Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Efficient Adaptive Multipath Routing for Wireless Sensor Networks

Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. All these protocols typically find the minimum energy path. In this paper we take a view that, always using the minimum energy path deprives the nodes energy quickly and the time taken to determine an alternate path increases. Multipath routing schemes distribute traffic among multiple paths instead of routing all the traffic along a single path. Two key questions that arise in multipath routing are how many paths are needed and how to select these paths. Clearly, the number and the quality of the paths selected dictate the performance of a multipath routing scheme. We propose an energy efficient adaptive multipath routing technique which utilizes multiple paths between source and the sink, adaptive because they have low routing overhead. This protocol is intended to provide a reliable transmission environment with low energy consumption, by efficiently utilizing the energy availability and the received signal strength of the nodes to identify multiple routes to the destination. Simulation results show that the energy efficient adaptive multipath routing scheme achieves much higher performance than the classical routing protocols, even in the presence of high node density and overcomes simultaneous packet forwarding
EMBHMAC: An efficient multihop broadcast based hybrid MAC protocol for wireless sensor networks

The objective of EMBHMAC is to reduce the energy consumption and delay in wireless sensor networks. The working of proposed protocol is based on sender's guidance, overhearing, hybrid TDMA/FDMA concept and controlled power mechanism. The sender's guidance reduces the redundant transmission and collision by giving guidance of how to forward the packets. Overhearing reduces the active time of nodes. Asynchronous duty-cycling can reduce the energy consumption by carrying out alternation between sleep mode and active mode. Delay in MAC layer is increased as a result of this. The proposed protocol can overcome this problem by using the hybrid TDMA/FDMA concept where within the same network we can use différent frequencies and multiple transmissions can be carried out at same time slot and hence reduces delay. Controlled power mechanism controls the power desired for transmission of data by varying the transmission power and this increases energy efficiency. The proposed protocol is compared with ADB and EMBA. The performance of proposed protocol is carried out in the absence and presence of an obstacle also.
Brief overview of T-tree: the Tropes Taxonomy building Tool

TROPES is an object-based knowledge representation system. It allows the representation of multiple taxonomies over the same set of objects through viewpoints and provides tools for classification (identification) of objects and categorisation (classification) of classes from their descriptions. T-TREE is an extension of TROPES for the construction of taxonomies from objects. Data analysis algorithms consider TROPES objects for producing TROPES taxonomies. Thus, data analysis is integrated into the knowledge representation system. Moreover, the original bridge notion permits the comparison and connection of adjacent taxonomies.
Morphological Real Time Video Edge Detection in Labview

Video Edge is one of the most fundamental and significance features. Edge detection is always one of the classical studying projects of computer vision and image processing field. The first step is video analysis and understanding. The purpose of edge detection [1] is to discover the information about the edge and hiding the background of the video. The correctness and reliability of its results affect directly the comprehension machine system made for objective world. Reading the AVI and some pre-process work done on that AVI file. Taking frames each time and doing normal edge detection in LabVIEW, and is made to display on the screen. The frames are continuously read and again the same steps are repeated until frames are finished. This paper describes the characteristics of edges, the properties of traditional detectors. Finally, this paper analyzed their advantages, disadvantages and presents some recommendations for future work. The LabVIEW is to build virtual instrumentation and take an effective graphical system design approach that can be effectively leverage the opportunities and take on the challenges of modern academic research and development. Keywords— LabVIEW, Morphological process, Sobel algorithm, Front panel, Edge detection.
Inhibition of mitochondrial permeability transition to prevent the post-cardiac arrest syndrome: a pre-clinical study.

AIMS Resuscitated cardiac arrest (CA), leading to harmful cardiovascular dysfunction and multiple organ failure, includes a whole-body hypoxia-reoxygenation phenomenon. Opening of the mitochondrial permeability transition pore (mPTP) appears to be a pivotal event in ischaemia-reperfusion injury. We hypothesized that pharmacological inhibition of mPTP opening may prevent the post-CA syndrome. METHODS AND RESULTS Anaesthetized New Zealand White rabbits underwent a 15 min primary asphyxial CA and 120 min of reperfusion following resuscitation. At reflow, animals received an intravenous bolus of either cyclosporine A (CsA, 5 mg/kg) or NIM 811 (2.5 mg/kg), two potent inhibitors of mPTP opening, or the CsA vehicle (control). Short-term survival, haemodynamics, regional (sonomicrometry), and global cardiac function (dP/dt and aortic flow) were assessed. We measured markers of cellular injuries and/or organ failure, including troponin Ic release, lacticodehydrogenase, lactate, creatinine, and alanine aminotransferase. Cyclosporine A and NIM 811 significantly improved short-term survival, post-resuscitation cardiac function, as well as liver and kidney failure (P < 0.05). CsA and NIM 811 both attenuated in vitro mPTP opening (calcium retention capacity by spectrofluorimetry) and restored oxidative phosphorylation when compared with controls (P < 0.05). CONCLUSION These data suggest that pharmacological inhibition of mPTP opening, added to basic life support, attenuates the post-CA syndrome and improves short-term outcomes in the rabbit model.
Emotions in Product Reviews--Empirics and Models

