Search results for: statistical features

Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

Procedia PDF Downloads 211

Authors: Syeda Mainaaz Unnisa, Deepa Suresh

Abstract:

Due to the increase in usage of public domain channels, such as the internet, and communication technology, there is a concern about the protection of intellectual property and security threats. This interest has led to growth in researching and implementing techniques for information hiding. Steganography is the art and science of hiding information in a private manner such that its existence cannot be recognized. Communication using steganographic techniques makes not only the secret message but also the presence of hidden communication, invisible. Steganalysis is the art of detecting the presence of this hidden communication. Parallel to steganography, steganalysis is also gaining prominence, since the detection of hidden messages can prevent catastrophic security incidents from occurring. Steganalysis can also be incredibly helpful in identifying and revealing holes with the current steganographic techniques, which makes them vulnerable to attacks. Through the formulation of new effective steganalysis methods, further research to improve the resistance of tested steganography techniques can be developed. Feature-based steganalysis method for JPEG images calculates the features of an image using the L1 norm of the difference between a stego image and the calibrated version of the image. This calibration can help retrieve some of the parameters of the cover image, revealing the variations between the cover and stego image and enabling a more accurate detection. Applying this method to various steganographic schemes, experimental results were compared and evaluated to derive conclusions and principles for more protected JPEG steganography.

Keywords: cover image, feature-based steganalysis, information hiding, steganalysis, steganography

Procedia PDF Downloads 217

Authors: Mohammed G. Alotaibi, Sameer Albahkaly, Salwa M. Bahkali, Abdullah M. Alghamdi, Raseel S. Alswidan, Maha Bin Shafi, Sarah Almaiman

Abstract:

Introduction: Rhinitis is common in Saudi Arabia. Therefore, our study was designed to evaluate the prevalence, triggering factors, severity and progression of rhinitis during pregnancy. Methods: Prospective cross-sectional study was conducted in eight governmental and private medical centers in Riyadh, Saudi Arabia, during June and July 2014. Validated Arabic language self-administered questionnaire was used. Sample size of 260 Saudi pregnant women was calculated by Raosoft sample size calculator. Random sampling was achieved by choosing one and skipping every five patients in the clinic list. Data were coded and entered manually into spreadsheets then transferred to SPSS statistical package version 16.0 for Windows. Consent, Privacy and confidentiality of information were assured. Results: Pregnancy rhinitis was reported 31.2% (CI 25.6 - 37.2%). Symptoms arising in first trimester appeared in 79.2% of PR cases and mostly worsen. The most prevalent symptoms were nasal pruritis (67.5%), followed by sneezing (57.1%), congestion (50.6%), and post nasal drip (46.7%). The major triggering factor was dust (71.4%), followed by Tobacco/Shisha smoke (57.6%) and perfume(47%). Preexisting allergic diseases were markedly associated with developing pregnancy rhinitis. Conclusion: Rhinitis during pregnancy manifested in one third of Saudi pregnant ladies. Nasal pruritus was the most common symptom and dust was the widespread triggering factor.

Keywords: allergy, pregnancy, Rhinitis, sneezing

Procedia PDF Downloads 256

Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

Abstract:

Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

Procedia PDF Downloads 279

Authors: Pinyada Santisarun, Yaowaret Tharawoot, Songyut Akkakoson

Abstract:

This paper reports on a literature review sub-study of a larger research project which has been designed to identify the rhetorical organization of a travel writing genre, together with the use of lexical choices, syntactical structures, and graphological features, based on a randomly-selected corpus of Thailand travel listicles. Conducted as a library-based overview, this study aims to specify theoretical and practical elements for the said larger study. The materials for the review have been retrieved from various Internet sources, covering both public search engines and library databases. Generally, the article focuses on answering questions about the ‘what’ and the ‘how’ of such background elements widely discussed in the literature as the meaning of listicles, how the travel listicles’ patterns and regularities can be categorized to form a new genre, the effect of computer-mediated communication on the travel world, the travel language, and the current situation concerning the importance of travel listicles. The theoretical and practical data derived from this study provide valuable insights into the way in which the genre analysis and lexico-syntactical examination of Thailand travel listicles in the present authors’ larger research project can be properly conducted. The data gained can be added to the expanding body of knowledge in the field of the ESP genre.

