Search results for: collective animal behavior algorithm

Authors: Salim Al Jadidi, Shian Gao, Shivananda Moolya

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Computational Fluid Dynamic (CFD) technique coupled with Sub-Grid-Scale (SGS) model is used to study the flow behavior of heavy oil-water-air flow in a horizontal pipe by adapting ANSYS Fluent CFD software. The technique suitable for the transport of water-lubricated heavy viscous oil in a horizontal pipe is the Core Annular flow (CAF) technique. The present study focuses on the numerical study of CAF adapting Large Eddy Simulations (LES). The basic objective of the present study is to gain a basic knowledge of the flow behavior of heavy oil using turbulent CAF through a conventional horizontal pipe. This work also focuses on the success and applicability of LES. The simulation of heavy oil-water-air three-phase flow and two-phase flow of heavy oil–water in a conventional horizontal pipe is performed using ANSYS Fluent 16.2 software. The influence of three-phase heavy oil-water air flow in a selected pipe is affected by gravity. It is also observed from the result that the air phase and the variation in the temperature impact the behavior of the annular stream and pressure drop. Some results obtained during the study are validated with the results gained from part of the literature experiments and simulations, and the results show reasonably good agreement between the studies.

Keywords: computational fluid dynamics, gravity, heavy viscous oil, three-phase flow

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

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The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Mohammad Hadi Jalali, Behrooz Shahriari, Mostafa Ghayour, Saeed Ziaei-Rad, Shahram Yousefi

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Most flexible rotors can be considered as beam-like structures. In many cases, rotors are modeled as one-dimensional bodies, made basically of beam-like shafts with rigid bodies attached to them. This approach is typical of rotor dynamics, both analytical and numerical, and several rotor dynamic codes, based on the finite element method, follow this trend. In this paper, a finite element model based on Timoshenko beam elements is utilized to analyze the lateral dynamic behavior of a certain rotor-bearing system in operating conditions.

Keywords: finite element method, Timoshenko beam elements, operational deflection shape, unbalance response

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Authors: Taha Zakaraia Abdel Wahid

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The behavior of the unsteady non-equilibrium distribution function for a dilute gas under the effect of non-linear thermal radiation field is presented. For the best of our knowledge this is done for the first time at all. The distinction and comparisons between the unsteady perturbed and the unsteady equilibrium velocity distribution functions are illustrated. The equilibrium time for the dilute gas is determined for the first time. The non-equilibrium thermodynamic properties of the system (gas+the heated plate) are investigated. The results are applied to the Argon gas, for various values of radiation field intensity. 3D-Graphics illustrating the calculated variables are drawn to predict their behavior. The results are discussed.

Keywords: dilute gas, radiation field, exact solutions, travelling wave method, unsteady BGK model, irreversible thermodynamics, unsteady non-equilibrium distribution functions

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Authors: Lawrence Gumbe

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Kenya Vision 2030 is the country's programme for transformation covering the period 2008 to 2030. Its objective is to help transform Kenya into a newly industrializing, middle-income, exceeding US$10000, country providing a high quality of life to all its citizens by 2030, in a clean and secure environment. Increased agricultural and production and productivity is crucial for the realization of Vision 2030. Mechanization of agriculture in order to achieve greater yields is the only way to achieve these objectives. There are contending groups and views on the strategy for agricultural mechanization. The first group are those who oppose the widespread adoption of advanced technologies (mostly internal combustion engines and tractors) in agricultural mechanization as entirely inappropriate in most situations in developing countries. This group argues that mechanically powered -agricultural mechanization often leads to displacement of labour and hence increased unemployment, and this results in a host of other socio-economic problems, amongst them, rural-urban migration, inequitable distribution of wealth and in many cases an increase in absolute poverty, balance of payments due to the need to import machinery, fuel and sometimes technical assistance to manage them. The second group comprises of those who view the use of the improved hand tools and animal powered technology as transitional step between the most rudimentary step in technological development (characterized by entire reliance on human muscle power) and the advanced technologies (characterized 'by reliance on tractors and other machinery). The third group comprises those who regard these intermediate technologies (ie. improved hand tools and draught animal technology in agriculture) as a ‘delaying’ tactic and they advocate the use of mechanical technologies as-the most appropriate. This group argues that alternatives to the mechanical technologies do not just exist as a practical matter, or, if they are available, they are inefficient and they cannot be compared to the mechanical technologies in terms of economics and productivity. The fourth group advocates a compromise between groups two and third above. This group views the improved hand tools and draught animal technology as more of an 18th century technology and the modem tractor and combine harvester as too advanced for developing countries. This group has been busy designing an ‘intermediate’, ‘appropriate’, ‘mini’, ‘micro’ tractor for use by farmers in developing countries. This paper analyses and concludes on the different agricultural mechanization strategies available to Kenya and other third world countries

