Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable Computing: Practice and Experience

The Internet of Things (IoT) vision is enticing; each and every “thing” in the world is expected to be eventually connected to the Internet, thereby becoming a part of the “context” within which the applications live. In most of the IoT research, the focus has been in enabling movable things to communicate, including phones, tablets, RFID tags, watches, and jewellery, to name but a few. In such an approach, the things are expected to have their own batteries or receive temporary power over short distance electro-magnetic field. This approach has also dominated the more fixed side of the IoT research, including a large fraction on the work on stationary sensors and actuators, focusing also there on battery-based operations and wireless communication. In this paper, we introduce an alternative view to the world of stationary Internet-connected things. We argue that a large majority of the fixed or stationary things would benefit from being permanently powered using wireline connections, and while doing so, it becomes natural to use the same wires also for their communication and contextual needs. Such an approach allows the appliances to become part of the the wider application context. With this in mind, we introduce the ELL-i platform, a new open source initiative for provide a low-cost flexible prototyping and production platform for extensible, Power-over-Ethernet based smart appliances. We describe the first ELL-i prototyping board, a number of application concepts, and discuss its business model.
Scalable Computing: Practice and Experience

The increasing energy consumption of large-scale high performance resources raises technical and economical concerns. A reduction of consumed energy in multicore systems is possible to some extent with an optimized usage of computing and memory resources that is tailored to specific HPC applications. The essential step towards more sustainable consumption of energy is its reliable measurements for each component of the system and selection of optimally configured resources for specific applications. This paper briefly surveys the current approaches for measuring and profiling power consumption in large scale systems. Then, a practical case study of a real-time power measurement of multicore computing system is presented on two real HPC applications: maximum clique algorithm and numerical weather prediction model. We assume that the computing resources are allocated in a HPC cloud on a pay-per-use basis. The measurements demonstrate that the minimal energy is consumed when all available cores (up to the scaling limit for a particular application) are used on their maximal frequencies and with threads binded to the cores.
Studying the interactive effect of potassium application and individual field crops on root penetration under drought condition

In this study, interactive effects of different potassium application and water restrict on: root penetration at Iran. The experimental unit had designed by achieved treatment in factorial on the basis completely randomized block design with three replications. Certain factors including potassium and non-potassium applications (0 and 200 kg/ha), certain field crops (maize, sorghum and millet) and water supply were studied. In this study crops water supply was determined by indicated irrigation conditions by keeping leaf relative water content (RWC) > 95% (non-drought stress condition or irrigation conditions) and drought condition by RWC = 60 - 70%. We noticed, however K fertilizer significantly increased the root penetration of plants. Although the non-drought stress treatment significantly increased root penetration and highest root penetration of maize was achieved under irrigation conditions (non-drought), but the highest roots penetration of sorghum and millet were indicated under the drought condition. Whereas K application persist less damaging of drought stress result and it enabled plant to significantly grew its root and penetrating along soil depth under the drought condition. Our finding may give applicable advice to farmers and agricultural researchers for management and concern on fertilizer strategy and carefully estimate soil potassium supply within arid or semi arid regions as most challengeable issues of environmental safety.
Scalable Computing: Practice and Experience

Abstract. Wireless Sensor Network (WSN) has emerged as one of the most important technologies serving an array of solutions for critical applications such as defense, industrial monitoring and decision purposes. Data routing in WSN is effective or non-effective depending upon the energy saving for nodes while transferring data packets to the sink. Mainly WSN divided into two modes; heterogeneous and homogeneous. Heterogeneous network in WSN mainly focused on the cluster head selection. Sink mobility in the heterogeneous network has still many open research issues, it is observed that it makes the network more energy efficient. The optimization in the network leads to the stability of the network at a much higher level. In this paper, the sink mobility is optimized for WSN using Honey Bee Optimization (HBO) technique by considering the parameters such as energy and distance. The proposed protocol shows significant improvement in the stability period by 33 % by covering 2928 rounds and enhanced network lifetime by 1500 rounds in compared with 2033 and 14084 rounds for iMBEENISH protocol respectively.
Scalable Computing: Practice and Experience

We present a task-parallel asynchronous API for numerical linear algebra that utilizes multiple CPUs, multiple GPUs, or a combination of both. Furthermore, we present a wrapper of this interface for use in MATLAB. Our API imposes only small overheads, scales perfectly to two processor cores, and shows even better performance when utilizing computational resources on the GPU.
HBaseSI: Multi-row Distributed Transactions with Global Strong Snapshot Isolation on Clouds

