Miracle-dz/UniFAR-FTUs huggingface dataset:
Constrained App Data Caching over Edge Server Graphs in Edge Computing Environment

Edge computing has emerged as a promising paradigm for powering a huge number of applications requiring low latency, e.g., real-time navigation, interactive gaming, virtual or augmented reality, etc. Edge computing offers highly accessible computing and storage resources, including CPU, storage and bandwidth, by deploying edge servers at base stations. With more users accessing edge apps, a huge number of data will be transmitted via edge servers between users’ devices and remote cloud servers. A service provider can cache its app data on edge servers to ensure the low data retrieval latency of its users. Due to the physical size limits of edge servers, the optimal data caching strategy must minimize overall user latency with consideration of constrained cache spaces on edge servers. From the service provider’s perspective, we formulate this Constrained Edge Data Caching (CEDC) problem and prove the NP-hardness of this CEDC problem. After that, we propose CEDC-IP, an optimal approach solved by the Integer Programming technique, to find optimal solutions to this CEDC problem. We also propose CEDC-A, an approximation algorithm with theoretical guarantee, to find approximate solutions to large-scale CEDC problems efficiently. Finally, we conduct extensive experiments on a widely-used real-world data set, and the experimental results demonstrate that both CEDC-IP and CEDC-A significantly outperform the other four representative approaches.
GosperMap: Using a Gosper Curve for Laying out Hierarchical Data.

The emergence of very large taxonomies that result from the increase in available data raises many problems of visualization and navigation through their corresponding hierarchies. On datasets of such scale, classical graph drawing methods do not take advantage of certain human cognitive skills such as shape recognition. In this paper, we propose a method that is based on the use of nested irregular shapes. We name it GosperMap as we rely on the use of a Gosper Curve to generate these shapes. By employing human perception mechanisms that were developed by handling, for example, cartographic maps, this technique facilitates the visualization and navigation of a taxonomy. An algorithm has been designed to preserve region containment according to the taxonomy and to set the leaves' sizes proportionally to a property, in such a way that the size of non-leaf regions corresponds to the sum of their children's sizes. Moreover, the input ordering of the hierarchy's nodes is preserved, i.e., the areas that represent two consecutive children of a node in the hierarchy are adjacent to one another. We illustrate our technique by providing visualization examples of the repartition of tax money in the U.S. over time. Furthermore, we validated the use of the GosperMap in a professional documentation context.
Graphe du Web – Classement de pages webs

This paper addresses the problem of topic distillation on the World Wide Web, namely, given a typical user query to find quality documents related to the query topic. Connectivity analysis has been shown to be useful in identifying high quality pages within a topic specific graph of hyperlinked documents. The essence of our approach is to augment a previous connectivity analysis based algorithm with content analysis. We identify three problems with the existing approach and devise algorithms to tackle them. The results of a user evaluation are reported that show an improvement of precision at 10 documents by at least 45% over pure connectivity analysis.
Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud

For mobile devices used in dynamic networks (that is, with frequent changes in topology due to node failure / unavailability and mobility in a mobile cloud) largely ignored, however, remained challenges in terms of reliability and efficiency. To the best of our knowledge, we can first have to address these challenges in an integrated manner for both data storage and processing in mobile cloud, an approach we call k-out-of-n-Computing. In our solution, mobile devices successfully retrieve or process data in the most energy-efficient manner, as long as k n are accessible from remote servers. Through a real implementation of the system, we demonstrate the feasibility of our approach. the first frame fault tolerant and energy-efficient Remote Storage & processing under a dynamic network topology, that is, to support mobile cloud. Our framework aims, for applications that require an energy-efficient and reliable distributed data storage and processing in a dynamic network. For example, military operations or civil protection. Three famous fault tolerance strategies are initiated in the following formulas to estimate the probability of default of the fault-tolerant modules. In this work, probability of default of a cloud component is described as the probability that precipitates an invocation of this component. The cost of the failure probability is in the range of [0.1]. In particular, we examine how data and processes with k-out such reliability of-n to store the data stored in mobile cloud that: 1) minimizing the energy consumption for distributed data collection; 2) minimizing the energy consumption of distributed data for processing and 3) data processing and dynamic topology changes are taken into account distributed. Scheduling techniques such as the decision set to be taken by scheduling manager, if the assigned node cloud struck leaves two planning techniques. These techniques are: restoration technique and fault tolerance technology.
Interactive comment on “HESS Opinions: A Planetary Boundary on Freshwater Use