Keywords: agriculture, mechanazation, transformation, industrialization

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Authors: Hyun-Ji Choi

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This paper aims to examine the meaning of ‘state’ as a monopoly of violence, in regard with South Korean democratic transition. Since institutional democratization in 1987, it is conventionally known that governmental authority has exercised its power through law and police force, rather than inclusive or private violence. In other words, 1987 pro-democracy movement has been a critical juncture for a step towards democratic consolidation. However, state coercion may continually be exerted despite institutional specification by law in South Korean context. Explicit case would be amendment of ‘the Law on Assembly and Demonstration’ which determines citizens’ right to take collective action mostly against government actions. This paper investigates amendment process of the law along with social reality since 1987 until 2015 to see how effectively institutionalization has progressed.

Keywords: democratic transition, historical institutionalism, state coercion, the law on Assembly and Demonstration

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Authors: Kumaresh Selvakumar, Man Young Kim

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Wet scrubbers have found widespread use in cleaning contaminated gas streams because of their ability to remove particulates and based on the applications of scrubbing of marine engine exhaust gases by spraying sea-water. In order to examine the flow characteristics inside the scrubber, the model is designated with flow properties of hot air and water sprayer. The flow dynamics of evaporation of hot air by the injection of water droplets is the key factor considered in this paper. The flow behavior inside the scrubber was investigated from the previous works and to sum up the evaporation rate with respect to the concentration of water droplets are predicted to bring out the competent modelling. The numerical analysis using CFD facilitates in understanding the problem better and empathies the behavior of the model over its entire operating envelope.

Keywords: concentration of water droplets, evaporation rate, scrubber, water sprayer

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Authors: George D. Hatzigeorgiou, Nikos G. Pnevmatikos

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This study examines the inelastic behavior of adjacent planar reinforced concrete (R.C.) frames subjected to strong ground motions. The investigation focuses on the effects of vertical ground motion on the seismic pounding. The examined structures are modeled and analyzed by RUAUMOKO dynamic nonlinear analysis program using reliable hysteretic models for both structural members and contact elements. It is found that the vertical ground motion mildly affects the seismic response of adjacent buildings subjected to structural pounding and, for this reason, it can be ignored from the displacement and interstorey drifts assessment. However, the structural damage is moderately affected by the vertical component of earthquakes.

Keywords: nonlinear seismic behavior, reinforced concrete structures, structural pounding, vertical ground motions

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Authors: Hassane Ousalem, Hideki Kimura, Akitoshi Hamada, Masuda Hiroyuki

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To provide tall unreinforced brick masonry walls of a century-old existing building with sufficient resistance against earthquake loading actions, additional reinforced concrete columns were integrated into the building at some designated locations and jointed to the existing masonry walls through dowel shear steel bars, resulting in composite structural elements. As conditions at the interface between the existing masonry and newly added reinforced concrete parts were not well grasped and the behavior of such composite elements would be complex, the experimental investigation was carried out. Three relatively large specimens were tested to investigate the overall behavior of brick masonry-reinforced concrete composite elements under lateral cyclic loadings. Confining the brick walls on only one side or on two opposite sides, as well as providing different amounts of dowel shear steel bars at the interface were the main parameters of the investigation. Test results showed that such strengthening provide a good seismic performance even at very large lateral drifts and the investigated amount of shear dowel lead to a good performance level that would result in a considerable cost reduction of the strengthening.

Keywords: unreinforced masonry, reinforced concrete, composite column, seismic strengthening, structural testing

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Authors: Giovanni Incerti

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In this paper the dynamic behavior of a synchronous belt drive during start-up is analyzed and discussed. Besides considering the belt elasticity, the mathematical model here proposed also takes into consideration the electrical behaviour of the DC motor. The solution of the motion equations is obtained by means of the modal analysis in state space, which allows to obtain the decoupling of all equations of the mathematical model without introducing the hypothesis of proportional damping. The mathematical model of the transmission and the solution algorithms have been implemented within a computing software that allows the user to simulate the dynamics of the system and to evaluate the effects due to the elasticity of the belt branches and to the electromagnetic behavior of the DC motor. In order to show the details of the calculation procedure, the paper presents a case study developed with the aid of the abovementioned software.

