Exploitation Of Techniques Research Articles

Cell dedifferentiation and multiplication of Burdock (Arctium Lappa) as a medicinal plant

Arctium lappa L. (Burdock) is an important plant with various pharmacological effects. According to the importance of this plant, optimization of its tissue culture will lead to more investigation and application of it. The aim of this study was to develop protocols for callus induction and shoot regeneration of A. lappa. In order to optimize of tissue culture in A. lappa, callus induction, indirect regeneration and direct regeneration were carried out in factorial experiment based on Completely Randomized Designs (CRDs). Hypocotyl and cotyledon were cultured on the Murashige and Skoog (MS) medium supplemented with different concentrations and combinations of 2,4-Dichlorophenoxyacetic acid (2,4-D) and 6-Benzylaminopurine (BAP) for callus induction. In indirect regeneration experiment various levels of BAP and α-Naphthaleneacetic acid (NAA) and two types of explants (calli derived from cotyledon and hypocotyl) were investigated. In direct regeneration section, various levels of BAP plus 2 mg/l NAA and different explants (cotyledon, hypocotyl and bud) were compared. In both cotyledon and hypocotyl, the maximumcallus inductionwas observed on a media containing 2 mg/l 2,4-D plus 1 mg/l BAP (100% and 76.19% respectively). The highest percentage of indirect regeneration (65%) was observed at 1 mg/l BAP plus 0.5 mg/l NAA on calli from hypocotyl. The highest percentage of direct regeneration (90.33) was observed in hypocotyl with a lateral bud explant on MS medium supplemented with 0.5 mg/l BAP plus 2 mg/l NAA. In this study, optimization of tissue culture protocol for A. lappa was carried out as a research technique, as well as technique for further exploitation of this plant.

The competitive advantage in business, capabilities and strategy. What general performance factors are found in the Spanish wine industry?

The wine sector in Europe has undergone a major change of trend in recent years, especially in Spain. On the one hand, the surface area has been reduced, but the production has been maintained by restructurings and improvements made in exploitation techniques. On the other hand, consumption has diminished causing a significant increase in competition. The Spanish wine sector is formed mainly by small and medium-sized firm, which is representative of the size of existing companies in Europe. This article aims to analyze the relationships between the competitive strategy, resources and capabilities of the firms, analyzing their technological and managerial capabilities, with business performance. 339 companies of the wine sector in Spain have been studied, differentiating between individual firms, cooperatives and mercantile companies. The results reveal that resources and capabilities along with strategies define competitive advantage, but their relationship and importance is different for each type of company.

Gestión cinegética racional ligada a la praxis de la caza y la recolección. ¿Entelequia aristotélica o quimera?

Gestión cinegética racional ligada a la praxis de la caza y la recolección. ¿Entelequia aristotélica o quimera? Desde los albores de su historia filogenética, el consumo de proteínas de origen animal ha tenido gran relevancia en la evolución de los humanos. La caza cooperativa representa una estrategia evolutiva estable a partir del momento en que los cazadores paleolíticos se especializan en la persecución de grandes animales. Todo este proceso implica la adopción de decisiones relacionadas con la gestión de la caza, algunas de las cuales siguen siendo utilizadas por los cazadores-recolectores contemporáneos. En estas sociedades que todavía practican la caza como medio de subsistencia, la composición de sus respectivas dietas y las técnicas de explotación empleadas son explicables bajo supuestos teóricos contenidos en la Teoría del Forrajeo Óptimo (TFO). Con objeto de poner a prueba dicha teoría, se han tomado en consideración cuatro decisiones que implican la adopción de diferentes estrategias de gestión por parte de los cazadores-recolectores: I) qué comer, II) dónde y cómo buscar el alimento, III) cuáles son el tamaño y composición más adecuados del grupo de cazadores-recolectores y IV) qué pautas de manipulación y reparto de las presas son más eficientes. La TFO se ha puesto a prueba en diversas ocasiones y, en un alto porcentaje de los casos estudiados, sus predicciones se ajustan a lo observado en distintas sociedades cazadoras-recolectoras. Esto significa que la maximización de los rendimientos de captura a corto plazo es su principal preocupación, en lugar de comportarse como “depredadores prudentes” o realizar una selección pasiva de sus presas en función del tamaño, accesibilidad y abundancia de las mismas. Dicho comportamiento no niega que los cazadores-recolectores actúen como conservacionistas pero descarta que esa sea la principal preocupación de su modo de vida. No cabe duda de que los pueblos indígenas tienen un amplio conocimiento del medio, pero no está claro si lo utilizan para mantener un balance con la naturaleza o para ser cazadores más eficientes Es más probable que la extracción sostenible se deba a una baja presión de caza en zonas donde abundan las presas, lo que constituye un epifenómeno en lugar de una estrategia deliberada de conservación. A tenor de los datos disponibles, seguir manteniendo el mito del salvaje ecológicamente noble es tan falaz como peligroso de cara a la solución de sus problemas presentes y futuros. Dicha concepción errónea deriva, en parte, de confundir sostenibilidad y conservación. No obstante, resulta oportuno recordar que las conclusiones derivadas de la presente revisión tienen un valor estrictamente académico y no justifican juicios morales improcedentes respecto a los derechos de los cazadores-recolectores.

