A Flexible Framework for Wide‐Spectrum VR Development

2010 ◽  
Vol 19 (4) ◽  
pp. 302-312 ◽  
Author(s):  
Franco Tecchia
Keyword(s):  
System Organization ◽  
Wide Spectrum ◽  
General Purpose ◽  
Development Environment ◽  
Wide Range ◽  
Flexible Framework ◽  
Complex Cluster ◽  
Scripting Language ◽  
Visualization Systems ◽  
Immersive Visualization

This paper presents results and experiences coming from 10 years of development and use of XVR, a flexible, general-purpose framework for virtual reality (VR) development. The resulting architecture, that comes under the form of a self-sufficient integrated development environment (IDE) organized around a dedicated scripting language and a virtual machine, is able to accommodate a wide range of applications needs, ranging from simple Web3D applications to motion-based simulators or complex cluster-based immersive visualization systems. Within the framework a common, archetypical structure is used for any application, showing how inhomogeneous needs and technologies can be effectively covered by using a single, rather simple, system organization. We also show how the framework flexibility allows for innovative development techniques such as multiple frameworks coexisting within a single, tightly integrated, VR application.

Cucurbitacins as Anticancer Agents: A Patent Review

2019 ◽  
Vol 14 (2) ◽  
pp. 133-143 ◽  
Author(s):  
Hidayat Hussain ◽  
Ivan R. Green ◽  
Muhammad Saleem ◽  
Khanzadi F. Khattak ◽  
Muhammad Irshad ◽  
...  
Keyword(s):  
Anticancer Agents ◽  
Wide Spectrum ◽  
Biological Effects ◽  
Therapeutic Effects ◽  
Cytotoxic Effects ◽  
Natural Sources ◽  
Oh Groups ◽  
Drug Candidates ◽  
The Past ◽  
Wide Range

Background: Cucurbitacins belong to a group of tetracyclic triterpenoids that display a wide range of biological effects. In the past, numerous cucurbitacins have been isolated from natural sources and many active compounds have been synthesized using the privileged scaffold in order to enhance its cytotoxic effects. Objective: his review covers patents on the therapeutic effects of natural cucurbitacins and their synthetic analogs published during the past decade. By far, the majority of patents published are related to cancer and Structure-Activity Relationships (SAR) of these compounds are included to lend gravitas to this important class of natural products. Methods: The date about the published patents was downloaded via online open access patent databases. Results: Cucurbitacins display significant cytotoxic properties, in particular cucurbitacins B and D which possess very potent effects towards a number of cancer cells. Numerous cucurbitacins isolated from natural sources have been derivatized through chemical modification at the C(2)-OH and C(25)- OH groups. Most importantly, an acyl ester of the C(25)-OH and, iso-propyl, n-propyl and ethyl ether groups of the C(2)-OH demonstrated the most increased cytotoxic activity. Conclusion: The significant cytotoxic effects of natural and semi-synthetic cucurbitacins make them attractive as new drug candidates. Moreover, cucurbitacins have the capability to form conjugates with other anticancer drugs which will synergistically enhance their anticancer effects. The authors believe that in order to get lead compounds, there should be a greater focus on the synthesis of homodimers, heterodimers, and halo derivatives of cucurbitacins. In the opinion of the authors the analysis of the published patents on the cucurbitacins indicates that these compounds can be developed into a regimen to treat a wide spectrum of cancers.

scholarly journals Greater trochanteric pain syndrome: Evaluation and management of a wide spectrum of pathology

2021 ◽  
Vol 9 ◽  
pp. 205031212110225
Author(s):  
Mark A Pianka ◽  
Joseph Serino ◽  
Steven F DeFroda ◽  
Blake M Bodendorfer
Keyword(s):  
Wide Spectrum ◽  
Pain Syndrome ◽  
Operative Management ◽  
Hip Pain ◽  
Greater Trochanteric Pain Syndrome ◽  
Trochanteric Bursitis ◽  
Treatment Indications ◽  
Careful Clinical Examination ◽  
Wide Range ◽  
Tendon Pathology

Greater trochanteric pain syndrome is a common cause of lateral hip pain, encompassing a spectrum of disorders, including trochanteric bursitis, abductor tendon pathology, and external coxa saltans. Greater trochanteric pain syndrome is primarily a clinical diagnosis, and careful clinical examination is essential for accurate diagnosis and treatment. A thorough history and physical exam may be used to help differentiate greater trochanteric pain syndrome from other common causes of hip pain, including osteoarthritis, femoroacetabular impingement, and lumbar stenosis. Although not required for diagnosis, plain radiographs and magnetic resonance imaging may be useful to exclude alternative pathologies or guide treatment of greater trochanteric pain syndrome. The majority of patients with greater trochanteric pain syndrome respond well to conservative management, including physical therapy, non-steroidal anti-inflammatory drugs, and corticosteroid injections. Operative management is typically indicated in patients with chronic symptoms refractory to conservative therapy. A wide range of surgical options, both open and endoscopic, are available and should be guided by the specific etiology of pain. The purpose of this review is to highlight pertinent clinical and radiographic features used in the diagnosis and management of greater trochanteric pain syndrome. In addition, treatment indications, techniques, and outcomes are described.