Keywords: belt drive, vibrations, startup, DC motor

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Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad

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Introduction: The effectiveness of Transtheoretical Model constructs on dietary behavior change has been subject to questions by some studies. The objective of this study was to determine the relationship between self–efficacy and decisional balance as mediator variables and transfer obese and overweight women among the stages of behavior change of calorie balanced dietary intake. Method: In this cross-sectional study, 448 obese and overweight 20-44 years old women were selected from three health centers in Yasuj, a city in south west of Iran. Anthropometric data were measured using standard techniques. Demographic, stages of change, self-efficacy and decisional balance data were collected by questionnaires and analyzed using One–Way ANOVA and Generalized Linear Models tests. Results: Demographic and anthropometric variables were not different significantly in different stages of change related to calorie intake except the pre-high school level of education (P=.047, OR=502, 95% CI= .255 ~ .990). Mean scores of Self-efficacy ( F(4.425)= 27.09, P= .000), decisional balance (F(4.394), P= .004), and pros (F(4.430)=5.33, P=000) were different significantly in five stages of change. However, the cons did not show a significant change in this regard (F(4.400)=1.83, P=.123). Discussion: Women movement through the stages of changes for calorie intake behavior can be predicted by self efficacy, decisional balance and pros.

Keywords: transtheoretical model, stages of change, self efficacy, decisional balance, calorie intake, women

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Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Ilzira A. Minigalieva, Tatiana V. Bushueva, Eleonore Frohlich, Vladimir Panov, Ekaterina Shishkina, Boris A. Katsnelson

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Background: The overwhelming majority of the experimental studies in the field of metal nanotoxicology have been performed on cultures of established cell lines, with very few researchers focusing on animal experiments, while a juxtaposition of conclusions inferred from these two types of research is blatantly lacking. The least studied aspect of this problem relates to characterizing and predicting the combined toxicity of metallic nanoparticles. Methods: Comparative and combined toxic effects of purposefully prepared spherical NiO and Mn₃O₄ nanoparticles (mean diameters 16.7 ± 8.2 nm and 18.4 ± 5.4 nm respectively) were estimated on cultures of human cell lines: MRC-5 fibroblasts, THP-1 monocytes, SY-SY5Y neuroblastoma cells, as well as on the latter two lines differentiated to macrophages and neurons, respectively. The combined cytotoxicity was mathematically modeled using the response surface methodology. Results: The comparative assessment of the studied NPs unspecific toxicity previously obtained in vivo was satisfactorily reproduced by the present in vitro tests. However, with respect to manganese-specific brain damage which had been demonstrated by us in animal experiment with the same NPs, the testing on neuronall cell culture showed only a certain enhancing effect of Mn₃O₄-NPs on the toxic action of NiO-NPs, while the role of the latter prevailed. Conclusion: From the point of view of the preventive toxicology, the experimental modeling of metallic NPs combined toxicity on cell cultures can give non-reliable predictions of the in vivo action’s effects.

Keywords: manganese oxide, nickel oxide, nanoparticles, in vitro toxicity

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Authors: Alvaro Jose Cordova, Hsuan Teh Hu

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The use of concrete masonry constructions in developing countries has become very frequent, especially for domestic purpose. Most of them with asymmetric wall configurations in plan resulting in significant torsional actions when subjected to seismic loads. The study consisted on the finding of a material model for hollow unreinforced concrete masonry and a validation with experimental data found in literature. Numerical simulations were performed to 20 buildings with variations in wall distributions and heights. Results were analyzed by inspection and with a non-linear static method. The findings revealed that eccentricities as well as structure rigidities have a strong influence on the overall response of concrete masonry buildings. In addition, slab rotations depicted more accurate information about the torsional behavior than maximum versus average displacement ratios. The failure modes in low buildings were characterized by high tensile strains in the first floor. Whereas in tall buildings these strains were lowered significantly by higher compression stresses due to a higher self-weight. These tall buildings developed multiple plastic hinges along the height. Finally, the non-linear static analysis exposed a brittle response for all masonry assemblies. This type of behavior is undesired in any construction and the need for a material model for reinforced masonry is pointed out.

