Search results for: Statistical Approaches

Authors: Kayijuka Idrissa

Abstract:

This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.

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Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

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Background: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, for which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. Objective: This article tried to optimize the layout of a troops’ cafeteria and to improve the overall efficiency of the dining process. Methods: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. Results: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interferences reduced as well, which verified corresponding simulation results. Conclusion: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: Troops’ cafeteria, layout optimization, dining efficiency, AnyLogic simulation, field experiment

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Authors: Natanya Meyer, Johann Landsberg

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Unemployment among the youth is a significant problem in South Africa. Large corporations and the public sector simply cannot create enough jobs. Too many youths in South Africa currently do not consider entrepreneurship as an option in order to become independent. Unlike the youth of the Netherlands, South African youth prefer to find employment in the public or private sector. The Netherlands has a much lower unemployment rate than South Africa and the Dutch are generally very entrepreneurial. From early on, entrepreneurship is considered a desirable career option in the Netherlands. The purpose of this study was to determine whether there is a difference in the perceptions of some Dutch and South African students in terms of unemployment and entrepreneurship. Questionnaires were distributed to students at the North West University's Vaal Triangle campus in Vanderbijlpark in Gauteng, South Africa and the Technical University of Delft in the Netherlands. A descriptive statistical analysis approach was followed and the means for the independent questions were calculated. The results demonstrate that the Dutch students are not as concerned about unemployment after completion of their studies as this is not as significant a problem as it is in South Africa. Both groups had positive responses towards the posed questions, but the South African group felt more strongly about the issues. Both groups of students felt that there was a need for more practical entrepreneurship training. The South African education system should focus on practical entrepreneurship training from a young age.

Keywords: Entrepreneurship development, entrepreneurship development programmes, entrepreneurship intention, Netherlands, South Africa, unemployment.

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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Development of a method to estimate gene functions is an important task in bioinformatics. One of the approaches for the annotation is the identification of the metabolic pathway that genes are involved in. Since gene expression data reflect various intracellular phenomena, those data are considered to be related with genes’ functions. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: Metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning.

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Authors: Mete Kazaz, Birol Gülnar

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Television news has gained a new dimension in terms of ideological approaches as a result of such factors as globalization, cross monopolization, presence of international companies etc. and certain strategies have been developed at the production, presentation and distribution stages of news. In this study, television news about a process called “settlement process” was investigated. In this framework, news about the settlement process on TV channels of TRT 1, ATV, FOX TV, NTV, HABERTÜRK, TRT HABER and STV was investigated using the content analysis method in terms of the strategies the ideology construction, attitude towards the party in power, attitude towards parties in opposition and attitude towards BDP (Peace and Democracy Part) and Imrali (the island where Abdullah Ocalan, head of PKK, is kept). First, the aforementioned TV channels were selected randomly from 3 groups in order to be able to reveal the representational capacity of commercial, news and public channels. The study covers 557 news items broadcast in the main news bulletins between the dates of 15 March 2013 and 15 March 2013. While there was a positive attitude towards the government in a sizable portion of the news about the settlement process (63.6%), the attitude of 25.3% of the news was impartial towards the government and 11.3% had a negative attitude. On the other hand, there was a negative attitude towards the Opposition in a considerable portion of the news about the settlement process (56.1%). The attitude of 35.9% of the news towards the Opposition was impartial whereas 8.0% had a positive attitude. While 34.9% of the news about the settlement process used the legitimization strategy from among the ideology construction strategies, 22.8% used the unification strategy, 15.7% the reification strategy, 15.6% fractional and 11% concealment/mystification strategy.

Keywords: Attitude, Ideological Framing, Television News.