I take it that the number of three referee and five short comments is comparatively high, so it might be helpful to sum up some major issues. Before that, I would like to thank, again, all commentators for their contributions. Most notably, I would like to thank Prof. Gerten and Prof. Rockström for taking a stand to defend the freshwater PB. I had the feeling that the tone of the discussion became a bit harsh towards the end, and I might not be entirely blameless in that matter. All the more, I honestly hope that no hard
Reliable, Memory Speed Storage for Cluster Computing Frameworks

Abstract : Tachyon is a distributed file system enabling reliable data sharing at memory speed across cluster computing frameworks. While caching today improves read workloads, writes are either network or disk bound, as replication is used for fault-tolerance. Tachyon eliminates this bottleneck by pushing lineage, a well-known technique borrowed from application frameworks, into the storage layer. The key challenge in making a long-lived lineage-based storage system is timely data recovery in case of failures. Tachyon addresses this issue by introducing a checkpointing algorithm that guarantees bounded recovery cost and resource allocation strategies for recomputation under common resource schedulers. Our evaluation shows that Tachyon outperforms in-memory HDFS by 110x for writes. It also improves the end-to-end latency of a realistic workflow by 4x. Tachyon is open source and is deployed at multiple companies.
Image Contrast Enhancement based Sub-histogram Equalization Technique without Over-equalization Noise

the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.
Performance of ISA Brown commercial layer after forced molting

A total of 29460 ISA Brown commercial layers were force molted with feed restricted (20g to 70g) forced molting method to assess the effects of molting of ISA Brown commercial layers at Valuka Layer Farm-1, C.P. Bangladesh Co., Ltd. Layers were forced molted between 73 to 76 weeks of age. Forced molting made significant differences on egg production. Egg production (77.11%) and egg weight (66.93g) were increased in post molting period than that in pre molting (67.26%) and molting (22.27%) period. The value of egg weight in pre molting period was 65.51g and molting period was 58.25g. During molting period body weight loss was 193.75g. Whereas, in pre molting and after molting period body weight gain were11.25g and 11.00g respectively. Feed conversion (FC) was significant at 1% level of significance (P<0.01). FC was better in post molting period (2.24), moderate in pre molting period (2.67) and worst in molting period (3.33). Mortality was slightly increased in molting period (0.21%) than that of pre molting (0.13%) and post molting (0.13%) period. The result of this experiment may be used to maximize egg production and egg weight in laying hens. Asian Australas. J. Biosci. Biotechnol. 2016, 1 (2), 338-345
Elimination of lexical ambiguities by grammars. The ELAG system

Due to lexical ambiguity, lexical tagging involves some automati c analysis and recognition of grammatical context, e.g. adjective-noun, subject-verb, etc., in order t o check local constraints. Such a short context sensitivity is required, for insta nce, to recognize technical terms in view of an indexation process, and for context-sensitive spel ling checkers. If the lexical tagger is coupled with a syntactic parser, the checki ng of local syntactic constraints and contextual reduction of lexical ambiguity can considerably speed up the rocess, by filtering out invalid analyses before parsing (R. Milne 1986). Dependi ng on systems, local constraint checking is viewed either as a part of lexical tagg ing, since it contributes to selecting tags for words, or as a part of syntactic parsing, since it takes i nto account contextual constraints, or as an intermediate step. In the case of a lexiconbased tagger like INTEX, a contextual constraint checking module can process the result of the t agg r and resolve some lexical ambiguities. In this article, we present a new, INTEX-compatible formalis m of expression of distributional constraints, ELAG (elimination of lexical ambiguiti es by grammars). We describe the main properties of ELAG and we exemplify them wit h simple rules formalizing exploitable constraints. We also present an INTEX-compatible evalua tion procedure for the lexical disambiguation results.
A Rule-based Approach for Anomaly Detection in Subscriber Usage Pattern

detect anomalous telephone calls. The method described here uses subscriber usage CDR (call detail record) data sampled over two observation periods: study period and test period. The study period contains call records of customers' non-anomalous behaviour. Customers are first grouped according to their similar usage behaviour (like, average number of local calls per week, etc). For customers in each group, we develop a probabilistic model to describe their usage. Next, we use maximum likelihood estimation (MLE) to estimate the parameters of the calling behaviour. Then we determine thresholds by calculating acceptable change within a group. MLE is used on the data in the test period to estimate the parameters of the calling behaviour. These parameters are compared against thresholds. Any deviation beyond the threshold is used to raise an alarm. This method has the advantage of identifying local anomalies as compared to techniques which identify global anomalies. The method is tested for 90 days of study data and 10 days of test data of telecom customers. For medium to large deviations in the data in test window, the method is able to identify 90% of anomalous usage with less than 1% false alarm rate.
Uncertainty-aware Decisions in Cloud Computing: Foundations and Future Directions