This paper presents the 'HBaseSI' client library, which provides global strong snapshot isolation (SI) for multi-row distributed transactions in HBase. This is the first strong SI mechanism developed for HBase. HBaseSI uses novel methods in handling distributed transactional management autonomously by individual clients. These methods greatly simplify the design of HBaseSI and can be generalized to other column-oriented stores with similar architecture as HBase. As a result of the simplicity in design, HBaseSI adds low overhead to HBase performance and directly inherits many desirable properties of HBase. HBaseSI is non-intrusive to existing HBase installations and user data, and is designed to be scalable across a large cloud in terms of data size and distribution.
Scalable Computing: Practice and Experience

Scientific Workflow is a composition of both coarse-grained and fine-grained computational tasks displaying varying execution requirements. Large-scale data transfer is involved in scientific workflows, so efficient techniques are required to reduce the makespan of the workflow. Task clustering is an efficient technique used in such a scenario that involves combining multiple tasks with shorter execution time into a single cluster to be executed on a resource. This leads to a reduction of scheduling overheads in scientific workflows and thus improvement of performance. However available task clustering methods involve clustering the tasks horizontally without the consideration of the structure of tasks in a workflow. We propose hybrid balanced task clustering algorithm that uses the parameter of impact factor of workflows along with the structure of workflow. According to this technique, tasks can be considered for clustering either vertically or horizontally based on the value of the impact factor. This minimizes the system overheads and the makespan for execution of a workflow. A simulation based evaluation is performed on real workflows that shows the proposed algorithm is efficient in recommending clusters. It shows improvement of 5-10% in makespan time of workflow depending on the type of workflow used.
Scalable Computing: Practice and Experience

In todays world, Android has revolutionized every facet of our lives. Almost all the important services such as banking, transportation, stock trade, medicine, education, etc. are extended to Android these days. Everything is available in the application market of android. Unfortunately, at the same time, the prosperity of these applications also attracts abusers and malicious attackers to perform different types of attacks. An appropriate action needs to be taken to protect Android device from these attacks. Android applications privacy analysis is an extension to the android privacy model, which traditionally emphasizes on prevention, and detection of attacks. It also deals with capturing, recording and analysis of Android applications to detect and investigate Android device intrusions. In this paper, we explore the comprehensive study about different techniques proposed to perform Android applications analytics. In addition to this, various aspects of android applications analytics have been reviewed along with related technologies and their limitations. This gives enhanced recognition of the problem, existing explanation space, and potential research scope to analyze and investigate various Android device intrusions against such attacks efficiently.
Scalable Computing: Practice and Experience

Wireless Sensor Network (WSN) is an advanced technology and has been used widely in many applications such as health monitoring, environment monitoring, military purpose etc. Nature of this network is that they are often placed in an open environment and are susceptible to various attacks. Traditional cryptography methods are not supportable in WSNs as they have high energy and resource constraints. Trust management has been proved to be an effective measure to enhance security as well as to handle threats for WSNs. Trust can be defined as level of reliableness in a node. Low Energy Adaptive Clustering (LEACH) is a cluster based routing protocol for WSN which is superior to direct communication protocol and known for its minimum transmission energy. However, LEACH itself has some limitations related to security. In this paper, an energy efficient and trust aware framework for secure routing in LEACH (EETA-LEACH), has been proposed that improves LEACH protocol by introducing trust to provide secure routing, while maintaining originality of LEACH protocol. This approach is a combination of trust-based routing module and trust management module that works together to select trusted Cluster Head (CH). The simulation results demonstrate that proposed scheme is better in terms of network lifetime and Packet Delivery Ratio (PDR). It is verified that malicious nodes will not be selected as CH and trust value of a malicious node decreases with time.
An Efficient Fault-Tolerant Routing Strategy for Tori and Meshes

In massively parallel computing system, high performance interconnection networks are decisive to get the maximum performance. While routing is one of the most important design issues of interconnection networks, fault-tolerance is another issue of growing importance in these machines, since the huge amount of hardware increases the probability of failure. This paper proposes a mechanism that provides both, scalable routing and fault-tolerance, for commercial switches to build direct regular topologies, which are the topologies used in large machines. The mechanism is very flexible and the hardware required is not complex. Furthermore, it allows a high number of faults having a minimal effect on performance.
Scalable Computing: Practice and Experience