Keywords: concrete damaged plasticity, concrete masonry, macro-modeling, nonlinear static analysis, torsional capacity

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Authors: Mayurachat Kanyamee, Srisuda Rassameepong, Narunest Chulakarn

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This experimental pretest-posttest control group design aimed to examine the effects of a family-based intervention on increasing fruit and vegetable intake and reduce fat and sugar intake and nutritional status among school-age children. Children were randomized to experimental 68 children and control 68 children. The experimental group received the intervention based on Social Cognitive Theory. The control group received the school’s usual educational program regarding healthy eating behavior. Data were collected via three questionnaires including: demographic characteristics; fruit and vegetable intake; and fat and sugar intake at baseline, sixteen weeks after baseline. Analysis of the data included the use of descriptive statistic and independent t-test. Results revealed the significant differences between the experimental and control group, regarding: fruit and vegetable intake, fat and sugar intake and nutritional status at sixteenth week after baseline. The findings suggest a family-based intervention, based on SCT, appears to be effective to improve eating behavior, and nutritional status of school -age children. So, the intervention can be applied to improve eating behavior among other groups of children.

Keywords: family-based intervention, children, unhealthy food, food safety

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Authors: Laurentius J. M. Rumokoy, Jimmy Posangi, Wisje Lusia Toar, Julio Lopez Aban

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The threat of pathogen infection agents to the neonates is a major health problem to the new born life livestock. Neonate losses became an important case in the world as well as in Indonesia. This condition can be triggered by an infection with nematode in conjunction with a failure of immunoglobulin passive transfer. The study was conducted to evaluate the role of the curcuma combined with IgG colostrum on the development of parasites in the gut of CD1 mice. Animal experiments were divided in four groups (G) based on the treatment: G1 (infection only); G2 (curcuma+infection), G3 (IgG + infection) and G4 (curcuma+IgG+infection). The parameters measured were EPG (eggs per gram) and female in the intestine. The results obtained showed that the treatment has no a significant influence on the number of eggs per gram of feces in the group infected compared to the control group without receiving IgG nor curcuma. However, the EGP response tended to decrease at day 6 in G3 and G4 with a minimum number at zero eggs. This performant showed that the immunoglobulin-G and curcuma substances could slightly decreased the number of eggs in animal infected with Strongyloides. The results obtained showed also that the treatment has no significant difference (P > 0.05) on female larva in the gut of MCD1 experimental. In other side, we found that the best performance to inhibit the female quantity in the gut was the treatment with IgG and infection of parasite in G3. In this treatment, the minimum number was five female only in the gut. The results described IgG response was better than the curcuma single use in reducing the female parasite in the gut. This positive response of IgG compared to other controls group was associated with the function of colostrum antibodies.

Keywords: parasites, livestock, curcuma, colostrums

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Authors: A. Bere, H. G. Sithuba, K. Kyei, C. Sigauke

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We employ a discrete logit survival model to investigate the risk factors for early alcohol intake among students at two tertiary institutions in Thohoyandou, South Africa. Data were collected from a sample of 744 students using a self-administered questionnaire. Significant covariates were arrived at through a regularization algorithm implemented using the glmmLasso package. The tuning parameter was determined using a five-fold cross-validation algorithm. The baseline hazard was modelled as a smooth function of time through the use of spline functions. The results show that the hazard of initial alcohol intake peaks at the age of about 16 years and that at any given time, being of a male gender, prior use of other drugs, having drinking peers, having experienced negative life events and physical abuse are associated with a higher risk of alcohol intake debut.

Keywords: cross-validation, discrete hazard model, LASSO, smooth baseline hazard

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

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The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

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A blind source separation method is proposed; in this method we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Aboozar Aghaei

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In the present work, the dissimilar Monel400 and SS316 were joined by friction stir welding (FSW). The applied rotating speed was 400 rpm, whereas the traverse speed varied between 50 and 150 mm/min. At a constant rotating speed, the sound welds were obtained at the welding speeds of 50 and 100 mm/min. However, a groove-like defect was formed when the welding speed exceeded 100 mm/min. The mechanical properties of the joints were evaluated using tensile and fatigue tests. The fatigue strength of dissimilar FSWed specimen was higher than that of both Monel400 and SS316. To study the failure behavior of FSWed specimens, the fracture surfaces were analyzed using scanning electron microscope (SEM). The failure analysis indicates that different mechanisms may contribute to the fracture of welds. This was attributed to the dissimilar characteristics of dissimilar materials exhibiting different failure behaviors.