Rectified Feature Matching for Spherical Panoramic Images

Spherical panoramic image processing has received renewed interest in the fields of photogrammetry and computer vision. The difficulty in spherical matching is largely due to inevitable image distortions introduced from the equirectangular projection. In this paper, we present an effective strategy for tackling the problem of distortion to improve the performance of spherical image matching. The effectiveness of the rectified matching is evaluated with simulated data and compared with state-of-art methods. In addition, experiments with respect to matching between omnidirectional and planar images, establishing 2D-to-3D correspondence with lidar, and the pose estimation of a spherical image sequence are conducted. The results verify the utility of the proposed method, which provides stable and evenly distributed corresponding points, and it is suitable for integration with conventional techniques for further 3D exploitation of imagery.

Local File Disclosure Vulnerability: A Case Study of Public-Sector Web Applications

Almost all public-sector organisations in Bangladesh now offer online services through web applications, along with the existing channels, in their endeavour to realise the dream of a ‘Digital Bangladesh’. Nations across the world have joined the online environment thanks to training and awareness initiatives by their government. File sharing and downloading activities using web applications have now become very common, not only ensuring the easy distribution of different types of files and documents but also enormously reducing the time and effort of users. Although the online services that are being used frequently have made users’ life easier, it has increased the risk of exploitation of local file disclosure (LFD) vulnerability in the web applications of different public-sector organisations due to unsecure design and careless coding. This paper analyses the root cause of LFD vulnerability, its exploitation techniques, and its impact on 129 public-sector websites in Bangladesh by examining the use of manual black box testing approach.

Designing cultural multilevel selection research for sustainability science

Humans stand out among animals in that we cooperate in large groups to exploit natural resources, and accumulate resource exploitation techniques across generations via cultural learning. This uniquely human form of adaptability is in large part to blame for the global sustainability crisis. This paper builds on cultural evolutionary theory to conceptualize and study environmental resource use and overexploitation. Human social learning and cooperation, particularly regarding social dilemmas, result in both sustainability crises and solutions. Examples include the collapse of global fisheries, and multilateral agreements to halt ozone depletion. We propose an explicitly evolutionary approach to study how crises and solutions may emerge, persist, or disappear. We first present a brief primer on cultural evolution to define group-level cultural adaptations for resource use. This includes criteria for identifying where group-level cultural adaptations may exist, and if a cultural evolutionary approach can be implemented in studying a given system. We then outline a step-by-step process for designing a study of group-level cultural adaptation, including the major methodological considerations that researchers should address in study design, such as tradeoffs between validity and control, issues of time scale, and the value of both qualitative and quantitative data and analysis. We discuss how to evaluate multiple types of evidence synthetically, including historical accounts, new and existing data sets, case studies, and simulations. The electronic supplement provides a tutorial and simple computer code in the R environment to lead users from theory to data to an illustration of an empirical test for group-level adaptations in sustainability research.

A survey of the double‐fetch vulnerabilities

SummaryRace conditions widely exist in concurrent programs, and concurrency errors caused by harmful races could lead to severe system failures. A double fetch is a typical situation when the system kernel inevitably accesses user space data multiple times, and it turns into a vulnerability when the data consistency is violated under a special race condition between kernel and user space. In this survey, we present the first (to the best of our knowledge) comprehensive study on double‐fetch vulnerabilities in the real world. Our study is based on the investigation of 91 real‐world double‐fetch vulnerabilities collected from the CVE database and other relevant reports, which covers a period of recent 12 years. Our work reveals some interesting findings on the double‐fetch vulnerabilities, ranging from the various occurrences across different kernels and system levels to the involvement of specific patterns. We also divide the consequences that are usually caused by the double‐fetch vulnerabilities into four categories and discuss each, summarize viable exploitation techniques from existing works, provide useful guidances to detect and practical strategies to prevent double‐fetch vulnerabilities.

