Search results for: Generalized autoregressive score

Authors: Chrysoula Karathanasi, Senad Karavdic, Angela Odero, Michèle Baumann

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It is not only the economic determinants that impact on life conditions, but maintaining a good level of life satisfaction (LS) may also be an important challenge currently. In Luxembourg, university students receive financial aid from the government. They are then registered at the Centre for Documentation and Information on Higher Education (CEDIES). Luxembourg is built on migration with almost half its population consisting of foreigners. It is upon this basis that our research aims to analyze the associations with mental health factors (health satisfaction, psychological quality of life, worry), perceived financial situation, career attitudes (adaptability, optimism, knowledge, planning) and LS, for non-Luxembourgish and native postgraduate students. Between 2012 and 2013, postgraduates registered at CEDIES were contacted by post and asked to participate in an online survey with either the option of English or French. The study population comprised of 644 respondents. Our statistical analysis excluded: those born abroad who had Luxembourgish citizenship, or those born in Luxembourg who did not have citizenship. Two groups were formed one consisting 147 non-Luxembourgish and the other 284 natives. A single item measured LS (1=not at all satisfied to 10=very satisfied). Bivariate tests, correlations and multiple linear regression models were used in which only significant relationships (p<0.05) were integrated. Among the two groups no differences were found between LS indicators (7.8/10 non-Luxembourgish; 8.0/10 natives) as both were higher than the European indicator of 7.2/10 (for 25-34 years). In the case of non-Luxembourgish students, they were older than natives (29.3 years vs. 26.3 years) perceived their financial situation as more difficult, and a higher percentage of their parents had an education level higher than a Bachelor's degree (father 59.2% vs 44.6% for natives; mother 51.4% vs 33.7% for natives). In addition, the father’s education was related to the LS of postgraduates and the higher was the score, the greater was the contribution to LS. Whereas for native students, when their scores of health satisfaction and career optimism were higher, their LS’ score was higher. For both groups their LS was linked to mental health-related factors, perception of their financial situation, career optimism, adaptability and planning. The higher the psychological quality of life score was, the greater the LS of postgraduates’ was. Good health and positive attitudes related to the job market enhanced their LS indicator.

Keywords: Career attitudes, fathers’ education level, life satisfaction, mental health.

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Authors: Toshihiko Matsuka

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One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.

Keywords: artificial intelligence, category learning, cognitive modeling, radial basis functions.

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Authors: Juan Zhang, Changzhao Li

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In this paper, we introduce a new class of nonsmooth pseudo-invex and nonsmooth quasi-invex functions to non-smooth variational problems. By using these concepts, numbers of necessary and sufficient conditions are established for a nonsmooth variational problem wherein Clarke’s generalized gradient is used. Also, weak, strong and converse duality are established.

Keywords: Variational problem, Nonsmooth pseudo-invex, Nonsmooth quasi-invex, Critical point, Duality

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Authors: Walid A. M. Ghoneim, Hamdy A. Ashour, Asmaa E. Abdo

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In this paper, linear analysis of a Switched Reluctance Generator (SRG) model is applied on the most common configurations (4/2, 6/4 and 8/6) for both conventional short-pitched and fully-pitched designs, in order to determine the optimum stator/rotor pole angles at which the maximum output voltage is generated per unit excitation current. This study is focused on SRG analysis and design as a proposed solution for renewable energy applications, such as wind energy conversion systems. The world’s potential to develop the renewable energy technologies through dedicated scientific researches was the motive behind this study due to its positive impact on economy and environment. In addition, the problem of rare earth metals (Permanent magnet) caused by mining limitations, banned export by top producers and environment restrictions leads to the unavailability of materials used for rotating machines manufacturing. This challenge gave authors the opportunity to study, analyze and determine the optimum design of the SRG that has the benefit to be free from permanent magnets, rotor windings, with flexible control system and compatible with any application that requires variable-speed operation. In addition, SRG has been proved to be very efficient and reliable in both low-speed or high-speed applications. Linear analysis was performed using MATLAB simulations based on the (Modified generalized matrix approach) of Switched Reluctance Machine (SRM). About 90 different pole angles combinations and excitation patterns were simulated through this study, and the optimum output results for each case were recorded and presented in detail. This procedure has been proved to be applicable for any SRG configuration, dimension and excitation pattern. The delivered results of this study provide evidence for using the 4-phase 8/6 fully pitched SRG as the main optimum configuration for the same machine dimensions at the same angular speed.

