Search results for: Random Forests [RF].

Authors: R. Bremananth, A. Chitra

Abstract:

Cryptography provides the secure manner of information transmission over the insecure channel. It authenticates messages based on the key but not on the user. It requires a lengthy key to encrypt and decrypt the sending and receiving the messages, respectively. But these keys can be guessed or cracked. Moreover, Maintaining and sharing lengthy, random keys in enciphering and deciphering process is the critical problem in the cryptography system. A new approach is described for generating a crypto key, which is acquired from a person-s iris pattern. In the biometric field, template created by the biometric algorithm can only be authenticated with the same person. Among the biometric templates, iris features can efficiently be distinguished with individuals and produces less false positives in the larger population. This type of iris code distribution provides merely less intra-class variability that aids the cryptosystem to confidently decrypt messages with an exact matching of iris pattern. In this proposed approach, the iris features are extracted using multi resolution wavelets. It produces 135-bit iris codes from each subject and is used for encrypting/decrypting the messages. The autocorrelators are used to recall original messages from the partially corrupted data produced by the decryption process. It intends to resolve the repudiation and key management problems. Results were analyzed in both conventional iris cryptography system (CIC) and non-repudiation iris cryptography system (NRIC). It shows that this new approach provides considerably high authentication in enciphering and deciphering processes.

Keywords: Autocorrelators, biometrics cryptography, irispatterns, wavelets.

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Authors: Jana Kaděrová, Miroslav Vořechovský

Abstract:

The presented paper copes with an experimental evaluation of a model based on modified Weibull size effect theory. Classical statistical Weibull theory was modified by introducing a new parameter (correlation length lp) representing the spatial autocorrelation of a random mechanical properties of material. This size effect modification was observed on two different materials used in civil engineering: unreinforced (plain) concrete and multi-filament yarns made of alkaliresistant (AR) glass which are used for textile-reinforced concrete. The behavior under flexural, resp. tensile loading was investigated by laboratory experiments. A high number of specimens of different sizes was tested to obtain statistically significant data which were subsequently corrected and statistically processed. Due to a distortion of the measured displacements caused by the unstiff experiment device, only the maximal load values were statistically evaluated. Results of the experiments showed a decreasing strength with an increasing sample length. Size effect curves were obtained and the correlation length was fitted according to measured data. Results did not exclude the existence of the proposed new parameter lp.

Keywords: Statistical size effect, concrete, multi filaments yarns, experiment, autocorrelation length.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

Abstract:

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

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Authors: Pirom Thangchitpianpol, Suttipong Jumroonrut

Abstract:

This research investigates the distribution of food demand for animal food and the optimum amount of that food production at minimum cost. The data consist of customer purchase orders for the food of laying hens, price of food for laying hens, cost per unit for the food inventory, cost related to food of laying hens in which the food is out of stock, such as fine, overtime, urgent purchase for material. They were collected from January, 1990 to December, 2013 from a factory in Nakhonratchasima province. The collected data are analyzed in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results are used in a stochastic linear programming model for aggregate planning in which the optimum production or minimum cost could be obtained. Programming algorithms in MATLAB and tools in Linprog software are used to get the solution. The distribution of the food demand for laying hens and the random numbers are used in the model. The study shows that the distribution of monthly food demand for laying has a normal distribution, the monthly average amount (unit: 30 kg) of production from January to December. The minimum total cost average for 12 months is Baht 62,329,181.77. Therefore, the production planning can reduce the cost by 14.64% from real cost.

Keywords: Animal food, Stochastic linear programming, Production planning, Demand Uncertainty.

