The Raman gain coefficient, the attenuations at signal and pump wavelengths and the refractive indices of both core and cladding of silica doped Germania optical fiber are functions of the Germania ratio, temperature ...
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Human resource is one of the most valuable assets in an organization. They are bounded to develop the unique and dynamic aspects that strengthen their competitive advantage to persist in an always changing market envi...
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Brain computer interface (BCI)-based virtual environment control has found broad applications in solving and pursuing factual healthcare issues concerning efficiency, safety, and costs. In this technical paper, an unm...
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ISBN:
(数字)9781665468190
ISBN:
(纸本)9781665468206
Brain computer interface (BCI)-based virtual environment control has found broad applications in solving and pursuing factual healthcare issues concerning efficiency, safety, and costs. In this technical paper, an unmanned ground vehicle (UGV) robot with a simulator-equipped BCI system was utilized. The Gazebo simulator was employed to develop a simulated setting. The software CitySim World allowed rendering the simulated milieu more down-to-earth. A non-invasive electroencephalogram (EEG)-based BCI was used to follow the brain signals and extract the P300 component, a kind of simultaneous BCI controlling procedure for safe, fast, and inexpensive implementation. This UGV control system using human brain activity can be beneficial for the real UGV platform control. It enables the discovery of the probable errors in the physical implementation. All the steps implementing our BCI system were appropriately provided (data acquisition system, user interface design, BCI data architecture, ROS/ robot Jackal, and implementation and tests). Furthermore, the project implementation and some solutions to possible issues were posed. The project outcomes were assessed by employing BCI in a simulation; before implementing real-time, to determine errors and resolve the validity of the project scope.
Tomato is a one of the most popular produced and extensively consumed vegetables in the world. Typical agricultural systems make extensive use of human labor which is more costly and less effective. This research expl...
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The IPv6 over Low-powered Wireless Personal Area Network (6LoWPAN) protocol was introduced to allow the transmission of Internet Protocol version 6 (IPv6) packets using the smaller-size frames of the IEEE 802.15.4 sta...
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This paper describes the organization and results of several MOOCs delivered about technical topics (i.e., digital electronics, VHDL design on FPGAs, open education and OERs repositories and the use of STEAM technolog...
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This paper describes the organization and results of several MOOCs delivered about technical topics (i.e., digital electronics, VHDL design on FPGAs, open education and OERs repositories and the use of STEAM technologies to encourage diversity and inclusion), where online laboratories have been used in some of them. An analysis of the enrollment, students participating on tasks or quizzes, drop-out rate and certifications requests have been done.
This paper addresses the influence of nanoparticles (NPs) on the dielectric properties of polyurethane. In this research, we only investigated the effect of Al2O3, MgO and ZnO NPs for concentrations up to 2% wt and in...
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Distinguishing causal connections from correlations is important in many scenarios. However, the presence of unobserved variables, such as the latent confounder, can introduce bias in conditional indep.ndence testing ...
Distinguishing causal connections from correlations is important in many scenarios. However, the presence of unobserved variables, such as the latent confounder, can introduce bias in conditional indep.ndence testing commonly employed in constraint-based causal discovery for identifying causal relations. To address this issue, existing methods introduced proxy variables to adjust for the bias caused by unobserveness. However, these methods were either limited to categorical variables or relied on strong parametric assumptions for identification. In this paper, we propose a novel hypothesis-testing procedure that can effectively examine the existence of the causal relationship over continuous variables, without any parametric constraint. Our procedure is based on discretization, which under completeness conditions, is able to asymptotically establish a linear equation whose coefficient vector is identifiable under the causal null hypothesis. Based on this, we introduce our test statistic and demonstrate its asymptotic level and power. We validate the effectiveness of our procedure using both synthetic and real-world data. Code is publicly available at https://***/lmz123321/proxy_causal_discovery.
The internet became a common communication platform for many people. However, information transmission is not secure, and there is a high probability of copying and altering the information easily. In the public netwo...
ISBN:
(纸本)9798400709036
The internet became a common communication platform for many people. However, information transmission is not secure, and there is a high probability of copying and altering the information easily. In the public network, transmitting sensitive or private information needs some kind of protection. Unless a secure channel is utilized for the transmission. Hiding the information is one of the efficient techniques that provides a solution for transmitting confidential data over communication channels. These techniques should meet various application requirements such as high robustness against attacks, real-time, and high hiding capacity. Generally, information-hiding techniques suffer from many challenges. This paper provides an insight into these techniques, their applications, and challenges to fill the gap of missing such an overview.
Phishing is a cyber threat where attackers create deceptive websites or emails to exploit individuals for fraudulent purposes such as providing sensitive information like usernames, passwords, or financial details. He...
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ISBN:
(数字)9798350373363
ISBN:
(纸本)9798350373370
Phishing is a cyber threat where attackers create deceptive websites or emails to exploit individuals for fraudulent purposes such as providing sensitive information like usernames, passwords, or financial details. Hence, detecting phishing emails is of paramount importance to protect sensitive information, preventing financial losses, protecting against identity theft, and maintaining trust. This study employs machine learning techniques to classify and categorize websites that are used for phishing attacks. To achieve this, we proposed a classification model for the detection of phishing domains based on classification rules. These rules were formulated based on analyzing and distributing them into three classifiers: domain name features, search engine opinion (SEO) information of the domain, and security scans by security vendors. A total of eleven classification rules were formulated which were distributed as follows: six rules for the first classifier, four rules for the second classifier, and one rule for the third classifier. Each classifier feeds its results to the main classifier, which then evaluates the received results based on its rules. Domain names from 222 confirmed phishing URLs were used to test the suggested model. The model demonstrated exceptional performance, achieving an impressive accuracy rate of 99.1% during testing.
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