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Authors: Mohammad Saber Eslamlou

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Morphology of Islamic cities has been extensively studied by researchers. In this regard, there exist much difference in method of analysis, classification, recognition, confrontation and comparative method of urban morphology. The present paper aims to examine the previous methods, approaches and insights and how Dr. Giulia Annalinda Neglia dealt with the analysis of morphology of Islamic cities. Neglia is assistant professor in University of Bari, Italy (UNIBA) who has published numerous papers and books on Islamic cities. We introduce the works in the field of morphology of Islamic cities and then, her thoughts, insights and research methodologies are presented and analyzed in critical perspective. This is a qualitative research on her written works, which have been classified in three major categories. The present paper focuses mainly on her works regarding morphology and physical shape of Islamic cities. The results of her works’ review suggest that she has used Moratoria typology in investigating morphology of Islamic cities. Moreover, overall structure of the cities under investigation is often described linear; however, she is against to define a single framework for the recognition of morphology in Islamic cities. She believes that fabric of each region in the city follows from the principles of a specific period or urban pattern, in particular, Hellenistic and Roman structures. Furthermore, she believes that it is impossible to understand the morphology of a city without taking into account the obvious and hidden developments associated with it, because form of building and their surrounding open spaces are written history of the city.

Keywords: City, Islamic city, morphology of city, Giulia Annalinda Neglia.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Fereydoon Sarmadian, Ali Keshavarzi

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Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.

Keywords: Artificial neural network, Field capacity, Permanentwilting point, Pedotransfer functions.

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Authors: Aaron A. R. Nwabude

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The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.

Keywords: VLE, Mathematical Concepts Acquisition, PilotStudy, SENs, KS4, Education, Teacher

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Authors: D. Geringswald, B. Hintze

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The miniaturization of circuits is advancing. During chip manufacturing, structures are filled for example by metal organic chemical vapor deposition (MOCVD). Since this process reaches its limits in case of very high aspect ratios, the use of alternatives such as the atomic layer deposition (ALD) is possible, requiring the extension of existing coating systems. However, it is an unsolved question to what extent MOCVD can achieve results similar as an ALD process. In this context, this work addresses the characterization of a metal organic vapor deposition of titanium nitride. Based on the current state of the art, the film properties coating thickness, sheet resistance, resistivity, stress and chemical composition are considered. The used setting parameters are temperature, plasma gas ratio, plasma power, plasma treatment time, deposition time, deposition pressure, number of cycles and TDMAT flow. The derived process instructions for unstructured wafers and inside a structure with high aspect ratio include lowering the process temperature and increasing the number of cycles, the deposition and the plasma treatment time as well as the plasma gas ratio of hydrogen to nitrogen (H₂:N₂). In contrast to the current process configuration, the deposited titanium nitride (TiN) layer is more uniform inside the entire test structure. Consequently, this paper provides approaches to employ the MOCVD for structures with increasing aspect ratios.

Keywords: ALD, high aspect ratio, PE-MOCVD, TiN.

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.

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Authors: Vladimir Korovkin, Albert Park, Evgeny Kaganer

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Digital divide, the gap in the access to the world of digital technologies and the socio-economic opportunities that they create is an important phenomenon of the XXI century. This gap may exist between countries, regions within a country or socio-demographic groups, creating the classes of “digital have and have nots”. While the 1st-level divide (the difference in opportunities to access the digital networks) was demonstrated to diminish with time, the issues of 2nd level divide (the difference in skills and usage of digital systems) and 3rd level divide (the difference in effects obtained from digital technology) may grow. The paper offers a systemic review of literature on the measurement of the digital divide, noting the certain conceptual stagnation due to the lack of effective instruments that would capture the complex nature of the phenomenon. As a result, many important concepts do not receive the empiric exploration they deserve. As a solution the paper suggests a composite Digital Life Index, that studies separately the digital supply and demand across seven independent dimensions providing for 14 subindices. The Index is based on Internet-borne data, a distinction from traditional research approaches that rely on official statistics or surveys. The application of the model to the study of the digital divide between Russian regions and between cities in China have brought promising results. The paper advances the existing methodological literature on the 2nd level digital divide and can also inform practical decision-making regarding the strategies of national and regional digital development.

