Low-level Capabilities Research Articles

High performance GPU graphics API abstraction layer in C# for real-time graphics

Real-Time rendering is the technique which allows us to have graphical applications in our everyday life, whether it is a 3D game or a tool with graphical user interface. Nowadays graphics rendering is handled by the GPU (Graphics Processing Unit) in our device. There are many layers of abstraction above the programming of GPUs through libraries and graphics engines, though the most low-level way of accessing a GPU in user-mode applications is using a Graphics API. Due to the need of high performance and low-level capabilities usually these APIs are used from C or C++, but we realized the need to utilize these APIs in higher level languages as well.In our approach we're using the .NET C# language for developing multi-platform real-time graphical applications instead of the C or C++ languages. Using the modern .NET environment, we're able to use Graphics APIs for rendering onto common .NET UI Frameworks while consuming all our previously implemented C# libraries and .NET technologies in the same application. To maintain compatibility with multiple platforms we're developing a library system allowing the use different Graphics APIs from the same C# source-code. The library system contains a Graphics API abstraction layer with multiple Graphics API implementations of this layer in C# and a C# to shader language compiler for cross-API shader development in C#.In this paper, we're proposing our considerations for implementing a library to be able to use the Vulkan and OpenGL APIs through a single C# codebase. We provide solutions for multi-platform rendering and dealing with the low-level challenges of using the two deeply different APIs, while maintaining performance capable to do real-time rendering.

Improved lightweight corrugated network design to auxetic perforated metamaterial

Auxetic metamaterials with peanut-shaped perforations are superior for durable morphing control applications due to its extremely low stress concentration level and controllable auxetic capability. However, there are some issues to be concerned for such metamaterials with complex cellular features, including (1) improving structure topology for higher material efficiency, (2) tunable Poisson's ratio from positive to negative, (3) characterization of full elastic properties. To this end, an improved lightweight design with orthogonal corrugated beams is proposed in this study to approximate the perforated auxetic structure and then its full anisotropic elastic constants are characterized by a distinctive computational homogenization model based on the eigenfunction expansion variational theory with simple implementation technique of periodic displacement constraints. The numerical model is verified by the experimental tests of three specimens with different geometrical topologies. Subsequently, the dependence of structural elastic responses on the microstructural configuration is highlighted towards an elevated understanding of cell-structure-property relationship. It is demonstrated that the local in-plane rotation of interconnected regions in unit cell under uniaxial loading contributes to the structural auxetic behavior. Also, it is feasible to achieve tailorable mechanical properties through flexible microstructural adjustment and a design criterion of the crucial zero Poisson's ratio is given by a polynomial in terms of the normalized amplitude and thickness of the curved beam. The results pave a way to the design and analysis of novel metamaterials with tunable mechanical properties.

Further Exploration of Deep Aggregation for Shadow Detection

Shadow detection is a fundamental challenge in the field of computer vision. It requires the network to understand the global semantics and local details of the image. All existing methods depend on the aggregation of the features of a multi-stage pre-trained convolution neural network but in comparison to high-level capabilities, low-level capabilities provide less to the detection performance. Using low-level features not only increases the complex difficulty of the network but also reduces the time efficiency. In this article, we propose a new shadow detector, which only uses high-level features and explores the complementary information between adjacent feature layers. Experiments show that the technique in this paper can accurately detect shadows and perform well compared with the most advanced methods. The detailed experiments performed in three public shadow detection datasets SUB, UCF, and ISTD demonstrate that the suggested method is efficient and stable.

The SemIoTic Ecosystem: A Semantic Bridge between IoT Devices and Smart Spaces

Smart space administration and application development is challenging in part due to the semantic gap that exists between the high-level requirements of users and the low-level capabilities of IoT devices. The stakeholders in a smart space are required to deal with communicating with specific IoT devices, capturing data, processing it, and abstracting it out to generate useful inferences. Additionally, this makes reusability of smart space applications difficult, since they are developed for specific sensor deployments. In this article, we present a holistic approach to IoT smart spaces, the SemIoTic ecosystem, to facilitate application development, space management, and service provision to its inhabitants. The ecosystem is based on a centralized repository, where developers can advertise their space-agnostic applications, and a SemIoTic system deployed in each smart space that interacts with those applications to provide them with the required information. SemIoTic applications are developed using a metamodel that defines high-level concepts abstracted from the smart space about the space itself and the people within it. Application requirements can be expressed then in terms of user-friendly high-level concepts, which are automatically translated by SemIoTic into sensor/actuator commands adapted to the underlying device deployment in each space. We present a reference implementation of the ecosystem that has been deployed at the University of California, Irvine and is abstracting data from hundreds of sensors in the space and providing applications to campus members.