Keywords: Generalized matrix approach, linear analysis, renewable applications, switched reluctance generator, SRG.

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Authors: Yuki Irie, Shota Ogawa, Hitomi Kosugi, Hiromitsu Shinozaki

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Dropout rates in higher educational institutions pose significant challenges for both students and institutions, with poor mental health (MH) emerging as a key risk factor. Healthcare college students, including medical students, are particularly vulnerable to MH issues due to the demanding academic schedules they face. Poor mental health (MH) would be considered as a key risk factor for dropout from higher educational institutions that pose significant challenges for both students and institutions. And, inadequate food access (FA) has been related to poor MH. Given that targeted students may experience multiple risk factors for poor MH and vulnerable FA, the study aims to clarify the relationship between MH and FA to enhance student well-being. A cross-sectional design was used to explore the association between MH status and FA among 421 students (147 male, 274 female). Participants completed two questionnaires assessing MH and FA during winter 2022. The mean MH score was 6.7 ± 4.6, with higher scores indicating worse MH (max. score 27). While year-round FA showed no significant association with MH, FA during winter was significantly associated with MH (p = 0.01). Although car ownership did not directly impact MH, it was significantly associated with FA (p < 0.01), thus indirectly influencing MH. Our findings underscore the importance of FA in promoting MH, particularly during winter. Adopting a lifestyle that facilitates easier FA may be beneficial for MH, given its indirect association with MH outcomes. These insights emphasize the significance of addressing FA-related challenges to enhance student’s mental well-being.

Keywords: Mental health, food access, co-medical students, lifestyle.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: Mohsen Zahraei

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In this paper, the notion of rank−k numerical range of rectangular complex matrix polynomials are introduced. Some algebraic and geometrical properties are investigated. Moreover, for Є > 0, the notion of Birkhoff-James approximate orthogonality sets for Є−higher rank numerical ranges of rectangular matrix polynomials is also introduced and studied. The proposed definitions yield a natural generalization of the standard higher rank numerical ranges.

Keywords: Rank−k numerical range, isometry, numerical range, rectangular matrix polynomials.

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Authors: M.Ghotbi, M.Ghotbi, Gh. Azari Takami

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In this study Vitaton (an organic supplement which contains fermentative β-carotene) and synthetic astaxanthin (CAROPHYLL® Pink) were evaluated as pro-growth factors in Rainbow trout diet. An 8 week feeding trial was conducted to determine the effects of Vitaton versus astaxanthin on rearing factors, survival rate and visual flesh color of Rainbow trout (Oncorhnchynchus mykiss) with initial weight of 196±5. Four practical diets were formulated to contain 50 and 80 (ppm) of β- carotene and astaxanthin and also a control diet was prepared without any pigment. Each diet was fed to triplicate groups of fish rearing in fresh water. Fish were fed twice daily. The water temperature fluctuated from 12 to 15 (C˚) and also dissolved oxygen content was between 7 to 7.5 (mg/lit) during the experimental period. At the end of the experiment, growth and food utilization parameters and survival rate were unaffected by dietary treatments (p>0.05). Also, there was no significant difference between carcass yield within treatments (p>0.05). No significant difference recognized between visual flesh color (SalmoFan score) of fish fed Vitaton-containing diets. On the contrary, feeding on diets containing 50 and 80 (ppm) of astaxanthin, increased SalmoFan score (flesh astaxanthin concentration) from <20 (<1 mg/kg) to 23.33 (2.03 mg/kg) and 27.67 (5.74 mg/kg), respectively. Ultimately, a significant difference was seen between flesh carotenoid concentrations of fish feeding on astaxanthin containing treatments and control treatment (P<0.05). It should be mentioned that just raw fillet color of fish belonged to 80 (ppm) of astaxanthin treatment was seen to be close to color targets (SalmoFan scores) adopted for harvest-size fish.