Social network analysis is one of the key areas of research during modern times. The social network is growing with more users and the ties between them day by day. This reason brings out many research queries and new conclusions from this area. Overlapping community detection in the social network is one such research problem which has acquired interest among researchers nowadays. Earlier, the investigation was in finding out algorithms to detect communities in the network sequentially. There are many distinguished findings toward overlapping community detection. Due to the velocity of data in the current era, the available algorithms will be a bit sluggish in processing the data. The proposed algorithm uses parallel processing engine to resolve this delay problem in the current scenario. The algorithm in parallel finds out the superior seed set in the network and expands it in parallel to find out the community. The work shows amazing improvement in the runtime and also detects quality groups in the network.
Challenges in Computer Architecture Evaluation

We focus on problems suited to the current evaluation infrastructure. The current limitation and trends in evaluation techniques are troublesome and could noticeably slow the rate of computer system innovation. New research has been recommended to help and make quantitative evaluations of computer systems manageable. We support research in the areas of simulation frameworks, benchmarking methodologies, analytic methods, and validation techniques.
Near-field modifications of stress induced by dyke injection at shallow depth

SUMMARY The deformation and stress fields accompanying dyke injection in rift zones are described in terms of a vertical crack opening in response to internal overpressure, in plane-strain configuration. Previous numerical computations of the displacement field induced by shallow dykes are found to be affected, in some cases, by significant distortion, mainly due to the limited extension of the computational domain, difficulties in handling the singularities in the proximity of the free surface and an incorrect choice of the reference frame; in particular, it is found that no subsidence can be ascribed to the mere opening of a tensile crack in a homogeneous, elastic half-space. If analytical constant-dislocation models are employed, surface displacements compare reasonably well with crack-model solutions if the upper tip is not too shallow; however, constant dislocation solutions present unphysical singularities along the tips, which distort significantly the near-field stress pattern with respect to crack solutions. If the principal stress axes are computed from crack models, a broad region is found on both sides of the dyke where the induced stress has a nearly vertical intermediate axis while the compressive axis is normal to the dyke plane. Strike-slip earthquakes are expected to prevail in this region. Above the upper crack tip, a small region is present where the tensile stress is dominant and the intermediate stress is still vertical. In the proximity of the free surface, typically within a few tens of metres of it, induced tensile stresses are greater than the lithostatic pressure: open fissures might then develop in cohesionless soil or pre-faulted rock. The induced pressure in the host rock is found to be negative (suction) in the proximity of the ground surface and positive at greater depth: fluid flow within the aquifers can be significantly altered by this induced overpressure and by the anisotropic modification of the pre-existing permeability. According to the modified Coulomb failure criterion, in the short term the shallower region, characterized by suction, is strengthened, while the deeper, pressurized region is weakened. These results can explain in a straightforward way the abundance of strike-slip focal mechanisms in volcanic areas, the switch between tensional and compressional axes inferred from focal mechanisms of earthquakes in connection with a dyke injection episode on Mount Etna, en echelon fracture systems observed at Piton de la Fournaise above the feeding dyke and precursory geochemical anomalies.
Cleavage–fold relationships in the Lower Cambrian Tubize Group, southeast Anglo-Brabant Fold Belt (Lembeek, Belgium)