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Authors: Kathaleeya Chanda, Panupong Chanplin, Suppara Charoenpoom

Abstract:

This purposes of the development of creative instruction model through digital media are to: 1) enable learners to learn from instruction media application; 2) help learners implementing instruction media correctly and appropriately; and 3) facilitate learners to apply technology for searching information and practicing skills to implement technology creatively. The sample group consists of 130 cases of secondary students studying in Bo Kluea School, Bo Kluea Nuea Sub-district, Bo Kluea District, Nan Province. The probability sampling was selected through the simple random sampling and the statistics used in this research are percentage, mean, standard deviation and one group pretest – posttest design. The findings are summarized as follows: The congruence index of instruction media for occupation and technology subjects is appropriate. By comparing between learning achievements before implementing the instruction media and learning achievements after implementing the instruction media, it is found that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. For the learning achievements from instruction media implementation, pretest mean is 16.24 while posttest mean is 26.28. Besides, pretest and posttest results are compared and differences of mean are tested, the test results show that the posttest achievements are higher than the pretest achievements with statistical significance at the level of .05. This can be interpreted that the learners achieve better learning progress.

Keywords: Teaching learning model, digital media, creative instruction model, facilitate learners.

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Authors: S. Z. Moussavi, A. Badri, F. Rastegar Kashkooli

Abstract:

Wind farms (WFs) with high level of penetration are being established in power systems worldwide more rapidly than other renewable resources. The Independent System Operator (ISO), as a policy maker, should propose appropriate places for WF installation in order to maximize the benefits for the investors. There is also a possibility of congestion relief using the new installation of WFs which should be taken into account by the ISO when proposing the locations for WF installation. In this context, efficient wind farm (WF) placement method is proposed in order to reduce burdens on congested lines. Since the wind speed is a random variable and load forecasts also contain uncertainties, probabilistic approaches are used for this type of study. AC probabilistic optimal power flow (P-OPF) is formulated and solved using Monte Carlo Simulations (MCS). In order to reduce computation time, point estimate methods (PEM) are introduced as efficient alternative for time-demanding MCS. Subsequently, WF optimal placement is determined using generation shift distribution factors (GSDF) considering a new parameter entitled, wind availability factor (WAF). In order to obtain more realistic results, N-1 contingency analysis is employed to find the optimal size of WF, by means of line outage distribution factors (LODF). The IEEE 30-bus test system is used to show and compare the accuracy of proposed methodology.

Keywords: Probabilistic optimal power flow, Wind power, Pointestimate methods, Congestion management

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Authors: Iau-Teh Wang, Chin-Yu Lee

Abstract:

Rockfall is a kind of irregular geological disaster. Its destruction time, space and movements are highly random. The impact force is determined by the way and velocity rocks move. The movement velocity of a rockfall depends on slope gradient of its moving paths, height, slope surface roughness and rock shapes. For effectively mitigate and prevent disasters brought by rockfalls, it is required to precisely calculate the moving paths of a rockfall so as to provide the best protective design. This paper applies Colorado Rockfall Simulation Program (CRSP) as our study tool to discuss the impact of slope shape and surface roughness on the moving paths of a single rockfall. The analytical results showed that the slope, m=1:1, acted as the threshold for rockfall bounce height on a monoclinal slight slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce height increased as JCR increased. If slope fixed and JRC increased, the bounce height of rocks increased gradually with reducing movement velocity. Therefore, the analysis on the moving paths of rockfalls with CRSP could simulate bouncing of falling rocks. By analyzing moving paths, velocity, and bounce height of falling rocks, we could effectively locate impact points of falling rocks on a slope. Such analysis can be served as a reference for future disaster prevention and control.

Keywords: Rockfall, Slope Shape, Moving Path, SurfaceRoughness.

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Authors: Ilaria Lucrezia Amerise

Abstract:

The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: Generalized extreme values (GEV), likelihood estimation, precipitation data, Wakeby distribution.

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Authors: Avadhoot Bhosale, Robin Davis P., Pradip Sarkar

Abstract:

The seismic performance of buildings with irregular distribution of mass, stiffness and strength along the height may be significantly different from that of regular buildings with masonry infill. Masonry infilled reinforced concrete (RC) frames are very common structural forms used for multi-storey building construction. These structures are found to perform better in past earthquakes owing to additional strength, stiffness and energy dissipation in the infill walls. The seismic performance of a building depends on the variation of material, structural and geometrical properties. The sensitivity of these properties affects the seismic response of the building. The main objective of the sensitivity analysis is to found out the most sensitive parameter that affects the response of the building. This paper presents a sensitivity analysis by considering 5% and 95% probability value of random variable in the infills characteristics, trying to obtain a reasonable range of results representing a wide number of possible situations that can be met in practice by using pushover analysis. The results show that the strength-related variation values of concrete and masonry, with the exception of tensile strength of the concrete, have shown a significant effect on the structural performance and that this effect increases with the progress of damage condition for the concrete. The seismic risk assessments of the selected frames are expressed in terms of reliability index.

