation, we provide tight learning bounds based on the novel concept of generalized discrepancy. These bounds strongly motivate our learning algorithm and it is shown, both theoretically and empirically, that this algorithm can significally improve upon the current state of the art. We extend the theoretical results of domain adaptation to the more challenging scenario of learning under drifting distributions. Moreover, we establish a deep connection between on-line learning and this problem. In particular, we provide a novel on-line to batch conversion that motivates a learning algorithm with excellent empirical performance. The second part of this thesis studies a crucial problem in the intersection of learning and game theory: revenue optimization in repeated auctions. More precisely, we study second-price and generalized second-price auctions with reserve. These auction mechanisms have become extremely popular in recent years due to the advent of online advertisement. Both type of auctions are characterized by a reserve price representing the minimum value at which the seller is willing to forego of the object in question. Therefore, selecting an optimal reserve price is crucial in achieving the largest possible revenue. We cast this problem as a learning problem and provide the first theoretical analysis for learning optimal reserve prices from samples for both second-price and generalized second-price auctions. These results however assume buyers do not react strategically to changes in reserve prices. Therefore, in the last chapter of this thesis we analyze the possible strategies for buyers and show that if the seller is more patient than the buyer, it is not in the best interest of the buyer to behave strategically.
Intelligent Tutoring System for Learning Programming

Tutoring systems for programming help students understand features of target programming languages, and develop their general problem solving skills. Our system guides novices in learning syntax and semantics of programming language, problem decomposition, program design and testing. It is language independent, adjusting automatically course material to the language subject of learning. Semantic analysis of student’s programs is based on comparison of abstract semantics trees of student’s and model-program. Model-program is coded by innovative programming language describing goals and variants of possible solutions. The notional machine defined by programming language, its verbal description of instruction actions and visualization of program execution, helps students to understand semantics of teaching language. Advancement through the course material controlled by computer teacher supports connection of new concepts to the present student’s knowledge. The system applies distinct teaching strategies to stoppers and movers.
Semantic Similarity Computation Based on Multi-Features Fusion

Semantic similarity is a core technique of many NLP research fields. However, stateof-the-art metrics for semantic similarity computation often operate at different levels, e.g., words or sentences. In this paper, semantic similarity computation metrics are firstly introduced and the quality is measured in order to determine their advantages and limitations; then a new semantic similarity metric based on multi-features fusion is proposed. Distributed representations of words are used for alignment-based disambiguation operation, and Wikipedia tags are used to enhance the performance of our approach. The proposed metric is unsupervised, and can be applied at different levels e.g., single words or entire documents. The metric is evaluated on both English and Chinese datasets, it is shown that the precision and recall scores are higher than metrics which simply using knowledge base or distributed representation of words.
Software Design Quality Metrics For Web Based Systems

the internet and the World Wide Web are the most amazing and dynamically growing computer technologies. With the growth of World Wide Web (WWW) the number of Web Based Hypermedia Applications (WBHAs) has also increased at a tremendous rate. A quality application can be produced only through a quality design.For aquality design it is necessary that all its aspects should be measured at the design phase.The existing metrics only cater the aspects of software applications after implementation phase. Many methodologies have been proposed for the web applications design and development. These methodologies do not cover the issues related to security.OODM was also proposed with the objectives of web application development but the security issues were also not covered in this methodology. Furthermore there are no measurements for the design schema and its different models in OODM.Other methodologies are also without this feature. A methodology for the design of a web application has been proposed in this dissertation. Secure Object oriented design methodology (S-OODM) is an extension of the OODM in which security issue has been incorporated in the analysis and design.Metrics for overall design schema and all its models have been proposed and validated through a case study of university web site.The case study shows that application with security constraints can be developed by using this methodology and validation of one design or comparison of different design can be carried out through these metrics.The designer can design a quality design through these metrics and can improve its quality without going on the next phase. Using these metrics the complexity of the design can be reduced.The performance of the design can be measured and hence can be increased.The valuable resources like cost, time and space can be measured and thus can be saved by using the proposed metrics. Navigational time is another feature of the web applications that can be measured and thus the easiest navigational path can be computed by using these metrics.User interaction is important in the web applications and this is also achieved by using the proposed metrics. The metrics provides valuable information about the vital components from the security point of view which help the designer to give a care full attention to the vital components. The methodology, OODM/S-OODM, is believed one of first web application development methodologies.It provides a complete, detailed and step-wise development process. Therefore, it needs to be automated. Work in this direction can be done.There can be another future direction of this work can be to upgrade this methodology (S-OODM) for the development of semantic web applications. It can further be extended for the sub domains as at present it deals with the domains only.
An App-Driven Garbage Collection to Enable Continual Vehicular Sensing in the Android Smartphone Apps

Thanks to their multiple sensors, the Android smartphones have drawn significant attention for supporting vehicular sensing apps. These apps usually require continual sampling of sensors to collect the events of driving. However, the standard garbage collection (GC) of the Dalvik virtual machine blocks these apps from collecting sensing information for hundreds of milliseconds, which leads to the failure of detecting vehicular events. To alleviate this problem, we present a scheme that proactively invokes the appdriven GC to reduce the duration of blocking based on free heap memory ratio or periodic calling. The experimental results show that we can significantly reduce 75% of the blocking time.
MobAppGen: a mobile applications generic framework