Performance Dashboard Tool to Visualize Adaptive Resilience Maturity of Transportation Agencies

Incorporating adaptive resilience as a core value of transportation systems will equip transportation agencies to better address the increasing pace of future changes—both in climate and transportation system performance demands. Quantifiable measures are instrumental in incorporating adaptive resilience in agency organizational frameworks. This paper presents a dashboard tool that evaluates the maturity of adaptive resilience capabilities of a transportation agency, using an Adaptive Resilience (AR) Capability Maturity Model. A demonstrative example is presented to show the potential application of the dashboard tool and its implications for transportation system resilience planning. The example shows how the tool can facilitate identification of adaptive resilience capabilities that are at low maturity and thus may need prioritization for future resilience investments, and capabilities that are at a high maturity level and thus can be leveraged to enhance the lower-level capabilities. The AR performance dashboard tool may be used by transportation agencies to communicate their adaptive resilience efforts and maturity to stakeholders. It can also be used by practitioners to streamline and prioritize process improvements in adaptive resilience efforts.

Online estimation of inertia and frequency regulation capability based on small perturbation

Urged by the low-carbon economic policies, several studies have demonstrated that the vastly available renewable energy sources (RESs) are considered as the promising substitute for the energy-intensive fossil fuel synchronous generators (SGs). This means the power system will operate at low inertia level and frequency regulation capability (FRC), which is provided by conventional SGs. This may weaken the frequency dynamic regulation capability of the system under a contingency transient event. This paper, therefore, develops an inertia and FRC estimation method based on a small sinusoidal active power disturbance. Firstly, utilize the RESs (i.e., energy storage/photovoltaic/wind units and other programable devices) as a sinusoidal active power injected into a power system to obtain the frequency response in frequency domain, namely FR(s). Secondly, analyze the relation between the nodal inertia with SG or RES and the resonance frequency of the amplitude of FR(s), and the relation between the nodal FRC and the dc gain of the amplitude of FR(s), respectively. Based on the deduced relationships, an evaluation framework with the small sinusoidal perturbation for the inertia and FRC estimation is presented. Simulation results demonstrate the effectiveness of the proposed small perturbation-based estimation approach in the modified 9-bus test system. This is useful for the design of the appropriate frequency control strategies for the grid operators and planners.

Graph Convolutional Networks for Cross-Modal Information Retrieval

In recent years, due to the wide application of deep learning and more modal research, the corresponding image retrieval system has gradually extended from traditional text retrieval to visual retrieval combined with images and has become the field of computer vision and natural language understanding and one of the important cross-research hotspots. This paper focuses on the research of graph convolutional networks for cross-modal information retrieval and has a general understanding of cross-modal information retrieval and the related theories of convolutional networks on the basis of literature data. Modal information retrieval is designed to combine high-level semantics with low-level visual capabilities in cross-modal information retrieval to improve the accuracy of information retrieval and then use experiments to verify the designed network model, and the result is that the model designed in this paper is more accurate than the traditional retrieval model, which is up to 90%.

Innovation-based strategic flexibility (ISF): Role of CEO ties with marketing and R&D

In this research, using a capability perspective, we first define innovation based, strategic flexibility (ISF) as consisting of three lower-level capabilities- market sensing, resource reconfiguration, and proactiveness; then link it to new-product/innovation outcomes, and develop a new metric of ISF that is input–output based. This metric captures a firm’s realized flexibility in translating market opportunities into innovation output. We then examine the role of CEO ties with marketing and R&D in driving a firm's ISF. Combining survey data of 191 CEOs with objective performance data, we find that (a) ISF is positively influenced by the frequency and duration of the CEO's relationship with the two functional units, but negatively influenced by CEO's relationship closeness, and (b) ISF contributes to future profit growth of firms. We test the robustness of our findings to the potential violation of sequential-ignorability assumption as defined in the causal mediation literature and find the results to be robust. The results provide insights into the role of CEO characteristics in driving innovation, and upper echelon’s contributions to marketing.

