Search results for: random generation

Authors: Jianwei Ma, Diriba Gemechu

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

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

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

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Authors: Y. B. Kirankumar, J. D. Mallapur

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Wireless Sensor Network (WSN) is an emerging technology, which has great invention for various low cost applications both for mass public as well as for defence. The wireless sensor communication technology allows random participation of sensor nodes with particular applications to take part in the network, which results in most of the uncovered simulation area, where fewer nodes are located at far distances. The drawback of such network would be that the additional energy is spent by the nodes located in a pattern of dense location, using more number of nodes for a smaller distance of communication adversely in a region with less number of nodes and additional energy is again spent by the source node in order to transmit a packet to neighbours, thereby transmitting the packet to reach the destination. The proposed work is intended to develop Energy Efficient Node Placement Algorithm (EENPA) in order to place the sensor node efficiently in simulated area, where all the nodes are equally located on a radial path to cover maximum area at equidistance. The total energy consumed by each node compared to random placement of nodes is less by having equal burden on fewer nodes of far location, having distributed the nodes in whole of the simulation area. Calculating the network lifetime also proves to be efficient as compared to random placement of nodes, hence increasing the network lifetime, too. Simulation is been carried out in a qualnet simulator, results are obtained on par with random placement of nodes with EENP algorithm.

Keywords: energy, WSN, wireless sensor network, energy approach

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Authors: Siamack A. Shirazi, Farzin Darihaki

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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.

Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid

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Authors: Kateriina Rannula, Elle Sõrmus, Siret Piirsalu

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Mixed generation classroom is a phenomenon that current higher education establishments are faced with daily trying to meet the needs of modern labor market with its emphasis on lifelong learning and retraining. Representatives of mainly X and Y generations in one classroom acquiring higher education is a challenge to lecturers considering all the characteristics that differ one generation from another. The importance of outlining different strategies and considering the needs of the students lies in the necessity for everyone to acquire the maximum of the provided knowledge as well as to understand each other to study together in one classroom and successfully cooperate in future workplaces. In addition to different generations, there are also learners with different native languages which have an impact on reading and understanding texts in third languages, including possible translation. Current research aims to investigate, describe and compare reading strategies among the representatives of generation X and Y. Hypotheses were formulated - representatives of generation X and Y use different reading strategies which is also different among first and third year students of the before mentioned generations. Current study is an empirical, qualitative study. To achieve the aim of the research, relevant literature was analyzed and a semi-structured questionnaire conducted among the first and third year students of Tallinn Health Care College. Questionnaire consisted of 25 statements on the text reading strategies, 3 multiple choice questions on preferences considering the design and medium of the text, and three open questions on the translation process when working with a text in student’s third language. The results of the questionnaire were categorized, analyzed and compared. Both, generation X and Y described their reading strategies to be 'scanning' and 'surfing'. Compared to generation X, first year generation Y learners valued interactivity and nonlinear texts. Students frequently used strategies of skimming, scanning, translating and highlighting together with relevant-thinking and assistance-seeking. Meanwhile, the third-year generation Y students no longer frequently used translating, resourcing and highlighting while Generation X learners still incorporated these strategies. Knowing about different needs of the generations currently inside the classrooms and on the labor market enables us with tools to provide sustainable education and grants the society a work force that is more flexible and able to move between professions. Future research should be conducted in order to investigate the amount of learning and strategy- adoption between generations. As for reading, main suggestions arising from the research are as follows: make a variety of materials available to students; allow them to select what they want to read and try to make those materials visually attractive, relevant, and appropriately challenging for learners considering the differences of generations.

Keywords: generation X, generation Y, learning strategies, reading strategies

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Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that is highly recommended or required for safety-critical software coverage. Therefore, many testing standards include this criterion and require it to be satisfied at a particular level of testing (e.g. validation and unit levels). However, an important amount of time is needed to meet those requirements. In this paper we propose to automate MC/DC test data generation. Thus, we present an approach to automatically generate MC/DC test data, from software module description written over a dedicated language. We introduce a new merging approach that provides high MC/DC coverage for the description, with only a little number of test cases.

Keywords: domain-specific language, MC/DC, test data generation, safety-critical software coverage

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Authors: Dongkyu Lee, Doan-Quoc Hoan, Soomi Shin

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The purpose of this study is to suggest the Value Innovation type Breakthrough Innovation which is a Big Thinking Process that realizes a creative idea for the next generation innovation Master Plan of a company. The BI based on the PVI methodology is believed to contribute to the launching of a new business, the acquisition of new markets, and the development of an innovative management process.