Keywords: Fragility curve, sensitivity analysis, reliability index, RC frames.

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Authors: Ibrahim Abdel Gadir Malik, Dafalla Siddig Dafalla, Abdelazim Ibrahim

Abstract:

Jabal Omar is located in the western side of Makkah city in Saudi Arabia. The proposed Jabal Omar Development project includes several multi-storey buildings, roads, bridges and below ground structures founded at various depths. In this study, geological mapping and site inspection which covered pre-selected areas were carried out within the easily accessed parts. Geological features; including rock types, structures, degree of weathering, and geotechnical hazards were observed and analyzed with specified software and also were documented in form of photographs. The presence of joints and fractures in the area made the rock blocks small and weak. The site is full of jointing; it was observed that, the northern side consists of 3 to 4 jointing systems with 2 random fractures associated with dykes. The southern part is affected by 2 to 3 jointing systems with minor fault and shear zones. From the field measurements and observations, it was concluded that, the Jabal Omar intruded by andesitic and basaltic dykes of different thickness and orientation. These dykes made the outcrop weak, highly deformed and made the rock masses sensitive to weathering.

Keywords: Rock, slope, stabilization, protection, Makkah.

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Authors: M. Athar Hussain, N.B. Jumani, Munazza Sultana., M. Zafar Iqbal

Abstract:

Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.

Keywords: Information and communication technologies, internet assisted learning, teaching business English, online instructional content.

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Authors: Thanasit Suksutdhi

Abstract:

This survey research aims to study the standard of service quality of food and beverage service staffs in hotel business by studying the service standard of three sample hotels, Siam Kempinski Hotel Bangkok, Four Seasons Resort Chiang Mai, and Banyan Tree Phuket. In order to find the international service standard of food and beverage service, triangular research, i.e. quantitative, qualitative, and survey were employed. In this research, questionnaires and in-depth interview were used for getting the information on the sequences and method of services. There were three parts of modified questionnaires to measure service quality and guest’s satisfaction including service facilities, attentiveness, responsibility, reliability, and circumspection. This study used sample random sampling to derive subjects with the return rate of the questionnaires was 70% or 280. Data were analyzed by SPSS to find arithmetic mean, SD, percentage, and comparison by t-test and One-way ANOVA. The results revealed that the service quality of the three hotels were in the international level which could create high satisfaction to the international customers. Recommendations for research implementations were to maintain the area of good service quality, and to improve some dimensions of service quality such as reliability. Training in service standard, product knowledge, and new technology for employees should be provided. Furthermore, in order to develop the service quality of the industry, training collaboration between hotel organization and educational institutions in food and beverage service should be considered.

Keywords: Service standard, food and beverage department, sequence of service, service method.

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Authors: Isabela Moreira Queiroz

Abstract:

Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management. 

Keywords: Probabilistic methods, risk assessment, risk management, slope stability.

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Authors: Fl. Loury, P. Sablonière

Abstract:

In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.

Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

Abstract:

Safety and security of Autonomous Vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, paper proposes fault-tolerance by diversity model taking into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: Autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security.

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Authors: Revoti Prasad Bora, Nikita Katyal

Abstract:

Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, cannibalization, promotion, baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression.