H M DIPU KABIR, Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Australia. ABBAS KHOSRAVI, Senior Member, IEEE; Associate Professor, Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Australia. SUBROTA K MONDAL , Faculty of Information Technology, Macau University of Science and Technology, Macao, China. MUSTANEER RAHMAN, Faculty of Computer Science and Information Technology, University of Malaya, Malaysia. SAEID NAHAVANDI, Fellow, IEEE; Professor, Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Australia. RAJKUMAR BUYYA, Fellow, IEEE; Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information Systems, The University of Melbourne, Australia.
Permafrost thaw induced changes to runoff generation and hydrologic connectivity in low-relief, discontinuous permafrost terrains

The presence of a talik (perennially thawed feature in a permafrost environment) below the active layer (ground that freezes and thaws annually) has important hydrologic and thermal implications as taliks can provide an active flowpath throughout the year. As taliks do not freeze over winter, they should be distinguished separately from the active layer. In areas of discontinuous permafrost where taliks are prevalent, measuring end of season thaw depth should not be considered a proxy for active layer thickness. At a site in the southern Northwest Territories, Canada, we measured active layer thickness and talik thickness across an ice-cored peat plateau in 2015 and 2016. In both years the average thickness of the active layer was 35 cm and 41 cm respectively, whereas talik thickness was 80 cm and 99 cm. The talik extended the entire width of the plateau and provides a year-round hydrological connection between a flat bog and a channel fen. The presence of a talik will increase the rate of permafrost thaw as it allows for greater advection of energy through this feature. As the active layer thaws in the spring, a two-layered flow system develops as snowmelt water flows over the frozen portion of the active layer of plateaus into adjacent wetlands, and stored water from the plateau is also routed through the unfrozen, saturated talik. This two-layered system continues until the entire active layer thaws. Flow through the talik is limited by the low hydraulic conductivity of deep peat (~ 3.5 m day), but as it persists throughout the year it amounts to ~10% of total runoff from the plateau.
Available online through www.ijma.info

------------------------------------------------------------------------------------------------------------------------------------------------ ABSTRACT T his research paper discusses the concept of M-data with reference to health care sector. Thereafter the concept of M-information is introduced including definitions, examples, nature, uses and extraction techniques. M-information can be extracted using algorithms, artificial neural networks, heuristics, data models, decision support systems, models etc. But this current paper is based on a CASE study that utilizes Queuing model. This leads to conceptual information that is represented as a series of production rules (IF….THEN). These rules can be used to validate the concept extracted from the underlying Decision Support model.
Online intention learning for human-robot interaction by scene observation

Intention recognition plays a key role in the cooperation among the humans. An intention describes an action or sequence of actions to be performed for achieving the intended purpose. The cooperating humans learn each others intentions while cooperation. In this paper we propose three ways how a robot can learn the intention of the cooperating human. In the first case, the robot learns the human intention by mapping the known human intention given in terms of scene information to the observed action sequence. The actions are already known to the robot. In the second case, the robot is only given the human actions but the robot estimates the human intention in terms of the changes that occur in the scene due to the human actions. The robot learns the human intention by mapping the observed action sequence to the human intention. The human intention is estimated from the scene information. In the third case, only the scene information is used in order to learn the human intention mapping. The scene information is used to infer the human actions as well as the human intention.
Bounded biharmonic weights for real-time deformation