ANTHROPOGENIC CHANGES OF THE “OLD COPPER BASIN” AREA LANDSCAPE (NORTH-SUDETIC SYNCLINORIUM) IN THE LIGHT OF LIDAR-BASED GEOMORPHOMETRIC ANALYSIS AND ARCHIVAL DATA

While the history, techniques of exploitation and deposit parameters of the copper ores in the North-Sudetic Synclinorium have been the subject of numerous investigations, the transformations of the terrain in the so-called “Old Copper Basin” (Lower Silesia, SW Poland) have not been analysed in detail before. This paper is intended to complement this gap. The authors present the results of the detailed geomorphometric analysis of the post-mining forms related directly to the copper mining. The LiDAR-based, high-resolution Digital Terrain Models (DTMs), which have been used in the analysis and description of the landforms, are currently considered as the most accurate and precise 3D-spatial data available in the numerical form. The following anthropogenic forms are distinguished in the study area: large- and small-scale ground deformations (depressions and small sinkholes), abandoned quarries, and forms associated with the exploitation and storage of the flotation wastes – post-flotation tailings and dumps. Our investigations have allowed visualization of the spatial distribution of the forms, estimation of their total volume as well as perspectives of their reclamation and protection.

Design of digital IIR filter with low quantization error using hybrid optimization technique

In this paper, a hybrid optimization technique based on particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm is presented for the optimal design of infinite impulse response (IIR) filter with low quantization effect. In this method, different variants of PSO have been exhaustively tested, and the time varying coefficients-PSO (TVC-PSO) is used to formulate a new hybrid technique for better exploitation and exploration, which is further modified by sorting and replacement mechanism of Scout Bee from ABC algorithm. For designing IIR filter, an objective function is constructed that satisfies the absolute error including peak ripples in passband and stopband regions in frequency domain, while stability of designed filter is confirmed by exploiting the lattice form structure during iterative computation that also reduces computation complexity. Several attributes such as passband error $$(e_{\mathrm{p}})$$ , stopband error $$(e_{\mathrm{s}})$$ , and stopband attenuation $$(A_{\mathrm{s}})$$ are used to measure the performance of proposed algorithm. The simulation results presented in this paper evidence that this technique can be effectively used for designing digital IIR filter with higher filter taps, and low quantization effect for fixed number of bits.

LOCALIZATION OF PATHOLOGY ON COMPLEX ARCHITECTURE BUILDING SURFACES

Abstract. The technology of 3D laser scanning is considered as one of the most common methods for heritage documentation. The point clouds that are being produced provide information of high detail, both geometric and thematic. There are various studies that examine techniques of the best exploitation of this information. In this study, an algorithm of pathology localization, such as cracks and fissures, on complex building surfaces is being tested. The algorithm makes use of the points’ position in the point cloud and tries to distinguish them in two groups-patterns; pathology and non-pathology. The extraction of the geometric information that is being used for recognizing the pattern of the points is being accomplished via Principal Component Analysis (PCA) in user-specified neighborhoods in the whole point cloud. The implementation of PCA leads to the definition of the normal vector at each point of the cloud. Two tests that operate separately examine both local and global geometric criteria among the points and conclude which of them should be categorized as pathology. The proposed algorithm was tested on parts of the Gazi Evrenos Baths masonry, which are located at the city of Giannitsa at Northern Greece.

Cluster spacing optimization of multi-stage fracturing in horizontal shale gas wells based on stimulated reservoir volume evaluation

The multi-stage fracturing in horizontal well is a common technique for shale gas reservoir exploitation, in which cluster spacing governs the fracturing performance. Undersized cluster spacing might make the stimulated reservoir volume (SRV), activated by the respective hydraulic fracture, excessively overlap with each other, while oversized cluster spacing might leave a large unstimulated volume between neighboring hydraulic fractures; in either case, fracturing would be inefficient. Previous design of cluster spacing has failed to maximize the SRV due to the absence of a dynamic SRV evaluation model. A numerical model of SRV evaluation in shale reservoir was established by integrating four main modules, including fracture propagation, reservoir pressure distribution, formation stress distribution, and natural fracture failure criterion. Then, a method to optimize cluster spacing was developed with the goal of maximizing SRV. In order to validate this method, it was applied in Fuling shale gas reservoir in Southwest China to determine the optimal cluster spacing. The sensitivity of key parameters on the optimal cluster spacing has been analyzed. This research proposed a compelling cluster spacing optimization method, which could reduce the uncertainty in cluster spacing design, and provides some new insights on the optimal design of multi-stage fracturing in horizontal shale gas well.

