Titanium dioxide (TiO2) nanotubes have gained particular interest as a material for gas sensors because of their vertical arrays, prepared by the anodization procedure. The presence of several oxygen vacancies in these nanotubes facilitates gas diffusion and provides additional active sites. This study examined the impact of voltages on the process of depositing iron nanoparticles onto arrays of TiO2 nanotubes (TNTs) for use as a gas sensor. The TNTs are manufactured using a straightforward and economical electrochemical anodization technique, specifically for gas sensor applications. By varying the deposition voltage (2-6 volts), ordered Fe-TNTs were efficiently manufactured using a simple two-step electrochemical process. It utilized energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and field-emission scanning electron microscopy (FESEM) to study morphology, structure, and composition. Furthermore, gas sensor testing was implemented to examine the gas sensor’s response. An increase in the Fe doping voltage with TNTs altered the structure of the nanotubes, particularly at the highest voltages, according to XRD analysis. The best sensor for Fe-TNTs was made by doping Fe with TiO2 nanotubes at a doping voltage of 3 volts, depending on how well the gas sensitizers worked. The study demonstrated that using iron can increase TiO2's efficiency as a gas sensor.
The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l
... Show MoreThe current study was carried out at the Fields belongs of Horticulture Department, Collage of Agricultural Engineering Science, University of Baghdad, Al-Jadiriyah for the spring season 2016 -2017 to study the effect for inoculation mycorrhizae and folair application with bio stimulators and their interaction in the growth characters of (local okra ptera). A factorial experiment (2 in randomized complete block design (RCBD), the experiment included (12) treatment Distributed in three replicates. The three factors used in this experiment included . The inoculation with control (C) Mycorrhizae ( M ) , Biozyme (B ) ( B1 2cm3.L-1), ( B2 4cm1-.L-1) , Phosphalas (P) (P 2cm3.L-1), ( M + B1), ( M + B2), (P +
... Show MoreResearch aimed to explore the Application Effect of the Conflict Management Strategies by the managements to solve conflict between and inside the conflicted parties within (IGEC) to increase the productivity of the workers. To collect data, 110 questioners had been distributed among managers and heads of departments of all managerial levels, 102 answered questioners regained, 5 of them were disqualify for statistical analytic, only 97 were taking in consideration for statistical analysis presenting 93% of the retained number.
SPSS Program supported with a group of statistical tools, had been used for analysis purposes such as Kronbach Alpha test to assure the validity & stability of the t
... Show MoreThe aim of this study is to evaluate the implementation of ICT applications in public service organizations, which is responsible for the implementation of public policy. The study examined the success of ICT in achieving its goals by meeting the main needs of the community members which is the first requirement in the success of sustainable development plans before determine the capabilities of ICT. The main pillar of success in the implementation of ICT systems is the key to improving the efficiency of the organization's performance. This is a reflection of the effectiveness and quality of the services provided to its beneficiaries. The study concluded that the current level of capabilities of individuals working in public organizations i
... Show MoreVirtual reality, VR, offers many benefits to technical education, including the delivery of information through multiple active channels, the addressing of different learning styles, and experiential-based learning. This paper presents work performed by the authors to apply VR to engineering education, in three broad project areas: virtual robotic learning, virtual mechatronics laboratory, and a virtual manufacturing platform. The first area provides guided exploration of domains otherwise inaccessible, such as the robotic cell components, robotic kinematics and work envelope. The second promotes mechatronics learning and guidance for new mechatronics engineers when dealing with robots in a safe and interactive manner. And the thir
... Show MoreThe aim of the current research is to identify the level of organizational culture among the headmasters and teachers of intermediate and secondary schools in Arar city. It also aims to identify the effect of job variables, qualifications, educational stage, and years of experience on the level of organizational culture and its domains. The research sample consisted of 62 participants divided into 7 headmasters and 55 teachers. The researcher used the questionnaire of the organizational culture. The researcher used also statistical methods such as mean, standard deviation, t-test, and One way ANOVA. The results revealed that the level of organizational culture and its four domains were high, and there was no effect of the variables (teac
... Show MoreThe use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
... Show MoreThis research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen
The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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