Keywords: Digital transformation, second-level digital divide, composite index, digital policy.

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Authors: Arash Sharghi, Irina Dotu

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The developments in the Middle East region have activated the involvement of a numerous diverse state and non-state actors in the regional affairs. The goals, positions, ideologies, different, and even contrast policy behaviors had procured the spreading and continuity of crisis. Non-state actors varying from Islamic organizations to takfiri-terrorist movements on one hand and regional and trans- regional actors, from another side, seek to reach their interests in the power struggle. Here, a research worthy question comes on the agenda: taking into consideration actors’ contradictory interests and constraints what are the regional peace and stability perspectives? Therein, different actors’ aims definition, their actions and behaviors, which affect instability, can be regarded as independent variables; whereas, on the contrary, Middle East peace and stability perspective analysis is a dependent variable. Though, this regional peace and war theory based research admits the significant influence of trans-regional actors, it asserts the roots of violence to derive from region itself. Consequently, hot war and conflict prevention and hot peace assurance in the Middle East region cannot be attained only by demands and approaches of trans-regional actors. Moreover, capacity of trans-regional actors is sufficient only for a cold war or cold peace to be reached in the region. Furthermore, within the framework of current conflict (struggle) between regional actors it seems to be difficult and even impossible to turn the cold war into a cold peace in the region.

Keywords: Cold peace, cold war, hot war, Middle East, non-state actors, regional and Great powers, war theory.

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Authors: Zviad Ghadua, Biswa Bhattacharya

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The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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Authors: Hany Mahgoub, Dietmar Rösner, Nabil Ismail, Fawzy Torkey

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This paper describes text mining technique for automatically extracting association rules from collections of textual documents. The technique called, Extracting Association Rules from Text (EART). It depends on keyword features for discover association rules amongst keywords labeling the documents. In this work, the EART system ignores the order in which the words occur, but instead focusing on the words and their statistical distributions in documents. The main contributions of the technique are that it integrates XML technology with Information Retrieval scheme (TFIDF) (for keyword/feature selection that automatically selects the most discriminative keywords for use in association rules generation) and use Data Mining technique for association rules discovery. It consists of three phases: Text Preprocessing phase (transformation, filtration, stemming and indexing of the documents), Association Rule Mining (ARM) phase (applying our designed algorithm for Generating Association Rules based on Weighting scheme GARW) and Visualization phase (visualization of results). Experiments applied on WebPages news documents related to the outbreak of the bird flu disease. The extracted association rules contain important features and describe the informative news included in the documents collection. The performance of the EART system compared with another system that uses the Apriori algorithm throughout the execution time and evaluating extracted association rules.

Keywords: Text mining, data mining, association rule mining

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Authors: Bagher Rahimpour Cami, Hamid Hassanpour, Hoda Mashayekhi

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Nowadays websites provide a vast number of resources for users. Recommender systems have been developed as an essential element of these websites to provide a personalized environment for users. They help users to retrieve interested resources from large sets of available resources. Due to the dynamic feature of user preference, constructing an appropriate model to estimate the user preference is the major task of recommender systems. Profile matching and latent factors are two main approaches to identify user preference. In this paper, we employed the latent factor and profile matching to cluster the user profile and identify user preference, respectively. The method uses the Distance Dependent Chines Restaurant Process as a Bayesian nonparametric framework to extract the latent factors from the user profile. These latent factors are mapped to user interests and a weighted distribution is used to identify user preferences. We evaluate the proposed method using a real-world data-set that contains news tweets of a news agency (BBC). The experimental results and comparisons show the superior recommendation accuracy of the proposed approach related to existing methods, and its ability to effectively evolve over time.

Keywords: Content-based recommender systems, dynamic user modeling, extracting user interests, predicting user preference.

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Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: Heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation.