Keywords: computer-mediated communication, digital writing, genre-based analysis, online travel writing, tourism language

Procedia PDF Downloads 148

Authors: M. Baldini, H. K. Jacobsen, M. Jaccard

Abstract:

In light of the international efforts to comply with the Paris agreement and emission targets for future energy systems, Denmark and Canada are among the front-runner countries dealing with climate change. The experiences in the energy sector have seen both countries coping with trade-offs between investments in renewable energy technologies and energy efficiency, thus tackling the climate issue from the supply and demand side respectively. On the demand side, the industrial sector is going through a remarkable transformation, with implementation of energy efficiency measures, change of input fuel for end-use processes and forecasted electrification as main features under the spotlight. By looking at Canada and Denmark's experiences as pathfinders on the demand and supply approach to climate change, it is possible to obtain valuable experience that may be applied to other countries aiming at the same goal. This paper presents a comparative study on industrial energy efficiency between Canada and Denmark. The study focuses on technologies and system options, policy design and implementation and modelling methodologies when implementing industrial energy savings in optimization models in comparison to simulation models. The study identifies gaps and junctures in the approach towards climate change actions and, learning from each other, lessen the differences to further foster the adoption of energy efficiency measurements in the industrial sector, aiming at reducing energy consumption and, consequently, CO₂ emissions.

Keywords: industrial energy efficiency, comparative study, CO₂ reduction, energy system modelling

Procedia PDF Downloads 175

Authors: Maria Kazantzaki, Evangelos Tsakalos, Eleni Filippaki, Yannis Bassiakos

Abstract:

Mediterranean areas are characterized by intense seismic and volcanic activity as well as eustatic changes, the result of which is the creation of particularly vulnerable coastal zones. The most vulnerable are low-lying coastal areas, the geomorphological evolution of which are highly affected by natural processes and anthropogenic interventions. Therefore, assessing changes that take place along coastal zones is of great importance in order to enable the development of integrated coastal management plans. A characteristic case is the gulf of Mirabello in N.E Crete, where intense coastal erosion, in combination with the tectonic subsidence of the area, threatens a large part of the coastal zone, resulting in direct socio-economic impacts. The present study assesses the temporal geomorphological changes that have taken place in the coastal zone of Mirabello gulf to provide a clear frame of the coastal zone evolution over time and performs a vulnerability assessment based on the coastal vulnerability index (CVI) methodology by Thieler and Hammar-Klose, considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates and mean significant wave height as well as mean tide range in the area. In light of this, an impact assessment, based on three different sea level rise scenarios, is also performed and presented.

Keywords: coastal vulnerability index, coastal erosion, GIS, sea level rise

Procedia PDF Downloads 176

Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

Procedia PDF Downloads 191

Authors: Sourour Chaabane, Davide Clematis, Marco Panizza

Abstract:

This study investigates the oxidation of Erythrosine B (EB) food dye by a homogeneous electro-Fenton process using iron (II) sulfate heptahydrate as a catalyst, carbon felt as cathode, and Ti/RuO2. The treated synthetic wastewater contains 100 mg L⁻¹ of EB and has a pH = 3. The effects of three independent variables have been considered for process optimization, such as applied current intensity (0.1 – 0.5 A), iron concentration (1 – 10 mM), and stirring rate (100 – 1000 rpm). Their interactions were investigated considering response surface methodology (RSM) based on Doehlert design as optimization method. EB removal efficiency and energy consumption were considered model responses after 30 minutes of electrolysis. Analysis of variance (ANOVA) revealed that the quadratic model was adequately fitted to the experimental data with R² (0.9819), adj-R² (0.9276) and low Fisher probability (< 0.0181) for EB removal model, and R² (0.9968), adj-R² (0.9872) and low Fisher probability (< 0.0014) relative to the energy consumption model reflected a robust statistical significance. The energy consumption model significantly depends on current density, as expected. The foregoing results obtained by RSM led to the following optimal conditions for EB degradation: current intensity of 0.2 A, iron concentration of 9.397 mM, and stirring rate of 500 rpm, which gave a maximum decolorization rate of 98.15 % with a minimum energy consumption of 0.74 kWh m⁻³ at 30 min of electrolysis.