scholarly journals A Generalization Performance Study Using Deep Learning Networks in Embedded Systems

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1031
Author(s):  
Joseba Gorospe ◽  
Rubén Mulero ◽  
Olatz Arbelaitz ◽  
Javier Muguerza ◽  
Miguel Ángel Antón
Keyword(s):  
Deep Learning ◽  
Embedded Systems ◽  
Embedded System ◽  
General Purpose ◽  
Learning Networks ◽  
Performance Study ◽  
Learning Techniques ◽  
Wide Range ◽  
Learning Architectures

Deep learning techniques are being increasingly used in the scientific community as a consequence of the high computational capacity of current systems and the increase in the amount of data available as a result of the digitalisation of society in general and the industrial world in particular. In addition, the immersion of the field of edge computing, which focuses on integrating artificial intelligence as close as possible to the client, makes it possible to implement systems that act in real time without the need to transfer all of the data to centralised servers. The combination of these two concepts can lead to systems with the capacity to make correct decisions and act based on them immediately and in situ. Despite this, the low capacity of embedded systems greatly hinders this integration, so the possibility of being able to integrate them into a wide range of micro-controllers can be a great advantage. This paper contributes with the generation of an environment based on Mbed OS and TensorFlow Lite to be embedded in any general purpose embedded system, allowing the introduction of deep learning architectures. The experiments herein prove that the proposed system is competitive if compared to other commercial systems.

scholarly journals MXenes for future nanophotonic device applications

Nanophotonics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1831-1853
Author(s):  
Jaeho Jeon ◽  
Yajie Yang ◽  
Haeju Choi ◽  
Jin-Hong Park ◽  
Byoung Hun Lee ◽  
...  
Keyword(s):  
Solar Cells ◽  
Transition Metal ◽  
Wide Spectrum ◽  
Building Blocks ◽  
Optoelectronic Device ◽  
High Yield ◽  
Saturable Absorption ◽  
Nanophotonic Device ◽  
Wide Range ◽  
Device Applications

AbstractTwo-dimensional (2D) layers of transition metal carbides, nitrides, or carbonitrides, collectively referred to as MXenes, are considered as the new family of 2D materials for the development of functional building blocks for optoelectronic and photonic device applications. Their advantages are based on their unique and tunable electronic and optical properties, which depend on the modulation of transition metal elements or surface functional groups. In this paper, we have presented a comprehensive review of MXenes to suggest an insightful perspective on future nanophotonic and optoelectronic device applications based on advanced synthesis processes and theoretically predicted or experimentally verified material properties. Recently developed optoelectronic and photonic devices, such as photodetectors, solar cells, fiber lasers, and light-emitting diodes are summarized in this review. Wide-spectrum photodetection with high photoresponsivity, high-yield solar cells, and effective saturable absorption were achieved by exploiting different MXenes. Further, the great potential of MXenes as an electrode material is predicted with a controllable work function in a wide range (1.6–8 eV) and high conductivity (~104 S/cm), and their potential as active channel material by generating a tunable energy bandgap is likewise shown. MXene can provide new functional building blocks for future generation nanophotonic device applications.

scholarly journals A flexible framework for anomaly Detection via dimensionality reduction

2021 ◽  
Author(s):  
Alireza Vafaei Sadr ◽  
Bruce A. Bassett ◽  
M. Kunz
Keyword(s):  
Anomaly Detection ◽  
Dimensionality Reduction ◽  
Dimensional Space ◽  
High Dimensions ◽  
Detection Algorithms ◽  
Latent Space ◽  
Wide Range ◽  
Flexible Framework ◽  
Online Anomaly Detection ◽  
Python Package

AbstractAnomaly detection is challenging, especially for large datasets in high dimensions. Here, we explore a general anomaly detection framework based on dimensionality reduction and unsupervised clustering. DRAMA is released as a general python package that implements the general framework with a wide range of built-in options. This approach identifies the primary prototypes in the data with anomalies detected by their large distances from the prototypes, either in the latent space or in the original, high-dimensional space. DRAMA is tested on a wide variety of simulated and real datasets, in up to 3000 dimensions, and is found to be robust and highly competitive with commonly used anomaly detection algorithms, especially in high dimensions. The flexibility of the DRAMA framework allows for significant optimization once some examples of anomalies are available, making it ideal for online anomaly detection, active learning, and highly unbalanced datasets. Besides, DRAMA naturally provides clustering of outliers for subsequent analysis.

scholarly journals An information theoretic approach to link prediction in multiplex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Large Scale ◽  
Similarity Measures ◽  
Prediction Method ◽  
General Purpose ◽  
Fast Method ◽  
Theoretic Approach ◽  
Multiplex Networks ◽  
Wide Range

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.

scholarly journals Towards an accurate description of perovskite ferroelectrics: exchange and correlation effects