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Authors: Yi-Hsiang Pan

Abstract:

The purpose of this study was to develop a “teachers’ self-efficacy scale for high school physical education teachers (TSES-HSPET)” in Taiwan. This scale is based on the self-efficacy theory of Bandura [1], [2]. This study used exploratory and confirmatory factor analyses to test the reliability and validity. The participants were high school physical education teachers in Taiwan. Both stratified random sampling and cluster sampling were used to sample participants for the study. 350 teachers were sampled in the first stage and 234 valid scales (male 133, female 101) returned. During the second stage, 350 teachers were sampled and 257 valid scales (male 143, female 110, 4 did not indicate gender) returned. The exploratory factor analysis was used in the first stage, and it got 60.77% of total variance for construct validity. The Cronbach’s alpha coefficient of internal consistency was 0.91 for sumscale, and subscales were 0.84 and 0.90. In the second stage, confirmatory factor analysis was used to test construct validity. The result showed that the fit index could be accepted (χ2 (75) =167.94, p <.05, RMSEA =0.07, SRMR=0.05, GFI=0.92, NNFI=0.97, CFI=0.98, PNFI=0.79). Average variance extracted of latent variables were 0.43 and 0.53, which composite reliability are 0.78 and 0.90. It is concluded that the TSES-HSPET is a well-considered measurement instrument with acceptable validity and reliability. It may be used to estimate teachers’ self-efficacy for high school physical education teachers.

Keywords: teaching in physical education, teacher's self-efficacy, teacher's belief

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Authors: Walid MOUDANI

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.

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Authors: Fereshteh Afkari, Davood Bagheri

Abstract:

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: S.Shanmugam, V.G. Srisanthi, S.Ramachandran

Abstract:

Reinforced concrete has good durability and excellent structural performance. But there are cases of early deterioration due to a number of factors, one prominent factor being corrosion of steel reinforcement. The process of corrosion sets in due to ingress of moisture, oxygen and other ingredients into the body of concrete, which is unsound, permeable and absorbent. Cracks due to structural and other causes such as creep, shrinkage, etc also allow ingress of moisture and other harmful ingredients and thus accelerate the rate of corrosion. There are several interactive factors both external and internal, which lead to corrosion of reinforcement and ultimately failure of structures. Suitable addition of mineral admixture like silica fume (SF) in concrete improves the strength and durability of concrete due to considerable improvement in the microstructure of concrete composites, especially at the transition zone. Secondary reinforcement in the form of fibre is added to concrete, which provides three dimensional random reinforcement in the entire mass of concrete. Reinforced concrete beams of size 0.1 m X 0.15 m and length 1m have been cast using M 35 grade of concrete. The beams after curing process were subjected to corrosion process by impressing an external Direct Current (Galvanostatic Method) for a period of 15 days under stressed and unstressed conditions. The corroded beams were tested by applying two point loads to determine the ultimate load carrying capacity and cracking pattern and the results of specimens were compared with that of the companion specimens. Gravimetric method is used to quantify corrosion that has occurred.

Keywords: Carbonation, Corrosion, Cracking, Spalling.

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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: Patrick Cummings, Laura Cassani, Deirdre Kelliher

Abstract:

In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps.

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Authors: Izian Abd. Karim, Kachalla Mohammed, Nora Farah A. A. Aziz, Law Teik Hua

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The economic use and ease of construction of profiled deck composite slab is marred with the complex and un-economic strength verification required for the serviceability and general safety considerations. Beside these, albeit factors such as shear span length, deck geometries and mechanical frictions greatly influence the longitudinal shear strength, that determines the ultimate strength of profiled deck composite slab, and number of methods available for its determination; partial shear and slope-intercept are the two methods according to Euro-code 4 provision. However, the complexity associated with shear behavior of profiled deck composite slab, the use of these methods in determining the load carrying capacities of such slab yields different and conflicting values. This couple with the time and cost constraint associated with the strength verification is a source of concern that draws more attentions nowadays, the issue is critical. Treating some of these known shear strength influencing factors as random variables, the load carrying capacity violation of profiled deck composite slab from the use of the two-methods defined according to Euro-code 4 are determined using reliability approach, and comparatively studied. The study reveals safety values from the use of m-k method shows good standing compared with that from the partial shear method.