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Authors: M. Gómez-Gómez, M. E. Sánchez-Vergara

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Many sustainable approaches to generate electric energy have emerged in the last few decades; one of them is through solar cells. Yet, this also has the disadvantage of highly polluting inorganic semiconductor manufacturing processes. Therefore, the use of molecular semiconductors must be considered. In this work, allene compounds C24H26O4 and C24H26O5 were used as dopants to manufacture semiconductor films based on PbPc by high-vacuum evaporation technique. IR spectroscopy was carried out to determine the phase and any significant chemical changes which may occur during the thermal evaporation. According to UV-visible spectroscopy and Tauc’s model, the deposition process generated thin films with an activation energy range of 1.47 eV to 1.55 eV for direct transitions and 1.29 eV to 1.33 eV for indirect transitions. These values place the manufactured films within the range of low bandgap semiconductors. The flexible devices were manufactured: polyethylene terephthalate (PET), Indium tin oxide (ITO)/organic semiconductor/Cubic Close Packed (CCP). The characterization of the devices was carried out by evaluating electrical conductivity using the four-probe collinear method. I-V curves were obtained under different lighting conditions at room temperature. OS1 (PbPc/C24H26O4) showed an Ohmic behavior, while OS2 (PbPc/C24H26O5) reached higher current values at lower voltages. The results obtained show that the semiconductor devices doped with allene compounds can be used in the manufacture of optoelectronic devices.

Keywords: Electrical properties, optical gap, phthalocyanine, thin film.

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Authors: Y. N. Phang, E. F. Loh

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Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling overdispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling overdispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling overdispered medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling overdispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling overdispersed medical count data when ZIP and ZINB are inadequate.

Keywords: Zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit.

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Authors: Iau-Teh Wang, Chin-Yu Lee

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The impact force of a rockfall is mainly determined by its moving behavior and velocity, which are contingent on the rock shape, slope gradient, height, and surface roughness of the moving path. It is essential to precisely calculate the moving path of the rockfall in order to effectively minimize and prevent damages caused by the rockfall. By applying the Colorado Rockfall Simulation Program (CRSP) program as the analysis tool, this research studies the influence of three shapes of rock (spherical, cylindrical and discoidal) and surface roughness on the moving path of a single rockfall. As revealed in the analysis, in addition to the slope gradient, the geometry of the falling rock and joint roughness coefficient ( JRC ) of the slope are the main factors affecting the moving behavior of a rockfall. On a single flat slope, both the rock-s bounce height and moving velocity increase as the surface gradient increases, with a critical gradient value of 1:m = 1 . Bouncing behavior and faster moving velocity occur more easily when the rock geometry is more oval. A flat piece tends to cause sliding behavior and is easily influenced by the change of surface undulation. When JRC <1.4 the moving velocity decreases and the bounce height increases as JRC increases. If the gradient is fixed, when JRC is greater, the bounce height will be higher, while the moving velocity will experience a downward trend. Therefore, the best protecting point and facilities can be chosen if the moving paths of rockfalls are precisely estimated.

Keywords: rock shape, surface roughness, moving path.

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Authors: Fereshteh Afkari, Davood Bagheri

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The effect of teaching method on learning assistance Dunn Review .The study, to compare the effects of collaboration on teaching mathematics learning courses, including writing, science, experimental girl students by other methods of teaching basic first paid and the amount of learning students methods have been trained to cooperate with other students with other traditional methods have been trained to compare. The survey on 100 students in Tehran that using random sampling ¬ cluster of girl students between the first primary selections was performed. Considering the topic of semi-experimental research methods used to practice the necessary information by questionnaire, examination questions by the researcher, in collaboration with teachers and view authority in this field and related courses that teach these must have been collected. Research samples to test and control groups were divided. Experimental group and control group collaboration using traditional methods of mathematics courses, including writing and experimental sciences were trained. Research results using statistical methods T is obtained in two independent groups show that, through training assistance will lead to positive results and student learning in comparison with traditional methods, will increase also led to collaboration methods increase skills to solve math lesson practice, better understanding and increased skill level of students in practical lessons such as science and has been writing.