Empathy framework for embodied conversational agents

Empathy is a complex socio-emotional behavior that results from the interaction between affective and cognitive mechanisms. Equipping embodied conversational agents (ECAs) with empathic capacity can benefit from the integration and evaluation of these low and high level capabilities in a hierarchical manner. Following the theoretical background on empathic behavior in humans, this paper presents a framework to equip ECAs with real time multi-modal empathic interaction capabilities. We present the implementation of this framework, which includes basic dialogue capabilities as well as three levels of empathic behavior in a conversational scenario. Our approach is an inclusive stand on modeling levels of empathy and provides a baseline behavior for empathic interaction.

The long march to catch-up: A history-friendly model of China’s mobile communications industry

This paper develops a history-friendly model of the process of catch-up by Chinese firms in the mobile communications industry. It aims to explain how the sectoral environment in terms of segmented markets and generational technological change facilitated the catch-up of domestic firms with respect to foreign multinationals. Segmented markets provided a nurturing environment in peripheral markets for the survival of domestic firms starting with low level capabilities in their infant stage. Generational technological change opened windows of opportunities for domestic firms to catch-up with foreign multinationals in new product segments. Segmented markets and generational technological change allowed domestic firms to leverage their initial advantages in peripheral markets to catch-up in core markets. Counterfactual simulations highlight that the process of catch-up was facilitated by relatedness across technological generations. This paper contributes to the literature on catch-up and industry evolution by illustrating the role of technological change and market regimes in the process of catching-up.

Pengaruh Model Pembelajaran Kooperatif Tipe Numbered Head Together (NHT) Terhadap Hasil Belajar Matematika Siswa Kelas VII Berdasarkan Level Kemampuan Matematis

This study examines the problem of improving mathematics learning outcomes among students with cooperative learning model NHT type and conventional learning approaches is reviewed as a whole and for each level of mathematical ability (high, medium, and low). This research is a quasi-experimental research design Nonequivalent Control Group Design uses Simple Random Sampling technique. The population in this study were students of class VII in a private junior high school in the city of Pekanbaru in Riau in the academic year 2014/2015. While the sample is graders VII2 as control class and class VII2 as an experimental class. The instrument used in this study is the mathematics achievement test. Quantitative analysis was performed using two mean difference test. The results showed that: (1) there is significant implementation of cooperative learning model NHT on the results of students' mathematics learning is reviewed as a whole and the level of ability was; (2) there is no effect of the application of cooperative learning model NHT towards mathematics learning outcomes of students based on high and low-level capabilities.

Semi-automatic rule-based domain terminology and software feature-relevant information extraction from natural language user manuals

Mature software systems comprise a vast number of heterogeneous system capabilities which are usually requested by different groups of stakeholders and which evolve over time. Software features describe and bundle low level capabilities logically on an abstract level and thus provide a structured and comprehensive overview of the entire capabilities of a software system. Software features are often not explicitly managed. Quite the contrary, feature-relevant information is often spread across several software engineering artifacts (e.g., user manual, issue tracking systems). It requires huge manual effort to identify and extract feature-relevant information from these artifacts in order to make feature knowledge explicit. In this paper we present a two-step-approach to extract feature-relevant information from a user manual: First we semi-automatically extract a domain terminology from a natural language user manual based on linguistic patterns. Then, we apply natural language processing techniques based on the extracted domain terminology and structural sentence information. Our approach is able to extract atomic feature-relevant information with an F1-score of at least 92.00%. We describe the implementation of the approach as well as evaluations based on example sections of a user manual taken from industry.

Pengaruh Model Pembelajaran Kooperatif Tipe Numbered Head Together (NHT) Terhadap Hasil Belajar Matematika Siswa Kelas VII Berdasarkan Level Kemampuan Matematis

This study examines the problem of improving mathematics learning outcomes among students with cooperative learning model NHT type and conventional learning approaches is reviewed as a whole and for each level of mathematical ability (high, medium, and low). This research is a quasi-experimental research design Nonequivalent Control Group Design uses Simple Random Sampling technique. The population in this study were students of class VII in a private junior high school in the city of Pekanbaru in Riau in the academic year 2014/2015. While the sample is graders VII2 as control class and class VII2 as an experimental class. The instrument used in this study is the mathematics achievement test. Quantitative analysis was performed using two mean difference test. The results showed that: (1) there is significant implementation of cooperative learning model NHT on the results of students' mathematics learning is reviewed as a whole and the level of ability was; (2) there is no effect of the application of cooperative learning model NHT towards mathematics learning outcomes of students based on high and low-level capabilities.