Keywords: electrofenton, erythrosineb, dye, response serface methdology, carbon felt

Procedia PDF Downloads 77

Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

Abstract:

Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

Procedia PDF Downloads 75

Authors: Ali M. Subyani

Abstract:

The increase in the greenhouse gas emission has had a severe impact on global climate change and is bound to affect the weather patterns worldwide. This climate change impacts are among the future significant effects on any society. Rainfall levels are drastically increasing with flash floods in some places and long periods of droughts in others, especially in arid regions. These extreme events are causes of interactions concerning environmental, socio-economic and cultural life and their implementation. This paper presents the detailed features of dry and wet spell durations and rainfall intensity series available (1971-2012) on daily basis for the Jeddah area, Western, Saudi Arabia. It also presents significant articles for combating the climate change impacts on this area. Results show trend changes in dry and wet spell durations and rainfall amount on daily, monthly and annual time series. Three rain seasons were proposed in this investigation: high rain, low rain, and dry seasons. It shows that the overall average dry spell durations is about 80 continuous days while the average wet spell durations is 1.39 days with an average rainfall intensity of 8.2 mm/day. Annual and seasonal autorun analyses confirm that the rainy seasons are tending to have more intense rainfall while the seasons are becoming drier. This study would help decision makers in future for water resources management and flood risk analysis.

Keywords: climate change, daily rainfall, dry and wet spill, Jeddah, Saudi Arabia

Procedia PDF Downloads 340

Authors: S. Yakubu, E. A. Isah

Abstract:

One of the objectives of the school discipline policy is to instill discipline among students. However, despite the availability of this policy in various secondary schools in Nigeria, there seem to be numerous cases of indiscipline among students, which has become a source of concern to all stakeholders in the education sector. In an attempt to proffer possible solutions to this unending challenge, the study investigated the influence of knowledge and attitude on compliance of secondary school students towards school discipline policy in Ibadan North Local Government Area of Oyo State, Nigeria. The descriptive survey research design was employed to collect the requisite data. The multi-stage sampling procedure was adopted to select 570 respondents as the sample for the study. The data collected were analyzed using statistical measures of Mean, Standard deviation and Pearson Product Moment Correlation. The findings of the study showed that knowledge and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State were significantly related (r =0.330, p<0.05). The study also revealed a significant relationship between attitude and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State (r = 0.593, p<0.05). Based on the findings, it was recommended that school rules and regulations should be emphasized and given more awareness for easy compliance. Also, students should be encouraged to portray a positive attitude towards their respective rules and regulations.

Keywords: knowledge, attitude, compliance, school discipline policy

Procedia PDF Downloads 190

Authors: Reza Mohammadzadeh

Abstract:

The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

Procedia PDF Downloads 279

Authors: Feng Yin

Abstract:

Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

Procedia PDF Downloads 282

Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

Abstract:

In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

Procedia PDF Downloads 306

Authors: Abrar Noorain, Zeinab Amara, Sulaf Abdelaziz

Abstract:

Background: Diabetic foot disease imposes a financial burden on diabetic patients and healthcare services. In Sudan, diabetic foot ulcer prevalence reached 18.1%. This study aims to assess the knowledge, attitudes, and practices and the correlation between the level of foot care knowledge and self-care practices among diabetic patients in Sudan. Methodology: In a cross-sectional study involving 262 patients with type 1 and type 2 diabetes attending diabetic clinics in three primary care centers in Khartoum, Sudan, during September to November 2022, information regarding participants sociodemographic status, foot care knowledge, attitudes, and practices was gathered using a validated, structured questionnaire in a face-to-face interview method. These data were analyzed using the statistical package for the social sciences (SPSS) 22. Results: The patients’ mean age was 54.9 years, with a female predominance (56%). Of the participants, 37% had diabetes mellitus for over ten years. On the topic of foot care, 35.5% of patients showed good knowledge, and 76% were aware of the risk of reduced foot sensation. In relation to nail care, only 19% knew how to cut nails correctly. Conclusion: Knowledge, attitudes, and practices about diabetic foot care are substandard. There is a positive correlation between foot care knowledge and self-care practices. Hence, educating diabetic patients with foot care knowledge through an awareness program and the characteristics of diabetic shoes may improve self-care practices.

Keywords: DM, DFD, DFU, PHC, SPSS

Procedia PDF Downloads 77

Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Luca Garbarino, Urbano Tancredi, Domenico Accardo, Michele Grassi, Giancarmine Fasano, Anna Elena Tirri

Abstract:

The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.

Keywords: ADS-B, avionics, NAVAIDs, real-time simulation, TCAS, UAS ground control station

Procedia PDF Downloads 232

Authors: Taimur Khan, Zakirullah, Muhammad Shahab

Abstract:

The SARS-CoV-2 variant BA.2.86 (Omicron) has emerged with unique mutations that may increase its transmission and infectivity. This study investigates how these mutations alter the Omicron receptor-binding domain's interaction network and dynamic properties (RBD) compared to the wild-type virus, focusing on its binding affinity to the human ACE2 (hACE2) receptor. Protein-protein docking and all-atom molecular dynamics simulations were used to analyze structural and dynamic differences. Despite the structural similarity to the wild-type virus, the Omicron variant exhibits a distinct interaction network involving new residues that enhance its binding capacity. The dynamic analysis reveals increased flexibility in the RBD, particularly in loop regions crucial for hACE2 interaction. Mutations significantly alter the secondary structure, leading to greater flexibility and conformational adaptability compared to the wild type. Binding free energy calculations confirm that the Omicron RBD has a higher binding affinity (-70.47 kcal/mol) to hACE2 than the wild-type RBD (-61.38 kcal/mol). These results suggest that the altered interaction network and enhanced dynamics of the Omicron variant contribute to its increased infectivity, providing insights for the development of targeted therapeutics and vaccines.

Keywords: SARS-CoV-2, molecular dynamic simulation, receptor binding domain, vaccine

Procedia PDF Downloads 30

Authors: Rihab Hamdi, Amel Hadri Hamida, Ouafae Bennis, Sakina Zerouali

Abstract:

This paper features a performance analysis and robustness assessment of a digitally controlled DC-DC three-cell buck converter associated in parallel, operating in continuous conduction mode (CCM), facing feeding parameters variation and loads disturbance. The control strategy relies on the continuous-time with an averaged modeling technique for high-frequency switching converter. The methodology is to modulate the complete design procedure, in regard to the existence of an instantaneous current operating point for designing the digital closed-loop, to the same continuous-time domain. Moreover, the adopted approach is to include a digital voltage control (DVC) technique, taking an account for digital control delays and sampling effects, which aims at improving efficiency and dynamic response and preventing generally undesired phenomena. The results obtained under load change, input change, and reference change clearly demonstrates an excellent dynamic response of the proposed technique, also as provide stability in any operating conditions, the effectiveness is fast with a smooth tracking of the specified output voltage. Simulations studies in MATLAB/Simulink environment are performed to verify the concept.