Keywords: method of teaching, learning, collaboration

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Authors: Yveta Pohnětalová, Veronika Nováková, Lucie Hrašová

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The paper presents the results of research in which we were looking for common characteristics of the family environment of students alternative and innovative education systems. Topicality comes from the fact that nowadays in the Czech Republic there are several civic and parental initiatives held with the aim to establish schools for their children. The goal of our research was to reveal key aspects of these families and to identify their common indicators. Among other things, we were interested what reasons lead parents to decide to enroll their child into different education than standard (common). The survey was qualitative and there were eighteen respondents of parents of alternative schools´ pupils. The reason to implement qualitative design was the opportunity to gain deeper insight into the essence of phenomena and to obtain detailed information, which would become the basis for subsequent quantitative research. There have been semi structured interviews done with the respondents which had been recorded and transcribed. By an analysis of gained data (categorization and by coding), we found out that common indicator of our respondents is higher education and higher economic level. This issue should be at the forefront of the researches because there is lack of analysis which would provide a comparison of common and alternative schools in the Czech Republic especially with regard to quality of education. Based on results, we consider questions whether approaches of these parents towards standard education come from their own experience or from the lack of knowledge of current goals and objectives of education policy of the Czech Republic.

Keywords: Alternative schools, family environment, quality of education, parents´ approach.

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Authors: Lule Herman, E. Ovuga, M. Mshilla, S. Ojara, G. Kimbugwe, A. P. Adrawa, N. Mahuro

Abstract:

Adolescents in Northern Uganda are at risk of teenage pregnancies, unsafe abortions and sexually transmitted infections (STIs). There is silence on sex both at home and school. This cross sectional descriptive analytical study interviews a random sample of 827 students and 13 teachers on knowledge, perception and acceptability to a comprehensive adolescent sexual and reproductive health education in “O” and “A” level secondary schools in Gulu District. Quantitative data was analyzed using SPSS 16.0. Directed content analysis of themes of transcribed qualitative data was conducted manually for common codes, sub-categories and categories. Of the 827 students; 54.3% (449) reported being in a sexual relationship especially those aged 15-17 years. Majority 96.1% (807) supported the teaching of a comprehensive ASRHE, citing no negative impact 71.5% (601). Majority 81.6% (686) agreed that such education could help prevention of STIs, abortions and teenage pregnancies, and that it should be taught by health workers 69.0% (580). Majority 76.6% (203) reported that ASRHE was not currently being taught in their schools. Students had low knowledge levels and misconceptions about ASRHE. ASRHE was highly acceptable though not being emphasized; its success in school settings requires multidisciplinary culturally sensitive approaches amongst which health workers should be frontiers.

Keywords: Acceptability, ASRHE, Knowledge, Perception.

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Authors: Sitansu Kumar Verma, Soni Yadav, Jitendra Singh, Shraddha, Ajay Kumar

Abstract:

MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.

Keywords: MicroRNAs, computational tools, gene regulation, databases, RNAi.

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Authors: Nwobu Obiamaka, Owolabi Akintola

Abstract:

This study examined the extent of statistical significant difference between the economic, environmental, governance and social aspects of sustainability reporting as a result of board committee on sustainability and time (year) of reporting for business organizations in the Nigerian banking sector. The years of reporting under consideration were 2010, 2011, 2012 and 2013. Content analysis methodology was employed through a reporting index used to score the amount of economic, environmental, governance and social indicators of sustainability reporting. The results of this study indicated that business organizations with board committee on sustainability had more indicators of sustainability reporting than those without board committees on sustainability issues. Also, sustainability reporting in 2013 was higher than that of prior years (2012, 2011 and 2010) for the economic, environmental and social indicators. The governance indicators of 2012 was highest compared to the other years (2013, 2011 and 2010) under consideration in this study. The implication of this finding is that business organizations that have board committees on sustainability are monitored by such boards to report more to their stakeholders. On the other hand, business organizations are appreciating the need to engage in sustainability reporting with each passing year. This could be due to the Central Bank of Nigeria (CBN) Sustainability Reporting framework that business organizations in the banking sector have to adhere to. When sustainability issues are monitored from the board of directors, business organizations are likely to increase and improve on their sustainability reporting.