Context‐awareness over transient cloud in D2D networks: energy performance analysis and evaluation

AbstractThe exponential increase in the number and types of mobile devices, along with their ever‐growing sets of capabilities, have enabled the development of new architectures that aim to harness such heterogeneity. Transient clouds are examples of mobile clouds, which are created on‐the‐fly by the devices present in an environment to share their physical resources (e.g. CPU, memory and network) and would disappear as the nodes leave the network. They enable a device to go beyond its own physical limitations through utilising the capabilities offered by nearby devices over an ad hoc network. This idea exploits the device‐to‐device (D2D) communications paradigm, which allows two nearby devices to communicate with each other in the licenced cellular bandwidth without a base station involved.In this paper, we present a transient context‐aware cloud (TCAC) paradigm based on the assumption that the nodes of the network care more about providing/learning higher level functionalities rather than lower level capabilities in D2D scenario. The proposed architecture, realised by using a WiFi Direct, can be portable through any paradigm, which exploits the D2D communications, so opening the doors to forthcoming 5G scenarios.We present a prototype implementation of our architecture over Android smartphones connected via WiFi Direct along with the performance metrics (power/energy consumption and accuracy) to show the benefits of TCAC. A theoretical and analytical model for the energy consumption related to a device within the TCAC is provided as well. Copyright © 2015 John Wiley & Sons, Ltd.

Collaborative case-based reasoning for knowledge discovery of elders health assessment system.

The existing Elders Health Assessment (EHA) system based on single-case-library reasoning has low intelligence level, poor coordination, and limited capabilities of assessment decision support. To effectively support knowledge reuse of EHA system, this paper proposes collaborative case reasoning and applies it to the whole knowledge reuse process of EHA system. It proposes a multi-case library reasoning application framework of EHA knowledge reuse system, and studies key techniques such as case representation, case retrieval algorithm, case optimization and correction, and reuse etc.. In the aspect of case representation, XML-based multi-case representation for case organization and storage is applied to facilitate case retrieval and management. In the aspect of retrieval method, Knowledge-Guided Approach with Nearest-Neighbor is proposed. Given the complexity of EHA, Gray Relational Analysis with weighted Euclidean Distance is used to measure the similarity so as to improve case retrieval accuracy.

Flat Luneburg Lens via Transformation Optics for Directive Antenna Applications

The great flexibility offered by transformation optics for controlling electromagnetic radiation by virtually re-shaping the electromagnetic space has inspired a myriad of dream-tailored electromagnetic devices. Here we show a 3D-transformed microwave Luneburg lens antenna which demonstrates high directivity, low side-lobe level, broadband response and steerable capabilities. A conventional Luneburg lens is redesigned accounting for dielectric materials that implement a coordinate transformation, modifying the lens geometry to accommodate its size and shape for easy integration with planar microwave antenna applications. An all dielectric lens is manufactured following a thorough holistic analysis of ceramic materials with different volume fractions of bi-modal distributed titanate fillers. Fabrication and measurements of a 3-D flat Luneburg lens antenna validate the design and confirm a high-directivity performance. A directivity of 17.96 dBi, low side-lobe levels for both main planes ~ -26 dB, excellent directivity performance within the X-band and beam-steering up to 34 ° were achieved.

Capability hierarchy in electronic procurement and procurement process performance: An empirical analysis

This paper examines the interrelationship between two hierarchically structured functional capabilities pertinent in the organizational procurement process, and the impact of these capabilities on procurement process performance. These functional capabilities operate at different levels in an organization's procurement process. We draw upon resource- and knowledge-based views of the firm to theorize that in this hierarchy of information technology-enabled procurement capabilities, the higher-level capability – procurement integration competence – enables firms to develop and deploy a lower-level capability – digital procurement competence. Further, we theorize that the lower-level capability impacts procurement process performance directly and completely mediates the relationship between higher-level capability and performance. Thus, although performance is impacted directly only by the lower-level capability, the higher-level capability facilitates the development and use of the lower-level capability. Our research model is tested using survey data from a large sample of 412 manufacturing firms. The results provide strong support for the proposed research model. In particular, we find that as hypothesized, the impact of procurement integration competence on performance is completely mediated by digital procurement competence. Our results suggest that when examined at the procurement process level, the impact of higher-level capabilities may be manifested completely through the lower-level capabilities. Theoretical and practical implications of the research are discussed.