Keywords: value, innovation, breakthrough innovation, Korean firm

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Authors: Arfan Riasat, M. Iqbal Zafar, Gulfam Riasat

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Pakistani women actively participate in livestock management activities, along with their normal domestic chores. The study was designed to measure the position and contribution of rural women, their constraints in livestock management activities and mainly how the rural women contribute for development in the district Faisalabad. It was envisioned that women participation in livestock activities have rarely been investigated. A multistage random sampling technique was used to collect the data from Tehsil Summandry of the district selected at random. Two union councils were taken by using simple random sampling technique. Four Chak (village) from each union council were selected at random and fifteen woman were further selected randomly from each selected chak. The results show that a vast majority of women were illiterate, having annual family income of one to two lac. They are living in joint family system. Their main occupation is agriculture and they spend long hours in whole livestock related activities to support their families. A large proportion of the respondents reported that they had to face problems and constraints in livestock activities in the context of decision making, medication, awareness, training along with social and economic issues. Analysis indicated that education level of women, income of household, age were significantly associated with level of participation. Women participation in livestock activities increased production and they were involved in income generating activities for better economic conditions of their families.

Keywords: women, participation, livestock, management, rural development

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Authors: Arezoo Heidary, Abolfazl Mirzazadeh, Aref Gholami-Qadikolaei

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In the business environment it is very common that a lot received may not be equal to quantity ordered. in this work, a random disturbance in a received quantity is considered. It is assumed a maximum allowable limit for storage space and inventory investment.The impact of lead time and ordering cost reductions once they act dependently is also investigated. Further, considering a mixture of back order and lost sales for allowable shortage system, the effect of investment on reducing lost sale rate is analyzed. For the proposed control system, a Lagrangian method is applied in order to solve the problem and an algorithmic procedure is utilized to achieve optimal solution with the global minimum expected cost. Finally, proves on concavity and convexity of the model in the decision variables are shown.

Keywords: stochastic inventory system, lead time, ordering cost, lost sale rate, inventory constraints, random disturbance

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Authors: Aliyu Mohammed Lawal, Dahiru Ya'u Gital

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The problems placed on the environment as a result of energy generation and usage in Nigeria are: Potential damage to the environment health by Co, Co2, Sox and Nox effluent gas emissions and global warming. For instance in the year 2004 in Nigeria energy consumption was 58% oil and 34% natural gas but about 94 million metric tons of Co2 was emitted out of which 64% came from fossil fuels while about 35% came from fuel wood. The findings from this research on how to alleviate these problems are that long term sustainable development solutions should be enhanced globally; energy should be used more rationally renewable energy resources should be exploited and the existing emissions should be controlled to tolerate limits because the increase in energy demand in Nigeria places enormous strain on current energy facilities.

Keywords: energy generation, environmental health, effluent gas emission, global warming, fossil fuel

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets.

Keywords: discriminative LMA features, features reduction, human motion recognition, random forest

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: Lauren M. McKinnon, Justin B. Miller, Michael F. Whiting, John S. K. Kauwe, Perry G. Ridge

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Background: Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Methods: Ramp sequences were compared from 211 vertebrates (110 Mammalian and 101 non-mammalian). The presence and absence of ramp sequences were analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life taxonomy to determine the number of parallelisms and reversals that occurred, and these results were compared to what would be expected due to random chance. Lastly, aligned nucleotides in ramp sequences were compared to the rest of the sequence in order to examine possible differences in phylogenetic signal between these regions of the gene. Results: Parsimony and maximum likelihood analyses of the presence/absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, the retention index of ramp sequences is significantly higher than would be expected due to random chance (p-value = 0). A chi-square analysis of completely orthologous ramp sequences resulted in a p-value of approximately zero as compared to random chance. Discussion: Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches.