Changing an object's shape is a basic operation in computer graphics, necessary for transforming raster images, vector graphics, geometric models, and animated characters. The fastest approaches for such object deformation involve linearly blending a small number of given affine transformations, typically each associated with bones of an internal skeleton, vertices of an enclosing cage, or a collection of loose point handles. Unfortunately, linear blending schemes are not always easy to use because they may require manually painting influence weights or modeling closed polyhedral cages around the input object. Our goal is to make the design and control of deformations simpler by allowing the user to work freely with the most convenient combination of handle types. We develop linear blending weights that produce smooth and intuitive deformations for points, bones, and cages of arbitrary topology. Our weights, called bounded biharmonic weights, minimize the Laplacian energy subject to bound constraints. Doing so spreads the influences of the handles in a shape-aware and localized manner, even for objects with complex and concave boundaries. The variational weight optimization also makes it possible to customize the weights so that they preserve the shape of specified essential object features. We demonstrate successful use of our blending weights for real-time deformation of 2D and 3D shapes.
Image Compression Using Deep Learning

1. Task Image compression has an important role in data transfer and storage, especially due to the data explosion that is increasing significantly faster than Moore’s Law. [1] It is a challenging task since there are highly complex unknown correlations between the pixels, as a result, it is hard to find and recover them. We want to find a well-compressed representation for images and, design and test networks that are able to recover it successfully in a lossless or lossy way.
A Theory of Concepts and Their Combinations II: A Hilbert Space Representation

The sets of contexts and properties of a concept are embedded in the complex Hilbert space of quantum mechanics. States are unit vectors or density operators, and contexts and properties are orthogonal projections. The way calculations are done in Hilbert space makes it possible to model how context influences the state of a concept. Moreover, a solution to the combination of concepts is proposed. Using the tensor product, a procedure for describing combined concepts is elaborated, providing a natural solution to the pet fish problem. This procedure allows the modeling of an arbitrary number of combined concepts. By way of example, a model for a simple sentence containing a subject, a predicate and an object, is presented.
Analysis on Industrial Land Efficiency in Sichuan Province from the Perspective of Sustainable Development

To promote the efficiency of industrial land in Sichuan province is an inevitable requirement of realizing sustainable development. Through the improvement of the Cobb-Douglas production function to construct the Two-way Fixed Effects panel model of output efficiency of urban industrial land, the data regression analysis of 93 prefecture-level cities since 1998 has found that the growth rate of industrial land efficiency indexes in Sichuan province is higher than the national level and has fallen back in recent years, but the absolute level is always lower than the national average, due to the fact that in the chase of national level, Sichuan industry did not fundamentally eliminate the root cause of low efficiency of industrial land. As a result, it is necessary to realize the improvement of optimal land utilization and land use efficiency through scientific planning, progressive construction steps and industrial transformation and upgrading, etc.
Gene mining: a novel and powerful ensemble decision approach to hunting for disease genes using microarray expression profiling

Current applications of microarrays focus on precise classification or discovery of biological types, for example tumor versus normal phenotypes in cancer research. Several challenging scientific tasks in the post-genomic epoch, like hunting for the genes underlying complex diseases from genome-wide gene expression profiles and thereby building the corresponding gene networks, are largely overlooked because of the lack of an efficient analysis approach. We have thus developed an innovative ensemble decision approach, which can efficiently perform multiple gene mining tasks. An application of this approach to analyze two publicly available data sets (colon data and leukemia data) identified 20 highly significant colon cancer genes and 23 highly significant molecular signatures for refining the acute leukemia phenotype, most of which have been verified either by biological experiments or by alternative analysis approaches. Furthermore, the globally optimal gene subsets identified by the novel approach have so far achieved the highest accuracy for classification of colon cancer tissue types. Establishment of this analysis strategy has offered the promise of advancing microarray technology as a means of deciphering the involved genetic complexities of complex diseases.
Innovations

In partnership with Performance Materials Corporation (PMC), RocTool has launched what is said to be the fi rst complete composite laptop cover. The composite cover was created by combining RocTool’s Cage System and PMC’s CFRT (continuous fi bre reinforced thermoplastic) technologies. Using this new approach, a lightweight laptop cover can be produced in approximately two minutes at a competitive price with what is said to be excellent surface quality and superior impact resistance compared with the magnesium or plastic currently used. This extremely short cycle opens a new potential market for the composites industry that may extend beyond laptops into new sectors and industries. Thomas Smith, CEO of PMC, commented that the Cage System technology provides a critical missing link in making high volume, complex CFRT parts. ‘These technologies provide for advanced composite performance approaching the detail and speed of injection moulding. The processes are also amenable to a high level of automation. ‘ One potential area of application is in consumer electronics where thin walls and high detail are required, including closed section shapes. RocTool and PMC have signed an Exclusive Development License Agreement for Laptop applications. Further information at www.roctool. com or www.performancematerials. com.