Keywords: Composite slab, first order reliability method, longitudinal shear, partial shear connection, slope-intercept.

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

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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: Salako Emmanuel Adekunle

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Computer education is referred to as the knowledge and ability to use computers and related technology efficiently, with a range of skills covering levels from basic use to advance. Computer continues to make an ever-increasing impact on all aspect of human endeavours such as education. With numerous benefits of computer education, what are the insights of students on computer education? This study investigated the perception of senior secondary school students on computer education in Federal Capital Territory (FCT), Abuja, Nigeria. A sample of 7500 senior secondary schools students was involved in the study, one hundred (100) private and fifty (50) public schools within FCT. They were selected by using simple random sampling technique. A questionnaire [PSSSCEQ] was developed and validated through expert judgement and reliability coefficient of 0.84 was obtained. It was used to gather relevant data on computer education. Findings confirmed that the students in the FCT had positive perception on computer education. Some factors were identified that affect students’ perception on computer education. The null hypotheses were tested using t-test and ANOVA statistical analyses at 0.05 level of significance. Based on these findings, some recommendations were made which include competent teachers should be employed into all secondary schools. This will help students to acquire relevant knowledge in computer education, technological supports should be provided to all secondary schools; this will help the users (students) to solve specific problems in computer education and financial supports should be provided to procure computer facilities that will enhance the teaching and the learning of computer education.

Keywords: Computer education, perception, secondary school, students.

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Authors: Salako Emmanuel Adekunle

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With numerous advantages of ICT in teaching such as using images to improve the retentive memory of students, academic staff is yet to deliver instructions adequately and effectively due to no power supply, lack of technical supports and non-availability of functional ICT tools. This study was conducted to investigate the attitudes of academic staff towards the use of information communication technology as a pedagogical tool for effective teaching in FCT College of Education, Zuba-Abuja, Nigeria. A sample of 200 academic staff from five schools/faculties was involved in the study. The respondents were selected by using simple random sampling technique (SRST). A questionnaire was developed and validated by the experts in Measurement and Evaluation, and reliability co-efficient of 0.85 was obtained. It was used to gather relevant data from the respondents. This study revealed that the respondents had positive attitudes towards the use of ICT as a pedagogical tool for effective teaching. Also, the uses of ICT by the academic staff included: to encourage closer relationship for attainment of higher academic, and to deliver instructions effectively. The study also revealed that there is a significant relationship between the attitudes and the uses of ICT by the academic staff. Based on these findings, some recommendations were made which include: power supply should be provided to operate ICT facilities for effective teaching, and technical assistance on ICT usage for effective delivery of instructions should be provided among other recommendations.

Keywords: Academic staff, attitudes, information communication technology, pedagogical tool, teaching and use.

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Authors: A. S. Haruna, M. U. Tambawal, A. A. Salawu

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The psychological impact of peer influence on its individual group members, can make them resist HIV/AIDS counselling and testing. This study investigated the correlate of peer influence and resistance to HIV/AIDS counselling and testing among students in tertiary institutions in Kano state, Nigeria. To achieve this, three null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841.Simple Random Sampling was used in the selection. A self-developed 20-item scale called Peer Influence and Psychological Resistance Inventory (PIPRI) was used for data collection. Pearson Product Moment Correlation (PPMCC) via test-retest method was applied to estimate a reliability coefficient of 0.86 for the scale. Data obtained was analyzed using t-test and PPMCC at 0.05 level of confidence. Results reveal 26.3% (397) of the respondents being influenced by their peer group, while 39.8% showed resistance. Also, the t-tests and PPMCC statistics were greater than their respective critical values. This shows that there was a significant gender difference in peer influence and a difference between peer influence and resistance to HIV/AIDS counselling and testing. However, a positive relationship between peer influence and resistance to HIV/AIDS counselling and testing was shown. A major recommendation offered suggests the use of reinforcement and social support for positive attitudes and maintenance of safe behaviour among students who patronize HIV/AIDS counselling.

Keywords: Peer influence, HIV/AIDS counselling and testing, Resistance.

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Authors: Aya Salama

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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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