• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.500-519
• /
• 2019

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

• ETRI Journal
• /
• v.41 no.2
• /
• pp.145-159
• /
• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.

• Current Optics and Photonics
• /
• v.3 no.1
• /
• pp.40-45
• /
• 2019

Adding tunability to biological light emitters offers an unprecedented technique in biological sensing and imaging. Here, we report a tunable, lithographic-free, planar, and ultrathin metal-insulator-metal (MIM) resonator capable of tuning the optical properties solely by a silk/sodium fluorescein hydrogel layer, a biocompatible light emitter. In water, the volume of the resonator was expanded by swelling, and then the resonant mode could be shifted. Simulations predicted the red-shifted resonance peak in transmission when the MIM was swollen in water. The red-shift could be attributed to the increase in the thickness of the silk hydrogel layer due to the absorbed water. The shift of the resonance could affect the fluorescence of the dye in the silk hydrogel layer.

• Advances in nano research
• /
• v.7 no.1
• /
• pp.51-61
• /
• 2019

This paper develops a four-unknown refined plate theory and the Galerkin method to investigate the size-dependent stability behavior of functionally graded material (FGM) under the thermal environment and the FGM having temperature-dependent material properties. In the current study two scale coefficients are considered to examine buckling behavior much accurately. Reuss micromechanical scheme is utilized to estimate the material properties of inhomogeneous nano-size plates. Governing differential equations, classical and non-classical boundary conditions are obtained by utilizing Hamiltonian principles. The results showed the high importance of considering temperature-dependent material properties for buckling analysis. Different influencing parametric on the buckling is studied which may help in design guidelines of such complex structures.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.200-206
• /
• 2021

Fraud in e-commerce transaction increased in the last decade especially with the increasing number of online stores and the lockdown that forced more people to pay for services and groceries online using their credit card. Several machine learning methods were proposed to detect fraudulent transaction. Neural networks showed promising results, but it has some few drawbacks that can be overcome using optimization methods. There are two categories of learning optimization methods, first-order methods which utilizes gradient information to construct the next training iteration whereas, and second-order methods which derivatives use Hessian to calculate the iteration based on the optimization trajectory. There also some training refinements procedures that aims to potentially enhance the original accuracy while possibly reduce the model size. This paper investigate the performance of several NN models in detecting fraud in e-commerce transaction. The backpropagation model which is classified as first learning algorithm achieved the best accuracy 96% among all the models.

• Smart Structures and Systems
• /
• v.30 no.3
• /
• pp.317-325
• /
• 2022

Among the approaches to the production of "green" energy, geothermal power systems are becoming quite popular in Europe. Their installation in existing buildings requires an extended, external pipes appendix and its laying operation needs a drilling activities nearby structural skeletons often designed to support static loads only, especially when ancient buildings are targeted. This contribution reports and discusses the experimental results achieved within a specific case study within the European project GEOFIT. In particular, standard accelerometric measurements in and nearby a single-story reinforced concrete building are collected and analysed in the absence of drilling (pre-drilling) and during drilling activities (drilling phase) to monitor the structure response to the external source of vibrations related to the excavations phase. The target is to outline automatic guidelines toward installations preventing from any sort of structural damage.

• Journal of applied mathematics & informatics
• /
• v.40 no.5_6
• /
• pp.959-977
• /
• 2022

The topological indices are numerical parameters which determined the biological, physical and chemical properties based on the structure of the chemical compounds. One of the recently topological indices is the uphill Zagreb indices. In this paper, the formulae of some uphill Zagreb indices for a few graph operations of some graphs have been derived. Furthermore, the precise formulae of those indices for the honeycomb network have been found along with their graphical profiles.

• Progress in Superconductivity and Cryogenics
• /
• v.24 no.4
• /
• pp.11-15
• /
• 2022

We conducted numerical calculations to obtain the critical current as a function of the magnetic flux through the topologically trivial and non-trivial superconducting quantum interference devices (SQUIDs), with varying the capacitive and inductive couplings of Josephson junctions (JJs). Our calculation results indicate that a nontrivial SQUID is almost indistinguishable from trivial SQUID, considering the effective capacitance coupling. When the SQUID contains 2π- and 4π-periodic supercurrents, the periodicity of the current-flux relation can be distinguished from the purely trivial or nontrivial SQUID cases, and its difference is sensitive to the relative ratio between the topologically trivial and nontrivial supercurrents. We believe that our calculation results would provide a practical guide to quantitatively measure the portion of the topologically nontrivial supercurrents in experiments.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.357-366
• /
• 2022

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

• Archives of Plastic Surgery
• /
• v.49 no.6
• /
• pp.785-786
• /
• 2022

The anterolateral thigh (ALT) flap has been extensively discussed in the literature as it allows for a wide variety and depth of tissues for complex wound coverage. Thanks to many cadaveric and angiographic studies of the subdermal plexus, it is to date ascertained that tailoring ALT thickness can be safely performed without compromising flap outcomes or causing additional morbidity. Recently, the authors applied and described a simpler, safer, and less time-consuming superthin ALT perforator (ALTP) free flap harvesting technique. The aim of this article is to show the versatility of the adipofascial flap harvested around the chosen perforators, which allowed us to safely expand the usage of ALTP superthin flaps.