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Simuck F. Yuk ◽  
Krishna Chaitanya Pitike ◽  
Serge M. Nakhmanson ◽  
Markus Eisenbach ◽  
Ying Wai Li ◽  
...  
Keyword(s):  
Density Functional ◽  
General Purpose ◽  
Correlation Effects ◽  
Lattice Constants ◽  
Bulk Solids ◽  
Wide Range ◽  
Exchange Enhancement ◽  
Experimental Values ◽  
Similar Accuracy ◽  
Ferroelectric Oxides

Abstract Using the van der Waals density functional with C09 exchange (vdW-DF-C09), which has been applied to describing a wide range of dispersion-bound systems, we explore the physical properties of prototypical ABO 3 bulk ferroelectric oxides. Surprisingly, vdW-DF-C09 provides a superior description of experimental values for lattice constants, polarization and bulk moduli, exhibiting similar accuracy to the modified Perdew-Burke-Erzenhoff functional which was designed specifically for bulk solids (PBEsol). The relative performance of vdW-DF-C09 is strongly linked to the form of the exchange enhancement factor which, like PBEsol, tends to behave like the gradient expansion approximation for small reduced gradients. These results suggest the general-purpose nature of the class of vdW-DF functionals, with particular consequences for predicting material functionality across dense and sparse matter regimes.

SYSTEMC IMPLEMENTATION AND PERFORMANCE EVALUATION OF A DECOUPLED GENERAL-PURPOSE MATRIX PROCESSOR

2010 ◽  
Vol 20 (02) ◽  
pp. 103-121 ◽  
Author(s):  
MOSTAFA I. SOLIMAN ◽  
ABDULMAJID F. Al-JUNAID
Keyword(s):  
Performance Evaluation ◽  
Matrix Multiplication ◽  
General Purpose ◽  
System Level ◽  
Memory Latency ◽  
Single Chip ◽  
Wide Range ◽  
Matrix Unit ◽  
And Performance ◽  
Vector Matrix

Technological advances in IC manufacturing provide us with the capability to integrate more and more functionality into a single chip. Today's modern processors have nearly one billion transistors on a single chip. With the increasing complexity of today's system, the designs have to be modeled at a high-level of abstraction before partitioning into hardware and software components for final implementation. This paper explains in detail the implementation and performance evaluation of a matrix processor called Mat-Core with SystemC (system level modeling language). Mat-Core is a research processor aiming at exploiting the increasingly number of transistors per IC to improve the performance of a wide range of applications. It extends a general-purpose scalar processor with a matrix unit. To hide memory latency, the extended matrix unit is decoupled into two components: address generation and data computation, which communicate through data queues. Like vector architectures, the data computation unit is organized in parallel lanes. However, on parallel lanes, Mat-Core can execute matrix-scalar, matrix-vector, and matrix-matrix instructions in addition to vector-scalar and vector-vector instructions. For controlling the execution of vector/matrix instructions on the matrix core, this paper extends the well known scoreboard technique. Furthermore, the performance of Mat-Core is evaluated on vector and matrix kernels. Our results show that the performance of four lanes Mat-Core with matrix registers of size 4 × 4 or 16 elements each, queues size of 10, start up time of 6 clock cycles, and memory latency of 10 clock cycles is about 0.94, 1.3, 2.3, 1.6, 2.3, and 5.5 FLOPs per clock cycle; achieved on scalar-vector multiplication, SAXPY, Givens, rank-1 update, vector-matrix multiplication, and matrix-matrix multiplication, respectively.

scholarly journals Framing the Values of Vernacular Architecture for a Value-Based Conservation: A Conceptual Framework

2021 ◽  
Vol 13 (9) ◽  
pp. 4974
Author(s):  
Obafemi A. P. Olukoya
Keyword(s):  
Vernacular Architecture ◽  
Conservation Strategy ◽  
Participatory Process ◽  
Value Assessment ◽  
A Value ◽  
Wide Range ◽  
Flexible Framework ◽  
Value Model ◽  
Contextual Values ◽  
Range Of Values

While a growing number of researchers have provided series of tough critiques of the typology-led heritage value assessment over the recent years, the impacts have been constrained by the continued obsession with expanding the list of the predetermined value typologies rather than escaping its limitations. While these sustained debates have provided important insights, this article argues that operationalizing these predetermined ‘one-size-fits-all’ value typologies is symptomatic of a number of shortcomings, especially in the context of capturing the pluralities of values in contextualized heritage such as vernacular architecture. It also often undermines inclusivity and participation in the valuing processes. However, rather than simply rejecting the values-based paradigm, this article proposes a conceptual value assessment framework that is informed by the theorization of vernacular architecture as a contextualized heritage. The proposed Vernacular Value Model (VVM) puts forward the ‘when(s)’ and ‘how(s)’ of amalgamating both technical and normative processes to capture the range of contextual values present in built vernacular heritage. To this end, this article posits that by drawing on such a proposed flexible framework, the conservation strategy for built vernacular heritage can be propagated as an inclusive and participatory process which captures the wide range of values for a more sustainable practices for conservation.

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