Keywords: codon usage bias, phylogenetics, phylogenomics, ramp sequence

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: Larry Hawkins, Scott K. Sakakura, Michael J. Salopek

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The Marshall Space Flight Center is designing and building a next-generation CO₂ removal system, the Four Bed Carbon Dioxide Scrubber (4BCO₂), which will use the International Space Station (ISS) as a testbed. The current ISS CO2 removal system has faced many challenges in both performance and reliability. Given that CO2 removal is an integral Environmental Control and Life Support System (ECLSS) subsystem, the 4BCO2 Scrubber has been designed to eliminate the shortfalls identified in the current ISS system. One of the key required upgrades was to improve the performance and reliability of the blower that provides the airflow through the CO₂ sorbent beds. A magnetically levitated blower, capable of higher airflow and pressure than the previous system, was developed to meet this need. The design and qualification testing of this next-generation blower are described here. The new blower features a high-efficiency permanent magnet motor, a five-axis, active magnetic bearing system, and a compact controller containing both a variable speed drive and a magnetic bearing controller. The blower uses a centrifugal impeller to pull air from the inlet port and drive it through an annular space around the motor and magnetic bearing components to the exhaust port. Technical challenges of the blower and controller development include survival of the blower system under launch random vibration loads, operation in microgravity, packaging under strict size and weight requirements, and successful operation during 4BCO₂ operational changeovers. An ANSYS structural dynamic model of the controller was used to predict response to the NASA defined random vibration spectrum and drive minor design changes. The simulation results are compared to measurements from qualification testing the controller on a vibration table. Predicted blower performance is compared to flow loop testing measurements. Dynamic response of the system to valve changeovers is presented and discussed using high bandwidth measurements from dynamic pressure probes, magnetic bearing position sensors, and actuator coil currents. The results presented in the paper show that the blower controller will survive launch vibration levels, the blower flow meets the requirements, and the magnetic bearings have adequate load capacity and control bandwidth to maintain the desired rotor position during the valve changeover transients.

Keywords: blower, carbon dioxide removal, environmental control and life support system, magnetic bearing, permanent magnet motor, validation testing, vibration

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Authors: Kuan-Wei Chen, Chien-Wei Chen, Tai-Ling Chang, Nan-Cheng Chen, Ching-Lin Hsieh, Gong-Hong Lin

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Background and Purposes: Deficits in sustained attention are common in patients with schizophrenia. Such impairment can limit patients to effectively execute daily activities and affect the efficacy of rehabilitation. The aims of this study were to examine the test-retest agreement, random measurement error, and practice effect of the Continuous Performance Test-Identical Pairs (CPT-IP) (a commonly used sustained attention test) in patients with schizophrenia. The results can provide empirical evidence for clinicians and researchers to apply a sustained attention test with sound psychometric properties in schizophrenia patients. Methods: We recruited patients with chronic schizophrenia to be assessed twice with 1 week interval using CPT-IP. The intra-class correlation coefficient (ICC) was used to examine the test-retest agreement. The percentage of minimal detectable change (MDC%) was used to examine the random measurement error. Moreover, the standardized response mean (SRM) was used to examine the practice effect. Results: A total of 56 patients participated in this study. Our results showed that the ICC was 0.82, MDC% was 47.4%, and SRMs were 0.36 for the CPT-IP. Conclusion: Our results indicate that CPT-IP has acceptable test-retests agreement, substantial random measurement error, and small practice effect in patients with schizophrenia. Therefore, to avoid overestimating patients’ changes in sustained attention, we suggest that clinicians interpret the change scores of CPT-IP conservatively in their routine repeated assessments.

Keywords: schizophrenia, sustained attention, CPT-IP, reliability

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Authors: Bernadette F. De La Cruz, Susan Marie R. Dela Cruz, Georgia D. Demavibas

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The Expanded Student Grant-in-Aid Program for Poverty Alleviation (ESGP-PA) is a government program that aims to contribute to the National Government’s thrusts in effectively addressing poverty alleviation by increasing the number of graduates in higher education among indigent households and to get these graduates employed in in-demand occupations in order to lift their families out of poverty. Higher education continues to see an influx of these students from poor families that have never previously sent anyone to college. There are many challenges that face college students at all levels, but these are special challenges for first-generation students. Challenges that face these students can include lack of interest in attending school, low aptitude, being not single anymore, factors such as unfamiliarity with college expectations, lack of preparations while in secondary school, and limited support from family members. This research looks at some of the challenges first-generation college students face and examines the impact of these challenges on student’s aspirations for the attainment of a college degree and ultimately a high-paying career.