Describing Geospatial Assets in the Web of Data: A Metadata Management Scenario

Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify editing tools that can be easily tailored to the specificities of a given project, workgroup, and Community of Practice. Our solution is a template-driven metadata editing tool that can be customised to any XML-based schema. Its output is constituted by standards-compliant metadata records that also have a semantics-aware counterpart eliciting novel exploitation techniques. Moreover, external data sources can easily be plugged in to provide autocompletion functionalities on the basis of the data structures made available on the Web of Data. Beside presenting the essentials on customisation of the editor by means of two use cases, we extend the methodology to the whole life cycle of geospatial metadata. We demonstrate the novel capabilities enabled by RDF-based metadata representation with respect to traditional metadata management in the geospatial domain.

Reading of Ground-Penetrating Radar (GPR) Images of Prehistoric Flint Mine; Case Study from Krzemionki Opatowskie Archaeological Site In Central Poland

Abstract Geophysical surveys conducted in order to map tunnels and vertical shafts at the Neolithic chert mining field Krzemionki used a ground-penetrating radar(GPR to test hypotheses regarding orientation, depth and subsurface complexity of these voids.Using two-dimensional reflection profiles the vertical shafts, now mostly filled with lithic debris, were easily visible. Amplitude mapping visualized debris at shaft margins as well as a collapsed material inside the voids. Some shallower horizontal tunnels were also visible as sub-horizontal planar reflections generated from both ceiling and floors of these void spaces. Extension of these interpretations to un-mapped areas of the ancient mining district and complexity of these prehistoric mining features could be examined to determine excavation intensity and exploitation techniques used during the Neolithic.

On local domain symmetry for model expansion

AbstractSymmetry in combinatorial problems is an extensively studied topic. We continue this research in the context of model expansion problems, with the aim of automating the workflow of detecting and breaking symmetry. We focus onlocal domain symmetry, which is induced by permutations of domain elements, and which can be detected on a first-order level. As such, our work is a continuation of the symmetry exploitation techniques of model generation systems, while it differs from more recent symmetry breaking techniques in answer set programming which detect symmetry on ground programs. Our main contributions are sufficient conditions for symmetry of model expansion problems, the identification oflocal domain interchangeability, which can often be broken completely, and efficient symmetry detection algorithms for both local domain interchangeability as well as local domain symmetry in general. Our approach is implemented in the model expansion system IDP, and we present experimental results showcasing the strong and weak points of our approach compared tosbass, a symmetry breaking technique for answer set programming.

Scalable analytics to detect DNS misuse for establishing stealthy communication channels

The Domain Name System (DNS) protocol is one of the few application protocols that are allowed to cross network perimeters of organizations. However, comprehensive monitoring of DNS traffic has been often overlooked in many organizations' cybersecurity strategies. As such, DNS provides a highly attractive channel for advanced threat actors and botnet operators to establish hard-to-block and stealthy communication channels between infected devices and command-and-control (C&C) infrastructures. Fast-fluxing (FF) and domain name generation algorithms (DGAs) are two well-known public DNS exploitation techniques to build agile C&C infrastructures. The detection of FF and DGA domain names is a big data problem, as it requires analyzing millions of DNS queries and replies over extended time periods. In this paper, we propose two algorithms to perform DNS analytics and effectively detect FF and DGA domain names. More importantly, we describe how the algorithms are implemented using two big data processing models: MapReduce and Feature Collection and Correlation Engine. The algorithms and implementation proposed are iterative and scale over long analysis periods. We describe the implementations and provide an evaluation complemented with case studies on 50 days of real-world DNS data consisting of more than 40 billion events, collected within a large corporate network.

HYBRID-BASED DENSE STEREO MATCHING

Abstract. Stereo matching generating accurate and dense disparity maps is an indispensable technique for 3D exploitation of imagery in the fields of Computer vision and Photogrammetry. Although numerous solutions and advances have been proposed in the literature, occlusions, disparity discontinuities, sparse texture, image distortion, and illumination changes still lead to problematic issues and await better treatment. In this paper, a hybrid-based method based on semi-global matching is presented to tackle the challenges on dense stereo matching. To ease the sensitiveness of SGM cost aggregation towards penalty parameters, a formal way to provide proper penalty estimates is proposed. To this end, the study manipulates a shape-adaptive cross-based matching with an edge constraint to generate an initial disparity map for penalty estimation. Image edges, indicating the potential locations of occlusions as well as disparity discontinuities, are approved by the edge drawing algorithm to ensure the local support regions not to cover significant disparity changes. Besides, an additional penalty parameter 𝑃𝑒 is imposed onto the energy function of SGM cost aggregation to specifically handle edge pixels. Furthermore, the final disparities of edge pixels are found by weighting both values derived from the SGM cost aggregation and the U-SURF matching, providing more reliable estimates at disparity discontinuity areas. Evaluations on Middlebury stereo benchmarks demonstrate satisfactory performance and reveal the potency of the hybrid-based dense stereo matching method.