Keywords: continuous conduction mode, digital control, parallel multi-cells converter, performance analysis, power electronics

Procedia PDF Downloads 153

Authors: Di Wei, Xing Hu, Yangjun Chen, Baofeng Li, Hong Chen

Abstract:

To achieve the research purpose of guiding the spatial morphology design of blocks through the indicators to obtain a good wind environment, it is necessary to find the most suitable type and value range of each urban spatial morphology indicator. At present, most of the relevant researches is based on the numerical simulation of the ideal block shape and rarely proposes the results based on the complex actual block types. Therefore, this paper firstly attempted to make theoretical speculation on the main factors influencing indicators' effectiveness by analyzing the physical significance and formulating the principle of each indicator. Then it was verified by the field wind environment measurement and statistical analysis, indicating that Porosity(P₀) can be used as an important indicator to guide the design of block wind environment in the case of deep street canyons, while Frontal Area Density (λF) can be used as a supplement in the case of shallow street canyons with no height difference. Finally, computational fluid dynamics (CFD) was used to quantify the impact of block height difference and street canyons depth on λF and P₀, finding the suitable type and value range of λF and P₀. This paper would provide a feasible wind environment index system for urban designers.

Keywords: urban spatial morphology indicator, urban microclimate, computational fluid dynamics, block ventilation, correlation analysis

Procedia PDF Downloads 141

Authors: James Bassey Ejue, Dorn Cklaimz Enamhe, Helen Francis Ejue

Abstract:

The study examined the influence of personal variables such as sex, type of school, and parental socio-economic status on secondary school students’ perception of school security. To guide the study, three null hypotheses were formulated. The research design adopted was the survey design, and a 20-item instrument was constructed and validated by the researchers through a test-retest procedure. The sample size for the study comprised 2,198 students made up of male and female students selected through a stratified random sampling technique. This was drawn from a study population of 21,988, made up of 12,635 students and 9353 students from public and private secondary schools, respectively. Data were analyzed using an independent t-test statistical tool. The findings showed that female students were more fearful in their perception of school security; the students in private schools perceived school to be more insecure than those in public schools; and the students from high parental socio-economic status are more associated with the perception of school as insecure than the ones from low parental socio-economic status. Based on these findings, it was recommended that, among others, more reassuring measures be put in place to check school security for females, for those in private schools, and for those from high parental socio-economic status. School counsellors should also be guided accordingly in designing intervention strategies.

Keywords: personal variables, students, perception, school security

Procedia PDF Downloads 81

Authors: Xingxing Peng

Abstract:

With the development of society, there are more and more online communication scenarios such as teleconference and online education. In the process of conference communication, the quality of voice communication is a very important part, and noise may cause the communication effect of participants to be greatly reduced. Therefore, voice noise reduction has an important impact on scenarios such as voice calls. This research focuses on the key technologies of the sound transmission process. The purpose is to maintain the audio quality to the maximum so that the listener can hear clearer and smoother sound. Firstly, to solve the problem that the traditional speech enhancement algorithm is not ideal when dealing with non-stationary noise, an adaptive speech noise reduction algorithm is studied in this paper. Traditional noise estimation methods are mainly used to deal with stationary noise. In this chapter, we study the spectral characteristics of different noise types, especially the characteristics of non-stationary Burst noise, and design a noise estimator module to deal with non-stationary noise. Noise features are extracted from non-speech segments, and the noise estimation module is adjusted in real time according to different noise characteristics. This adaptive algorithm can enhance speech according to different noise characteristics, improve the performance of traditional algorithms to deal with non-stationary noise, so as to achieve better enhancement effect. The experimental results show that the algorithm proposed in this chapter is effective and can better adapt to different types of noise, so as to obtain better speech enhancement effect.

Keywords: speech noise reduction, speech enhancement, self-adaptation, Wiener filter algorithm

Procedia PDF Downloads 62

Authors: Adrian Ionut Nicoara, Denisa Ionela Ene, Alina Maria Holban, Cristina Busuioc

Abstract:

At present, the development of materials with biomedical applications is a domain of interest that will produce a full series of benefits in engineering and medicine. In this sense, it is required to use a natural material, and this paper is focused on the development of a composite material based on bacterial cellulose – hydroxyapatite and silver nanoparticles with applications in hard tissue. Bacterial cellulose own features like biocompatibility, non-toxicity character and flexibility. Moreover, the bacterial cellulose can be conjugated with different forms of active silver to possess antimicrobial activity. Hydroxyapatite is well known that can mimic at a significant level the activity of the initial bone. The material was synthesized by using an ultrasound probe and finally characterized by several methods. Thereby, the morphological properties were analyzed by using Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Because the synthesized material has medical application in restore the tissue and to fight against microbial invasion, the samples were tested from the biological point of view by evaluating the biodegradability in phosphate-buffered saline (PBS) and simulated body fluid (SBF) and moreover the antimicrobial effect was performed on Gram-positive bacterium Staphylococcus aureus, Gram-negative bacterium Escherichia coli, and fungi Candida albicans. The results reveal that the obtained material has specific characteristics for bone regeneration.