Keywords: Governance, organizations, reporting, sustainability.

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Authors: J. P. Dubois, Omar M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool developed to a more complex concept of structural risk minimization (SRM). In this paper, SVM is applied to signal detection in communication systems in the presence of channel noise in various environments in the form of Rayleigh fading, additive white Gaussian background noise (AWGN), and interference noise generalized as additive color Gaussian noise (ACGN). The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these advanced stochastic noise models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to conventional binary signaling optimal model-based detector driven by binary phase shift keying (BPSK) modulation. We show that the SVM performance is superior to that of conventional matched filter-, innovation filter-, and Wiener filter-driven detectors, even in the presence of random Doppler carrier deviation, especially for low SNR (signal-to-noise ratio) ranges. For large SNR, the performance of the SVM was similar to that of the classical detectors. However, the convergence between SVM and maximum likelihood detection occurred at a higher SNR as the noise environment became more hostile.

Keywords: Colour noise, Doppler shift, innovation filter, least square-support vector machine, matched filter, Rayleigh fading, Wiener filter.

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Authors: Francis O. Iyoha, Daniel E. Gberevbie, Charles T. Iruonagbe, Matthew E. Egharevba

Abstract:

Cost of governance in Nigeria has become a challenge to development and concern to practitioners and scholars alike in the field of business and social science research. In the 2010 national budget of NGN4.6 trillion or USD28.75billion for instance, only a pantry sum of NGN1.8trillion or USD11.15billion was earmarked for capital expenditure. Similarly, in 2013, out of a total national budget of NGN4.92trillion or USD30.75billion, only the sum of NGN1.50trllion or USD9.38billion was voted for capital expenditure. Therefore, based on the data sourced from the Nigerian Office of Statistics, Central bank of Nigeria Statistical Bulletin as well as from the United Nations Development Programme, this study examined the causes of high cost of governance in Nigeria. It found out that the high cost of governance in the country is in the interest of the ruling class, arising from their unethical behaviour – corrupt practices and the poor management of public resources. As a result, the study recommends the need to intensify the war against corruption and mismanagement of public resources by government officials as possible solution to overcome the high cost of governance in Nigeria. This could be achieved by strengthening the constitutional powers of the various anti-corruption agencies in the area of arrest, investigation and prosecution of offenders without the interference of the executive arm of government either at the local, state or federal level.

Keywords: Capital expenditure, Cost of governance, recurrent expenditure, unethical behaviour.

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: Data mining, data science, trajectory, animal behavior.

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Authors: Aya Salama

Abstract:

Digital Twin has emerged as a compelling research area, capturing the attention of scholars over the past decade. It finds applications across diverse fields, including smart manufacturing and healthcare, offering significant time and cost savings. Notably, it often intersects with other cutting-edge technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, the concept of a Human Digital Twin (HDT) is still in its infancy and requires further demonstration of its practicality. HDT takes the notion of Digital Twin a step further by extending it to living entities, notably humans, who are vastly different from inanimate physical objects. The primary objective of this research was to create an HDT capable of automating real-time human responses by simulating human behavior. To achieve this, the study delved into various areas, including clustering, supervised classification, topic extraction, and sentiment analysis. The paper successfully demonstrated the feasibility of HDT for generating personalized responses in social messaging applications. Notably, the proposed approach achieved an overall accuracy of 63%, a highly promising result that could pave the way for further exploration of the HDT concept. The methodology employed Random Forest for clustering the question database and matching new questions, while K-nearest neighbor was utilized for sentiment analysis.

Keywords: Human Digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification and clustering.

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Authors: K. Atashgar

Abstract:

When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.

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