HYBRID-BASED DENSE STEREO MATCHING

Stereo matching generating accurate and dense disparity maps is an indispensable technique for 3D exploitation of imagery in the fields of Computer vision and Photogrammetry. Although numerous solutions and advances have been proposed in the literature, occlusions, disparity discontinuities, sparse texture, image distortion, and illumination changes still lead to problematic issues and await better treatment. In this paper, a hybrid-based method based on semi-global matching is presented to tackle the challenges on dense stereo matching. To ease the sensitiveness of SGM cost aggregation towards penalty parameters, a formal way to provide proper penalty estimates is proposed. To this end, the study manipulates a shape-adaptive cross-based matching with an edge constraint to generate an initial disparity map for penalty estimation. Image edges, indicating the potential locations of occlusions as well as disparity discontinuities, are approved by the edge drawing algorithm to ensure the local support regions not to cover significant disparity changes. Besides, an additional penalty parameter 𝑃𝑒 is imposed onto the energy function of SGM cost aggregation to specifically handle edge pixels. Furthermore, the final disparities of edge pixels are found by weighting both values derived from the SGM cost aggregation and the U-SURF matching, providing more reliable estimates at disparity discontinuity areas. Evaluations on Middlebury stereo benchmarks demonstrate satisfactory performance and reveal the potency of the hybrid-based dense stereo matching method.

Advanced interference management technique: potentials and limitations

Interference management has the potential to improve spectrum efficiency in current and next generation wireless systems (e.g., 3GPP LTE and IEEE 802.11). Recently, new paradigms for interference management have emerged to tackle interference in a general class of wireless networks: interference shaping and interference exploitation. Interference shaping is a technique that creates a particular linear combination of interference signals when transmitters propagate signals to minimize the aggregated interference effect at each receiver. Interference exploitation is a method that harnesses interference in decoding as side information to improve data rates. Both approaches offer better performance in interference-limited communication regimes than traditionally thought possible. This article provides a high-level overview of several different interference shaping and exploitation techniques for single-hop, multihop, and multi-way network architectures with graphical illustrations. The article concludes with a discussion of practical challenges associated with adopting sophisticated interference management strategies in the future.

Hyperspectral Unmixing Based on Local Collaborative Sparse Regression

Spectral unmixing is an important technique for hyperspectral data exploitation. In order to solve the unmixing problem using a collection of previously available spectral signatures (i.e., a spectral library), sparse unmixing aims at finding the optimal subset of endmembers to represent the pixels in a hyperspectral image. The classic collaborative unmixing globally assumes that all pixels in a hyperspectral scene share the same active set of endmembers. This assumption rarely holds in practice, as endmembers tend to appear localized in spatially homogeneous areas rather than spread over the whole image. To address this limitation, in this letter, we introduce a new strategy to preserve local collaborativity for sparse hyperspectral unmixing. The proposed approach, which is called local collaborative sparse unmixing, considers the fact that endmember signatures generally appear distributed in local spatial regions instead of uniformly distributed throughout the scene. The proposed approach, which includes spatial information in the standard collaborative formulation, has been experimentally validated using both simulated and real hyperspectral data sets.

A Cost-Sensitive Decision Tree Learning Algorithm Based on a Multi-Armed Bandit Framework

This paper develops a new algorithm for inducing cost-sensitive decision trees that is inspired by the multi-armed bandit problem, in which a player in a casino has to decide which slot machine (bandit) from a selection of slot machines is likely to pay out the most. Game Theory proposes a solution to this multi-armed bandit problem by using a process of exploration and exploitation in which reward is maximized. This paper utilizes these concepts to develop a new algorithm by viewing the rewards as a reduction in costs, and utilizing the exploration and exploitation techniques so that a compromise between decisions based on accuracy and decisions based on costs can be found. The algorithm employs the notion of lever pulls in the multi-armed bandit game to select the attributes during decision tree induction, using a look-ahead methodology to explore potential attributes and exploit the attributes which maximizes the reward. The new algorithm is evaluated on fifteen datasets and compared to six well-known algorithms J48, EG2, MetaCost, AdaCostM1, ICET and ACT. The results obtained show that the new multi-armed based algorithm can produce more cost-effective trees without compromising accuracy. The paper also includes a critical appraisal of the limitations of the new algorithm and proposes avenues for further research.