Keywords: bacterial cellulose, biomaterials, hydroxyapatite, scaffolds materials

Procedia PDF Downloads 137

Authors: A. E. Kobryn

Abstract:

We present both descriptive and predictive modeling of structural properties of blends of PCBM or organic-inorganic hybrid perovskites of the type CH3NH3PbX3 (X=Cl, Br, I) with P3HT, P3BT or squaraine SQ2 dye sensitizer, including adsorption on TiO2 clusters having rutile (110) surface. In our study, we use a methodology that allows computing the microscopic structure of blends on the nanometer scale and getting insight on miscibility of its components at various thermodynamic conditions. The methodology is based on the integral equation theory of molecular liquids in the reference interaction site representation/model (RISM) and uses the universal force field. Input parameters for RISM, such as optimized molecular geometries and charge distribution of interaction sites, are derived with the use of the density functional theory methods. To compare the diffusivity of the PCBM in binary blends with P3HT and P3BT, respectively, the study is complemented with MD simulation. A very good agreement with experiment and the reports of alternative modeling or simulation is observed for PCBM in P3HT system. The performance of P3BT with perovskites, however, seems as expected. The calculated nanoscale morphologies of blends of P3HT, P3BT or SQ2 with perovskites, including adsorption on TiO2, are all new and serve as an instrument in rational design of organic/hybrid photovoltaics. They are used in collaboration with experts who actually make prototypes or devices for practical applications.

Keywords: multiscale theory and modeling, nanoscale morphology, organic-inorganic halide perovskites, three dimensional distribution

Procedia PDF Downloads 157

Authors: Mebarek Boukelkoul, Abdelhalim Haroun

Abstract:

By means of the first principle calculation, we have investigated the structural, magnetic and magneto-optical properties of the ultra-thin films of Fen/Cu(001) with (n=1, 2, 3). We adopted a relativistic approach using DFT theorem with local spin density approximation (LSDA). The electronic structure is performed within the framework of the Spin-Polarized Relativistic (SPR) Linear Muffin-Tin Orbitals (LMTO) with the Atomic Sphere Approximation (ASA) method. During the variational principle, the crystal wave function is expressed as a linear combination of the Bloch sums of the so-called relativistic muffin-tin orbitals centered on the atomic sites. The crystalline structure is calculated after an atomic relaxation process using the optimization of the total energy with respect to the atomic interplane distance. A body-centered tetragonal (BCT) pseudomorphic crystalline structure with a tetragonality ratio c/a larger than unity is found. The magnetic behaviour is characterized by an enhanced magnetic moment and a ferromagnetic interplane coupling. The polar magneto-optical Kerr effect spectra are given over a photon energy range extended to 15eV and the microscopic origin of the most interesting features are interpreted by interband transitions. Unlike thin layers, the anisotropy in the ultra-thin films is characterized by a perpendicular magnetization which is perpendicular to the film plane.