Online communities provide Internet users with means to overcome some information barriers and constraints, such as the difficulty to gather independent information about products and firms. Product review communities allow customers to share their opinions and emotions after the purchase of a product. We introduce a new dataset of product reviews from Amazon.com, with emotional information extracted by sentiment detection tools. Our statistical analysis of this data provides evidence for the existence of polemic reviews, as well as for the coexistence of positive and negative emotions inside reviews. We find a strong bias towards large values in the expression of positive emotions, while negative ones are more evenly distributed. We identified different time dynamics of the creation of reviews dependent on the presence of marketing and word of mouth effects. We define an agent-based model of the users of product review communities using a modeling framework for online emotions. This model can reproduce the scenarios of response to external influences, as well as some properties of the distributions of positive and negative emotions expressed in product reviews. This analysis and model can provide guidelines to manufacturers on how to increase customer satisfaction and how to measure the emotional impact of marketing campaigns through reviews data.
Robots in casinos: Distributed control and the problem of efficient action selection

In this paper we characterise a tension between two views about how an agent could achieve efficient action selection. On one hand, it is common in some of the cognitive and behavioural sciences to maintain that efficient action selection requires that the value of all actions or options available to an agent are represented on a unidimensional scale of values, in other words that action selection make use of a “common currency”. On the other hand, early work in situated, embodied robotics and distributed control associated with Rodney Brooks maintained that “intelligence” could be achieved without the instantiation of any representations at all, and without centralised control systems. This line of thinking has exerted significant influence in situated and enactivist approaches to human cognition. If what situated roboticists count as “intelligence” includes capacity for efficient action selection, then their claim that intelligence can be achieved without representations is in tension with the views of those who argue that efficient action selection requires that a common currency be represented. We argue here that the apparent tension is genuine, develop an analysis of the tension itself, and offer a preliminary overview of the considerations relevant to navigating it.
Framework for consistent maintenance of geometric data and abstract task-knowledge from range observations

We present a framework for on-line exploration of object attributes from range data designed to include the cognitive aspects for surprise detection. In this framework we introduce a layered representation of the environment that couples the pure geometric 3D representation of the world to the abstract knowledge about the structures in the scene. This knowledge in the higher layer represents a-priori known, task-relevant information about structures in the world like mass, handling properties and grasping points being examples in the case of a manipulation task. The coupling of abstract knowledge to the geometry in the dual layered structure of our map helps to ensure consistency of the representation. The focus of the paper is on data association of dense 3D points from range sensors. We introduce a z-buffered re-projection method as a way to filter outlier information in sensor readings and present our technique for fusion based on the uncertainties in the map representation and the current observation. In contrast to common registration methods, our approach does not store the data as one rigid model but as a set of independent point clusters (foreground) embedded in a 3D point cloud of the supporting structure (background). This allows us to cope with dynamic changes in the world. We register the incoming data not rigidly to the entire map but we update independently the pose of single objects represented in our hierarchical model. The fusion approach combines a local-heuristic with a global-robust procedure and the correspondence search cost of O(nm) is reduced to a set of m sub-searches with linear cost each. The benefit of the re-projection is twofold: it helps speeding up the point matching search by ordering the 3D data according to the manner they might have been captured and making the matching process robust by filtering out outliers and occluded object parts. We present the theoretical framework and we validate our approach on range data from a binocular stereo setup.
Diameter dependence of scattering limited transport properties of Si nanowire MOSFETs under uniaxial tensile strain

Effects of the diameter on the drain current of uniaxially strained Si nanowire (NW) MOSFETs are investigated. Based on the deterministic solution of the multi-subband Boltzmann transport equation, the drain current is calculated considering the intravalley acoustic phonon scatterings, intervalley phonon scatterings and interface roughness scatterings. We found 3 nm diameter [110] oriented Si NW MOSFETs shows ~2X drain current enhancement by the 1% uniaxial tensile strain.
Segmentation of 3D Articulated Objects by Dynamic Grouping of Discontinuities