Keywords: ESGP-PA, first-generation college students, low aptitude, poverty alleviation

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Authors: Pradthana Sianglam, Wittaya Ngeontae

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A new approach for the fabrication of cadmium ion (Cd2+) sensor is demonstrated. The detection principle is based on the in-situ generation of cadmium sulfide quantum dots (CdS QDs) in the presence of chiral thiol containing compound and detection by the circular dichroism spectroscopy (CD). Basically, the generation of CdS QDs can be done in the presence of Cd2+, sulfide ion and suitable capping compounds. In addition, the strong CD signal can be recorded if the generated QDs possess chiral property (from chiral capping molecule). Thus, the degree of CD signal change depends on the number of the generated CdS QDs which can be related to the concentration of Cd2+ (excess of other components). In this work, we use the mixture of cysteamine (Cys) and L-Penicillamine (LPA) as the capping molecules. The strong CD signal can be observed when the solution contains sodium sulfide, Cys, LPA, and Cd2+. Moreover, the CD signal is linearly related to the concentration of Cd2+. This approach shows excellence selectivity towards the detection of Cd2+ when comparing to other cation. The proposed CD sensor provides low limit detection limits around 70 µM and can be used with real water samples with satisfactory results.

Keywords: circular dichroism sensor, quantum dots, enaniomer, in-situ generation, chemical sensor, heavy metal ion

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Authors: Rasaq Kareem, Jacob Gbadeyan

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In this study, analysis of the entropy generation of an unsteady reactive hydromagnetic generalized couette fluid flow of a two-step exothermic chemical reaction through a channel with isothermal wall temperature under the influence of different chemical kinetics namely: Sensitized, Arrhenius and Bimolecular kinetics was investigated. The modelled nonlinear dimensionless equations governing the fluid flow were simplified and solved using the combined Laplace Differential Transform Method (LDTM). The effects of fluid parameters associated with the problem on the fluid temperature, entropy generation rate and Bejan number were discussed and presented through graphs.

Keywords: couette, entropy, exothermic, unsteady

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Houda Jalali, Hassan Abbassi

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In this numerical work, natural convection and entropy generation of Al₂O₃–water nanofluid in square cavity have been studied. A two-dimensional steady laminar natural convection in a differentially heated square cavity of length L, filled with a nanofluid is investigated numerically. The horizontal walls are considered adiabatic. Vertical walls corresponding to x=0 and x=L are respectively maintained at hot temperature, T_h and cold temperature, T_c. The resolution is performed by the CFD code "FLUENT" in combination with GAMBIT as mesh generator. These simulations are performed by maintaining the Rayleigh numbers varied as 10³ ≤ Ra ≤ 10⁶, while the solid volume fraction varied from 1% to 5%, the particle size is fixed at dp=33 nm and a range of the temperature from 20 to 70 °C. We used models of thermophysical nanofluids properties based on experimental measurements for studying the effect of adding solid particle into water in natural convection heat transfer and entropy generation of nanofluid. Such as models of thermal conductivity and dynamic viscosity which are dependent on solid volume fraction, particle size and temperature. The average Nusselt number is calculated at the hot wall of the cavity in a different solid volume fraction. The most important results is that at low temperatures (less than 40 °C), the addition of nanosolids Al₂O₃ into water leads to a decrease in heat transfer and entropy generation instead of the expected increase, whereas at high temperature, heat transfer and entropy generation increase with the addition of nanosolids. This behavior is due to the contradictory effects of viscosity and thermal conductivity of the nanofluid. These effects are discussed in this work.

Keywords: entropy generation, heat transfer, nanofluid, natural convection

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Authors: Geoffrey J. Blanford, Christoph Weissbart

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The prospects for the European power sector indicate that it has to almost fully decarbonize in order to reach the economy-wide target of CO₂-emission reduction. We apply the EU-REGEN model to explain the penetration of RES from an economic perspective, their spatial distribution, and the complementary role of conventional generation technologies. Furthermore, we identify economic consequences of national energy and climate targets. Our study shows that onshore wind power will be the most crucial generation technology for the future European power sector. Its geographic distribution is driven by resource quality. Gas power will be the major conventional generation technology for backing-up wind power. Moreover, a complete phase out of coal power proves to be not economically optimal. The paper demonstrates that existing national targets have a negative impact, especially on the German region with higher prices and lower revenues. The remaining regions profit are hardly affected. We encourage an EU-wide coordination on the expansion of wind power with harmonized policies. Yet, this requires profitable market structures for both, RES and conventional generation technologies.

Keywords: European, policy evaluation, power sector investment, technology choices

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Authors: Adavbiele Airewe Stephen

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Sustainable energy use is exploiting energy resources within acceptable levels of global resource depletion without destroying the ecological balance of an area. In the context of sustainability, the rush to quell the energy crisis of the fossil fuels of the 1970's by embarking on nuclear energy technology has now been seen as a disaster. In the circumstance, action (policy) suggested in this study to avoid future occurrence is exergy maximization/entropy generation minimization and the use is renewable energy technologies that are hybrid based. Thirty-two (32) selected hybrid renewable energy technologies were assessed with respect to their energetic efficiencies and entropy generation. The results indicated that determining which of the hybrid technologies is the most efficient process and sustainable is a matter of defining efficiency and knowing which of them possesses the minimum entropy generation.