Little is known about the cleavage–fold relationships in the Lower Palaeozoic Brabant Massif, primarily because of the scarcity of suitable exposures. Moreover, to date, folds have only been described in the Ordovician and Silurian sequences along the southern extremity of the basement. However, excavation works for the construction of the TGV(railway)-track south of Brussels created an opportunity to study cleavage–fold relationships in the Lower Cambrian terrigenous series (Tubize Group) in a more central part of the Brabant Massif. The structural features observed seemed inconsistent with the suspected regional trends. Primarily, a divergent cleavage fan was observed in a region thought to have a regular cleavage attitude. The symmetrical but divergent disposition of the cleavage with regard to the fold hinges is explained by flexural folding of a pre-existing bedding-parallel compaction fabric. Cleavage development and folding are considered synchronous. The divergent cleavage fan reflects local strain variations. Also the steeply plunging hinge lines of the open, subangular folds are seemingly inconsistent with the regional trend characterized by subhorizontal fold hinges. Taking into account the structural position of the fold assemblage in the subvertical limb of a large-scale, upright, isoclinal fold structure, the fold assemblage is interpreted as an incongruous parasitic feature. The steeply plunging hinge lines are considered to be caused by fold hinge rotation during progressive coaxial deformation. Although this incongruous fold assemblage with its divergent cleavage fan is localized, it provides important information on both local and regional deformation circumstances in this part of the Anglo-Brabant Fold Belt.
Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of field plots across two mixed conifer forest landscapes in north-central Idaho. Our objective was to compare alternative models for producing unbiased maps of basal area per acre (BAA; ft2/acre), towards the greater goal of developing more accurate and efficient inventory techniques. We generated 60 topographic or stand structure metrics from LiDAR that were used as candidate predictor variables for modeling and mapping BAA at the scale of 30m pixels. Tree diameters were tallied in 1/10 and 1/5 acre fixed-radius plots (N = 165). Four models are presented, all based on 12 predictor variables. The first imputes BAA as an auxiliary variable from an imputation model that uses the machine learning algorithm randomForest in classification mode, and was developed in a prior study to map species-level basal areas of 11 conifer species; the second uses randomForest in regression mode to predict BAA as a single response variable from these same 12 predictor variables. The third is a linear regression model that predicts ln-transformed BAA using a best subset of 12 different predictor variables; the fourth again uses randomForest in regression mode, based on the same best subset of 12 variables selected for the linear regression model. We aggregated the pixel-level predictions within industrial forest stand boundaries, and then used equivalence plots to evaluate how well the aggregated predictions matched independent stand exams (having projected the tree growth in FVS and updated the stand tables to July 2003, the time of the LiDAR acquisition). All four models overpredicted BAA, but the bias was significant only in the case of the regression model. Predictions from the two randomForest models run in regression mode were very similar, despite using different predictor variables. We conclude that randomForest can be used to impute or predict canopy structure information from LiDAR-derived topographic and structural metrics with sufficient accuracy for operational management of conifer forests. In the future, tree lists could be imputed from LiDAR-derived canopy structure metrics empirically related to plot-level tree measurements. This will allow projections of tree growth at the pixel level across forested landscapes, instead of at the stand level as is the current norm.
Periodontitis Associates with a Type 1 IFN Signature in Peripheral Blood Neutrophils1

Peripheral blood neutrophils from periodontitis patients exhibit a hyperreactive and hyperactive phenotype (collectively termed hyperresponsivity) in terms of production of reactive oxygen species (ROS). The molecular basis for this phenomenon, however, has yet to be determined. Our objectives were to identify genes differentially expressed in hyperresponsive peripheral blood neutrophils from chronic periodontitis patients relative to periodontally healthy controls and use these data to identify potential contributory pathways to the hyperresponsive neutrophil phenotype. Using microarray technology we demonstrated differential expression of 163 genes (149 increased, 14 decreased) representing a range of ontological classes. There was increased expression of a significant number of IFN-stimulated genes (ISG). RT-PCR analysis of ISG transcripts in individual and pooled samples further corroborated these data, and indicated that levels decreased to near those of controls following successful therapy. Significantly enhanced FcγR-stimulated ROS production was subsequently achieved by priming control neutrophils with IFN-α/-β/-γ, but not LPS, and gene expression analysis indicated that exposure to the type I IFN (in particular IFN-α) better replicated the mRNA profile observed in vivo. Further studies demonstrated that plasma levels of IFN-α were significantly higher in samples from patients relative to unaffected controls. Following successful periodontitis treatment, plasma IFN-α levels, neutrophil ISG expression, and FcγR-stimulated neutrophil ROS output of patients, all decreased to levels comparable with those of controls. In conclusion, although chronic periodontitis is a complex disease, raised IFN-α may be one determinant of the distinct molecular phenotype and hyperresponsivity exhibited by patients’ peripheral blood neutrophils.
VTL 6: a semi-tall, non-lodging, and high yielding rice (Oryza sativa L.) variety for the coastal saline zones of Kerala.

To evolve a lodging resistant, abiotic stress tolerant, and high yielding rice variety for the pokkali areas of Kerala, F 1 of the cross between ‘Cheruvirippu’ and IR 5 was crossed with ‘Jaya’. Based on evaluation of the promising cultures at local, regional, and national levels, VTL 6, the first saline tolerat, semi-tall, non-lodging high yielding rice variety of Kerala was released for cultivation in the coastal saline areas of Kerala in October 2004. This variety has multiple tolerance to abiotic stresses like salinity, acidity, and submergence, and is a medium duration, red kernelled variety with good cooking quality. Average yield under close planting without chemical fertilizers and plant protection chemicals is about 4500 kg ha-1 .