Segmentation of 3D articulated objects into a small number of parts is an important step for recognition of objects in 3D space. Range data provides ready-to-use information to derive a reasonably stable and accurate differential structure of the surfaces, which allow us to track discontinuities between these parts. We present a mixed and comprehensive approach to segmenting and extracting prototypical parts from 3D articulated objects. Discontinuity points detected from the images are combined using a "snake-type" minimization technique, and deformable superquadric models are fitted to the resulting regions afterwards. We compare our approach with others for part-based segmentation.
Hybrid Row-Column Partitioning in Teradata

Data partitioning is an indispensable ingredient of database systems due to the performance improvement it can bring to any given mixed workload. Data can be partitioned horizontally or vertically. While some commercial proprietary and open source database systems have one flavor or mixed flavors of these partitioning forms, Teradata Database offers a unique hybrid row-column store solution that seamlessly combines both of these partitioning schemes. The key feature of this hybrid solution is that either row, column, or combined partitions are all stored and handled in the same way internally by the underlying file system storage layer. In this paper, we present the main characteristics and explain the implementation approach of Teradata's row-column store. We also discuss query optimization techniques applicable specifically to partitioned tables. Furthermore, we present a performance study that demonstrates how different partitioning options impact the performance of various queries.
Glen or Glenda Empowering Users and Applications with Private Namespaces

Private name spaces were first introduced into L INUX during the 2.5 kernel series. Their use has been limited due to name space manipulation being considered a privileged operation. Giving users and applications the ability to create private name spaces as well as the ability to mount and bind resources is the key to unlocking the full potential of this technology. There are serious performance, security and stability issues involved with user-controlled dynamic private name spaces in L INUX . This paper proposes mechanisms and policies for maintaining system integrity while unlocking the power of dynamic name spaces for normal users. It discusses relevant potential applications of this technology including its use with F ILESYSTEM IN USERSPACE[24], V9FS[8] (the LINUX port of the PLAN 9 resource sharing protocol) and PLAN 9 FROM USER SPACE[4] (the PLAN 9 application suite including user space synthetic file servers ported to UNIX variants).
Ask Alice: an artificial retrieval of information agent

We present a demonstration of the ARIA framework, a modular approach for rapid development of virtual humans for information retrieval that have linguistic, emotional, and social skills and a strong personality. We demonstrate the framework's capabilities in a scenario where `Alice in Wonderland', a popular English literature book, is embodied by a virtual human representing Alice. The user can engage in an information exchange dialogue, where Alice acts as the expert on the book, and the user as an interested novice. Besides speech recognition, sophisticated audio-visual behaviour analysis is used to inform the core agent dialogue module about the user's state and intentions, so that it can go beyond simple chat-bot dialogue. The behaviour generation module features a unique new capability of being able to deal gracefully with interruptions of the agent.
Facilitating Magnetic Recording Technology Scaling for Data Center Hard Disk Drives through Filesystem-Level Transparent Local Erasure Coding

This paper presents a simple yet effective design solution to facilitate technology scaling for hard disk drives (HDDs) being deployed in data centers. Emerging magnetic recording technologies improve storage areal density mainly through reducing the track pitch, which however makes HDDs subject to higher read retry rates. More frequent HDD read retries could cause intolerable tail latency for large-scale systems such as data centers. To reduce the occurrence of costly read retry, one intuitive solution is to apply erasure coding locally on each HDD or JBOD (just a bunch of disks). To be practically viable, local erasure coding must have very low coding redundancy, which demands very long codeword length (e.g., one codeword spans hundreds of 4kB sectors) and hence large file size. This makes local erasure coding mainly suitable for data center applications. This paper contends that local erasure coding should be implemented transparently within filesystems, and accordingly presents a basic design framework and elaborates on important design issues. Meanwhile, this paper derives the mathematical formulations for estimating its effect on reducing HDD read tail latency. Using Reed-Solomon (RS) based erasure codes as test vehicles, we carried out detailed analysis and experiments to evaluate its implementation feasibility and effectiveness. We integrated the developed design solution into ext4 to further demonstrate its feasibility and quantitatively measure its impact on average speed performance of various big data benchmarks.
Cell surface proteoglycan associates with the cytoskeleton at the basolateral cell surface of mouse mammary epithelial cells