Keywords: ultrathin films, magnetism, magneto-optics, pseudomorphic structure

Procedia PDF Downloads 339

Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

Abstract:

Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: pollution, printing industry, simple linear regression analysis, wastewater

Procedia PDF Downloads 236

Authors: Jamaluddin Abd Rashid, Aris Abdul Rahman

Abstract:

Mobile phones have become the most popular way to communicate with other individuals and it has created an unspoken social dependency. Making phone calls, instant messaging, playing online games and accessing the Internet are among the features added to a mobile phone, attracting teenagers to spend more hours fixated on their gadgets. As such, this study attempted to examine the frequency of time spent on mobile phones and how this influenced academic performance. A quantitative methodology was applied in this study, where face to face survey through the distribution of questionnaires was facilitated onto a group of 200 secondary school students from the Shah Alam community in Selangor,Malaysia. Both genders, male and females were assessed equally to find out if there exists a correlation between genders when measuring higher or lower frequency of attachment to mobile phones. It can also be seen that 100% correspondents have a mobile phone in their possession. The adolescents uses mobile phones daily, which shows students being somewhat addicted, as they tend to feel that it is necessary to use a mobile phone. The main findings of this research found out that, students that are mobile phone addictive received a lower grade in schools. Mobile phone addiction does affect academic performance negatively. As this study discusses the modern-day phenomenon, it is hoped that the findings and discussion could add to present literary works and help future researchers understand the relationship between mobile phone addiction and academic performance.

Keywords: academic performance, mobile phone addiction, social media, student

Procedia PDF Downloads 351

Authors: J. R. Ashrapov, G. A. Alihodzhaeva, D. E. Abdullaev, N. R. Kadirbekov

Abstract:

Diagnosis of brain tumors is one of the challenges, as several central nervous system diseases run the same symptoms. Modern diagnostic techniques such as CT, MRI helps to significantly improve the surgery in the operating period, after surgery, after allowing time to identify postoperative complications in neurosurgery. Purpose: To study the MRI characteristics and localization of brain tumors in children and to detect the postoperative complications in the postoperative period. Materials and methods: A retrospective study of treatment of 62 children with brain tumors in age from 2 to 5 years was performed. Results of the review: MRI scan of the brain of the 62 patients 52 (83.8%) case revealed a brain tumor. Distribution on MRI of brain tumors found in 15 (24.1%) - glioblastomas, 21 (33.8%) - astrocytomas, 7 (11.2%) - medulloblastomas, 9 (14.5%) - a tumor origin (craniopharyngiomas, chordoma of the skull base). MRI revealed the following characteristic features: an additional sign of the heterogeneous MRI signal of hyper and hypointensive T1 and T2 modes with a different perifocal swelling degree with involvement in the process of brain vessels. The main objectives of postoperative MRI study are the identification of early or late postoperative complications, evaluation of radical surgery, the identification of the extended-growing tumor that (in terms of 3-4 weeks). MRI performed in the following cases: 1. Suspicion of a hematoma (3 days or more) 2. Suspicion continued tumor growth (in terms of 3-4 weeks). Conclusions: Magnetic resonance tomography is a highly informative method of diagnostics of brain tumors in children. MRI also helps to determine the effectiveness and tactics of treatment and the follow up in the postoperative period.

Keywords: brain tumors, children, MRI, treatment

Procedia PDF Downloads 148

Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

Abstract:

Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

Procedia PDF Downloads 174

Authors: Guo Jinhong

Abstract:

The purpose of this study is to explore the association between board member functions and information disclosure levels. Based on the literature variables, such as the characteristics of the board of directors in the past, a single comprehensive indicator is established as a substitute variable for board functions, and the information disclosure evaluation results published by the Securities and Foundation are used to measure the information disclosure level of the company. This study focuses on companies listed on the Taiwan Stock Exchange from 2006 to 2010 and uses descriptive statistical analysis, univariate analysis, correlation analysis and ordered normal probability (Ordered Probit) regression for empirical analysis. The empirical results show that there is a significant positive correlation between the function of board members and the level of information disclosure. This study also conducts a sensitivity test and draws similar conclusions, showing that boards with better board member functions have higher levels of information disclosure. In addition, this study also found that higher board independence, lower director shareholding pledge ratio, higher director shareholding ratio, and directors with rich professional knowledge and practical experience can help improve the level of information disclosure. The empirical results of this study provide strong support for the "relative regulations to improve the level of information disclosure" formulated by the competent authorities in recent years.

Keywords: function of board members, information disclosure, securities, foundation

Procedia PDF Downloads 102