Keywords: mechanical properties, stainless steel, frictions, monel

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Authors: Bello Yusuf Idi

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The Gongola arm of the Upper Banue Trough, Northeastern Nigeria is predominantly covered by the outcrops of Limestone-bearing rocks in form of Sandstone with intercalation of carbonate clay, shale, basaltic, felsphatic and migmatide rocks at subpixel dimension. In this work, subpixel classification algorithm was used to classify the data acquired from landsat 7 Enhance Thematic Mapper (ETM+) satellite system with the aim of producing fractional distribution image for three most economically important solid minerals of the area: Limestone, Basalt and Migmatide. Linear Spectral Unmixing (LSU) algorithm was used to produce fractional distribution image of abundance of the three mineral resources within a 100Km2 portion of the area. The results show that the minerals occur at different proportion all over the area. The fractional map could therefore serve as a guide to the ongoing reconnaissance for the economic potentiality of the formation.

Keywords: linear spectral un-mixing, upper benue trough, gongola arm, geological engineering

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgiana Duarte

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The Chinese version of the Child Behavior Checklist (CBCL) is the one of the Achenbach systems of empirically based assessment (ASEBA) scales, by which behavioral and emotional problems of early adolescents were examined. In order to further understand the robustness of the scale, its reliability has been examined. CBCL consists of 8 problems to measure internalizing, externalizing and social problems. In internalizing problem, there are Anxious, Withdrawn and Somatic Complaints. In this study, as an example, we only examined the anxious aspect which consisted of 13 questions. Cronbach alpha and factor analysis methods were used to examine the reliability of the scale. The result indicated that Cronbach alpha value was above 0.80.

Keywords: anxious/depressed problems, ASEBA, CBCL, Cronbach Alpha, reliability

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Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga

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Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.

Keywords: genetic algorithm, neural networks, word prediction, machine learning

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Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

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In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

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Authors: Saeid Asghari

Abstract:

The growing interest in sustainability and healthy lifestyles has stimulated the development of solutions that promote mindful consumption and healthier choices. One such solution is the use of transparent graded lanes in product packaging, which enables consumers to visually track their product consumption and encourages portion control. However, the extent to which this packaging affects consumer behavior, trust, and loyalty towards a product or brand, as well as the effectiveness of messaging on the graded lanes, remains unclear. The research aims to examine the impact of transparent graded lanes on consumer behavior, trust, and loyalty towards products or brands in the context of the Janbo chain supermarket in Tehran, Iran, focusing on Ketchup and edible oils containers. A representative sample of 720 respondents is selected using quota sampling based on sex, age, and financial status. The study assesses the effect of messaging on the graded lanes in enhancing consumer recall and recognition of the product at the time of purchase, increasing repeat purchases, and fostering long-term relationships with customers. Furthermore, the potential outcomes of using transparent graded lanes, including the promotion of healthy consumption habits and the reduction of food waste, are also considered. The findings and results can inform the development of effective messaging strategies for graded lanes and suggest ways to enhance consumer engagement with product packaging. Moreover, the study's outcomes can contribute to the broader discourse on sustainable consumption and healthy lifestyles, highlighting the potential role of packaging innovations in promoting these values. We used four theories (social cognitive theory, self-perception theory, nudge theory, and marketing and consumer behavior) to examine the effect of these transparent graded lanes on consumer behavior. The conceptual model integrates the use of transparent graded lanes, consumer behavior, trust and loyalty, messaging, and promotion of healthy consumption habits. The study aims to provide insights into how transparent graded lanes can promote mindful consumption, increase consumer recognition and recall of the product, and foster long-term relationships with customers. Findings suggest that the use of transparent graded lanes on Ketchup and edible oils containers can have a positive impact on consumer behavior, trust, and loyalty towards a product or brand, as well as promote mindful consumption and healthier choices. The messaging on the graded lanes is also found to be effective in promoting recall and recognition of the product at the time of purchase and encouraging repeat purchases. However, the impact of transparent graded lanes may be limited by factors such as cultural norms, personal values, and financial status. Broadly speaking, the investigation provides valuable insights into the potential benefits and challenges of using transparent graded lanes in product packaging, as well as effective strategies for promoting healthy consumption habits and building long-term relationships with customers.

Keywords: packaging customer behavior, purchase, brand loyalty, healthy consumption

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

Abstract:

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

Procedia PDF Downloads 397