The cell surface proteoglycan on normal murine mammary gland mouse mammary epithelial cells consists of an ectodomain bearing heparan and chondroitin sulfate chains and a lipophilic domain that is presumed to be intercalated into the plasma membrane. Because the ectodomain binds to matrix components produced by stromal cells with specificity and high affinity, we have proposed that the cell surface proteoglycan is a matrix receptor that binds epithelial cells to their underlying basement membrane. We now show that the proteoglycan surrounds cells grown in subconfluent or newly confluent monolayers, but becomes restricted to the basolateral surface of cells that have been confluent for a week or more; Triton X-100 extraction distinguishes three fractions of cell surface proteoglycan: a fraction released by detergent and presumed to be free in the membrane, a fraction bound via a salt-labile linkage, and a nonextractable fraction; the latter two fractions co-localize with actin filament bundles at the basal cell surface; and when proteoglycans at the apical cell surface are cross- linked by antibodies, they initially assimilate into detergent- resistant, immobile clusters that are subsequently aggregated by the cytoskeleton. These findings suggest that the proteoglycan, initially present on the entire surface and free in the plane of the membrane, becomes sequestered at the basolateral cell surface and bound to the actin-rich cytoskeleton as the cells become polarized in vitro. Binding of matrix components may cross-link proteoglycans at the basal cell surface and cause them to associate with the actin cytoskeleton, providing a mechanism by which the cell surface proteoglycan acts as a matrix receptor to stabilize the morphology of epithelial sheets.
Merging Topological Maps for Localisation in Large Environments

This article presents a method for the creation of a topological map without having to previously create a geometric map. Independently obtained topological paths are compared pairwise to search for possible overlap in the view sequence. Each individual topological path is created from a sequence of raw data views that are sampled by leading the robot along a path in the environment. The multiple topological paths are ’stitched together’ into a generic Topological map by identifying overlapping segments in the individual sequences. A general topological map can be created by considering all the multiple sequences or separate runs through the environment. Results on the merger of upto 8 seperate paths indicate that this method of mapping large environments, by selective touring through the environment, can generate robust topological maps.
Research and Implementation of Hybrid Recommendation Algorithm Based on Collaborative Filtering and Word2Vec

According to the traditional recommendation technology which is applied in large-scale mobile data set is difficult to balance the accuracy and efficiency of recommendation, this paper puts forward a hybrid recommendation algorithm based on collaborative filtering and Word2Vec. The traditional collaborative filtering algorithm is realized with MapReduce framework and Hive database on the Hadoop platform. Use the Word2Vec model to train the tag information of the mobile data to get the similarity between the tags, and recommend applications to the user according to the similarity. Finally, according to the feedback behavior of the user, the recommendation results are mixed with weight. The experimental results show that the hybrid recommendation algorithm improves the efficiency and accuracy of recommendation greatly, and makes it more advantageous in the large-scale data set.
Effectively Indexing the Multidimensional Uncertain Objects

As the uncertainty is inherent in a wide spectrum of applications such as radio frequency identification (RFID) networks and location-based services (LBS), it is highly demanded to address the uncertainty of the objects. In this paper, we propose a novel indexing structure, named U-Quadtree, to organize the uncertain objects in the multidimensional space such that the queries can be processed efficiently by taking advantage of U-Quadtree. Particularly, we focus on the range search on multidimensional uncertain objects since it is a fundamental query in a spatial database. We propose a cost model which carefully considers various factors that may impact the performance. Then, an effective and efficient index construction algorithm is proposed to build the optimal U-Quadtree regarding the cost model. We show that U-Quadtree can also efficiently support other types of queries such as uncertain range query and nearest neighbor query. Comprehensive experiments demonstrate that our techniques outperform the existing works on multidimensional uncertain objects.
Visual Object Categorization via Sparse Representation

In this paper, we consider the problem of classifying a real world image to the corresponding object class based on its visual content via sparse representation, which is originally used as a powerful tool for acquiring, representing and compressing high-dimensional signals. Assuming the intuitive hypothesis that an image could be represented by a linear combination of the training images from the same class, we propose a novel approach for visual object categorization in which a sparse representation of the image is first of all obtained by solving a L1 (or L0)-minimization problem and then fed into a traditional classifier such as Support Vector Machine (SVM) to finally perform the specified task. Experimental results obtained on the SIMPLIcity database have shown that this new approach can improve the classification performance compared to standard SVM using directly features extracted from the image.
TWOFOLD CONTINUITY IN IMMERSIVE LANGUAGE LEARNING

Overview: An immersive language learning environment undertakes to engage the student in a two-medium communication process: a conver­ sation supplemented by graphical interaction in an ordinary scene on the computer screen. The fundamental rationale for such a system is that it promotes language learning by enabling the student to we the new lan­ guage, not analyse or translate it. In this paper, we examine two constel­ lations of issues that arise in trying to provide computer-based language immersion, issues concerning discourse and issues of tutorial strategy, and consider how to deal with their apparently confticting demands.