Keywords: entropy, exergy, hybrid renewable energy technologies, sustainability

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Authors: Min-Hao Wang, Shih-Chih Chen

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Recently, the merits such as simple structure, low power consumption, and compatibility with complementary metal oxide semiconductor (CMOS) process give an advantage of resistive random access memory (RRAM) as a promising candidate for the next generation memory， hafnium dioxide (HfO2) has been widely studied as an oxide layer material, but the use of copper (Cu) as both top and bottom electrodes has rarely been studied. In this study, radio frequency sputtering was used to deposit the intermediate layer HfO₂, and electron beam evaporation was used. For the upper and lower electrodes (cu), using different AR: O ratios, we found that the control of the metal filament will make the filament widely distributed, causing the current to rise to the limit current during Reset. However, if the flow ratio is controlled well, the ON/OFF ratio can reach 104, and the set voltage is controlled below 3v.

Keywords: RRAM, metal filament, HfO₂, Cu electrode

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Authors: Oluseyi O. Ajayi, Ohiose D. Ohijeagbon, Mercy Ogbonnaya, Ameh Attabo

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The study assessed the potential and economic viability of stand-alone wind systems for embedded generation, taking into account its benefits to small off-grid rural communities at 40 meteorological sites in Nigeria. A specific electric load profile was developed to accommodate communities consisting of 200 homes, a school and a community health centre. This load profile was incorporated within the distributed generation analysis producing energy in the MW range, while optimally meeting daily load demand for the rural communities. Twenty-four years (1987 to 2010) of wind speed data at a height of 10m utilized for the study were sourced from the Nigeria Meteorological Department, Oshodi. The HOMER® software optimizing tool was engaged for the feasibility study and design. Each site was suited to 3MW wind turbines in sets of five, thus 15MW was designed for each site. This design configuration was adopted in order to easily compare the distributed generation system amongst the sites to determine their relative economic viability in terms of life cycle cost, as well as levelised cost of producing energy. A net present value was estimated in terms of life cycle cost for 25 of the 40 meteorological sites. On the other hand, the remaining sites yielded a net present cost; meaning the installations at these locations were not economically viable when utilizing the present tariff regime for embedded generation in Nigeria.

Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, Nigeria

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Authors: Sara Zadehomidi

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Iran, a geographically arid and semi-arid country, experiences varying levels of rainfall across its territory. Five major and important rivers, namely Karun, Dez, Karkheh, Jarrahi, and Hendijan, are valuable assets of the Khuzestan province. To address various needs, including those of farmers (especially during hot seasons with no rainfall), drinking water requirements, industrial and environmental, and most importantly, electricity production, dams have been constructed on several of these rivers, with some dams still under construction. The outflow of water from dam reservoirs must be managed in a way that not only preserves the reservoir's potential effectively but also ensures the maximum revenue from electricity generation. Furthermore, it should meet the other mentioned requirements. In this study, scientific methods such as optimization using Lingo software were employed to achieve these objectives. The results, when executed and adhering to the proposed electricity production program with Lingo software, indicate a 35.7% increase in electricity sales revenue over a one-year examination period. Considering that several electricity plants are currently under construction, the importance and necessity of utilizing computer systems for expediting and optimizing the electricity generation program planning from electricity plants will become evident in the future.

Keywords: Ahvaz, electricity generation programs, Iran, optimizing

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Authors: M. N. Tandjaoui, C. Banoudjafar, C. Benachaiba, O. Abdelkhalek, A. Kechich

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Advanced power electronic systems are deemed to be an integral part of renewable, green, and efficient energy systems. Wind energy is one of the renewable means of electricity generation that is now the world’s fastest growing energy source can bring new challenges when it is connected to the power grid due to the fluctuation nature of the wind and the comparatively new types of its generators. The wind energy is part of the worldwide discussion on the future of energy generation and use and consequent effects on the environment. However, this paper will introduce some of the requirements and aspects of the power electronic involved with modern wind generation systems, including modern power electronics and converters, and the issues of integrating wind turbines into power systems.

Keywords: power electronics, renewable energy, smart grid, green energy, power technology

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Authors: Rama Debbarma

Abstract:

The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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