The development of mobile telephony, combined to the fact that mobile applications are becoming indispensable for users, has caused that a need of a fast and effective implementation of new services appears. There are tools and kits that facilitate developers' tasks but, considering that in mobile applications there are many concerns that cut across several aspects, the implementation of new applications may result in duplicated code within the same project or in similar ones. The existing way of development is also a tedious and error prone task that may produce hard to maintain applications. To remedy these concerns we propose a framework called MobAppGen which allows code reuse by modularizing mobile applications and that is able to develop client and server sides. In this paper we introduce the framework and we present some examples of its operation.
TIPOLOGI RUMAH JAWA DI KAWASAN PERDESAAN SUMBER POLAMAN LAWANG

The house is a place of living things live. A basic requirement for this stay originated from human shaping social life, to live together and form a pattern settlement. The formation of the villages in the village SumberPolaman, Lawang usually starts from a group of people who form a small village then more and more perfect. This area is shaped and influenced by natural factors as well as the physical expression of the region and culture that has been passed down from generation to generation. The house located in the village of Lawang SumberPolaman generally in the form of a traditional rural home with a simple roof forms that are divided by type and function of each. The wall is in the form of a plank of wood, bamboo and brick wall. While generally still use plaster floor, but there are some homes that already use a ceramic material. The main purpose of writing to determine the typology of residential buildings form the population and settlement patterns that exist in the village SumberPolaman, Lawang. The method used is descriptive method qualitative approach to typology that is the way to describe and classify the various types of data related to residential buildings in the village SumberPolaman, Lawang.
Research on moving target tracking technology based on complex background

With the needs of social development, video tracking based on the algorithm has gradually been in a hot research in the software.CamShift algorithm is a real-time tracking algorithm, using color histogram model get each image frame color projection, and according to previous frame tracking results to adjust the search window positions and sizes, resulting in the current image size and central location of the target.Primarily,this system is a moving object tracking detection system based on CamShift. the system can track moving objects on the indoor environment or to track the moving object in the video stream.
Multi-scale approach to assess the impacts of land use evolution and rainwater management practices on the hydrology of periurban catchments. Application to the Yzeron catchment (150 km 2 )

The anthropogenic influence or " artificialization " generated by land use evolution and water flow paths modifications induces changes in the hydrology of watersheds. To help stakeholders to assess the vulnerability of their territory by addressing different rainwater management and planning issues, a methodology based on a multi-scale distributed hydrological modelling approach is proposed. The objective is to quantify the impact of ongoing urbanization and stormwater management on the long-term hydrological cycle of a medium-sized watershed (150 km 2). The described method relies on several tools and data: a distributed hydrological model adapted to the characteristics of periurban areas, land use and land cover maps from different dates (past, present, future) and information about rainwater management collected from local authorities. The case study area is the Yzeron periurban catchment, located near Lyon (France).
Prediksi Perubahan Penggunaan Lahan dan Pola Berdasarkan Citra Landsat Multiwaktu dengan Land Change Modeler (LCM) Idrisi Selva 17: Studi Kasus Sub-Das Brantas Hulu

Sebagian besar area Sub-DAS Brantas hulu terletak di wilayah administrasi Kota Batu. Tujuan dari penelitian ini adalah untuk menganalisis perubahan penggunaan lahan dari tahun 2001 hingga 2011 dan 2015 serta memprediksinya di tahun 2020 dan 2025. Metode yang digunakan dalam penelitian adalah analisis perubahan penggunaan lahan dari citra landsat 7 ETM+ tahun 2001 dan 2011 untuk memprediksi penggunaan lahan di tahun 2015 yang selanjutnya uji validitas dengan membandingkan peta penggunaan lahan hasil pemodelan dengan peta aktual penggunaan lahan Sub-DAS Brantas Hulu. Perangkat lunak yang digunakan adalah Idrisi Selva 17 dengan instrumen Land Change Modeler (LCM) dengan pemilihan Multi-Layer Perceptron (MLP) yang digunakan untuk mengevaluasi beberapa variabel yang berpengaruh terhadap perubahan penggunaan lahan. Di tahun 2020, didapatkan luas hutan sebesar 8883.19 Ha, luas ladang sebesar 2066.59 Ha, luas sawah sebesar 295.15 Ha, luas pemukiman sebesar 3193,75 Ha, luas tanaman campuran sebesar 5221.73 Ha, dan luas lahan terbuka pada kaldera sebesar 380,96 Ha. Sedangkan di tahun 2025, luas penggunaan lahan berupa hutan sebesar 9134.50 Ha, sedangkan luas penggunaan lahan ladang sebesar 1766,72 Ha, luas sawah sebesar 295,96 Ha, sedangkan luas pemukiman sebesar 3314,97 Ha, luas tanaman campuran sebesar 5147.67 Ha, dan luas lahan terbuka pada kaldera sebesar 380.98 Ha. Faktor pendorong perubahan penggunaan lahan di wilayah penelitian lebih disebabkan oleh jaringan jalan. DOI: http://dx.doi. org/10.17977/um017v22i12017p032