Understanding the Complexities and Resource Sustainability in Afram Plains, Ghana

The main objective of the study was to determine the key driving forces behind the ever increasing problem of tree species loss and environmental degradations in the Afram plains and propose management action areas for reducing the loss. The study used participatory research method tools to assess farmers' views on their livelihood strategies and the causes of dwindling forest resources in the area. There may be many forces jeopardising forest resources in the study area but charcoal production was reported as the single most important factor driving the loss of tree species in the area. Charcoal burning was becoming increasingly a full time occupation for many young people as their families struggle with poor soil fertility and declining agricultural productivity. There is, therefore, the need to consider financial and technological investment in agricultural diversification to be able to reduce biodiversity loss within the agroecosystems of the area. It will significantly help these forest dependent communities to diversify their economies and soften the impacts of charcoal production and farming activities on the agroecosystem biodiversity. In addition, due to low level capabilities of local people, an effective and efficient implementation of educational programs is needed to enhance their capabilities in managing agroecosystems. Finally, it worth emphasising that efforts to reduce forest tree species loss and environmental degradation will be jeopardised or eventually be unsustainable unless project initiators address cash income and energy needs of local people. Agroforestry systems including plantations development could be part of the solutions to sustainable management of the agroecosystems in the area.

Small-spatial scale changes in productivity of suprabenthic and infaunal crustaceans at the continental shelf of Ebro Delta (western Mediterranean)

Production ( P) and production/biomass ratio ( P/B) were estimated from 21 species of peracarid and eucarid crustaceans belonging to two different compartments (infauna: 10 species and suprabenthos: 11 species) using the Hynes size–frequency method. Calculations were based on 7 cruises performed between December 2002 and November 2003 in the continental shelf of the Ebro river delta (ED, Catalan Sea: northwestern Mediterranean). Within ED, P and P/B were compared between two neighbouring sites, one located on 47 m (S1), the other at 61 m (S2). The possible effects of natural variability on production were considered. Sediments in ED were muddy (%clay between 40 and 65%). No significant trend in production comparing S1 and S2 was detected, with 50% of species showing higher P value in S1, and 50% in S2. A significant trend emerged from P/B estimates, with 18 of 21 species showing higher P/B at S1. Similarly significant trends for infauna and suprabenthos were found after analyzing both compartments separately. It is suggested that the more significant P/B found on S1 both among infauna and suprabenthos could be caused by the higher temperature and organic matter content (%TOC) at S1. In multi-linear regression (MLR) models, differences in P between S1 and S2 were greater with increasing differences in the density of species ( RD) between sites. Differences were greater in infauna than in suprabenthos, and greater among rare species (those with low dominance, %D). P/B differences between S1 and S2 were mainly explained by %D and RD, and to a lesser extent by differences between sites in the mean size of species ( RW). In other words changes in P and P/B were not explained by removal of large size specimens. Some trawling activity occurred at S2, and it may alter the habitat of small macrofauna. In addition to natural variability, we discussed the possible influence of trawling disturbance on P and P/B, bearing in mind the feeding type, mobility, and dispersal capability of species. We suggest that amphipods of the genus Ampelisca, showing higher P/B on S1, characterized by low mobility (probably tube-dwellers), low trophic level (e.g. filter feeding strategies) and low dispersal capability (not free larvae), could be especially vulnerable to trawling impact.

Fabric Level and Application Level QoS Guarantees in Grid Computing

In the paper, a cross-layer optimization between application layer and fabric layer is proposed. The aim is to optimize the end-to-end quality of the dynamic grid application as well as efficiently utilizing the grid resources. The application layer QoS and fabric layer QoS are closely interrelated in Grids since the upper layer service is based on the lower level's capabilities. A fabric level and application level QoS scheduling algorithm is proposed. We formulate the integrated design of resource allocation and user QoS satisfaction control into a constrained optimization problem. The optimization framework provides a layered approach to the sum utility maximization problem. The application layer adaptively adjusts user's resource demand based on the current resource conditions, while the fabric layer adaptively allocates CPU, storage and bandwidth required by the upper layer.