Keywords: Astaxanthin, Flesh color, Rainbow trout, Vitaton, β- carotene,

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Authors: Xu Jianguo

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In this paper, a generalized self-consistent scheme, or “three phase model", is used to set up a micro-mechanics model for rough surface contact with randomly distributed asperities. The dimensionless average real pressure p is obtained as function of the ratio of the real contact area to the apparent contact area, 0 A / A r . Both elastic and plastic materials are considered, and the influence of the plasticity of material on p is discussed. Both two-dimensional and three-dimensional rough surface contact problems are considered.

Keywords: Contact mechanics, plastic deformation, self-consistent scheme.

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Authors: Amal E. Shehata, Manal E. Fareed

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Osteoarthritis (OA) is the most prevalent and far common debilitating form of arthritis which can be defined as a degenerative condition affecting synovial joint. Patients suffering from osteoarthritis often complain of dull ache pain on movement. Physical agents can fight the painful process when correctly indicated and used such as heat or cold therapy Aim. This study was carried out to: Compare the effect of cold, warm and contrast therapy on controlling knee osteoarthritis associated problems. Setting: The study was carried out in orthopedic outpatient clinics of Menoufia University and teaching Hospitals, Egypt. Sample: A convenient sample of 60 adult patients with unilateral knee osteoarthritis. Tools: three tools were utilized to collect the data. Tool I : An interviewing questionnaire. It comprised of three parts covering  sociodemographic data, medical data and adverse effects of the treatment protocol. Tool II : Knee Injury and Osteoarthritis Outcome Score (KOOS) It consists of five main parts. Tool II1 : 0-10 Numeric pain rating scale. Results: reveled that the total knee symptoms score was decreased from moderate symptoms pre intervention to mild symptoms after warm and contrast method of therapy, but the contrast therapy had significant effect in reducing the knee symptoms and pain than the other symptoms. Conclusions: all of the three methods of therapy resulted in improvement in all knee symptoms and pain but the most appropriate protocol of treatment to relive symptoms and pain was contrast therapy.

Keywords: Knee Osteoarthritis, Cold, Warm and Contrast Therapy.

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

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The research explored the effect of morphemic analysis awareness on ESL secondary school students’ vocabulary acquisition. The quasi-experimental study was conducted with 100 ESL secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morph-Analysis Test and Morph-Vocabulary Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morph- Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the findings of the research are discussed in two main areas. First, individual instructions of two types of morphemic awareness have contributed significant results on inflectional and derivational awareness among the ESL secondary school students. Nevertheless, derivational morphology achieved a significant but relatively smaller amount of effect on secondary school students’ morphological awareness compared to inflectional morphology in this research. Second finding showed that the awareness of inflectional and derivational morphology was found significantly related to vocabulary achievement of ESL secondary school students. Nevertheless, inflectional morphemic awareness had higher significant effect on ESL secondary school students’ vocabulary acquisition. Despite these findings, the study implies that morphemic analysis awareness can serve as an alternative strategy for ESL secondary school students in acquiring English vocabulary.

Keywords: Morphemic analysis, vocabulary, ESL students.

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Authors: Shahlan Surat, Saemah Rahman, Saadiah Kummin

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When teachers reflect and evaluate whether their teaching methods actually have an impact on students’ learning, they will adjust their practices accordingly. This inevitably improves their students’ learning and performance. The approach in meta-teaching can invigorate and create a passion for teaching. It thus helps to increase the commitment and love for the teaching profession. This study was conducted to determine the level of metacognitive thinking of teachers in the process of teaching and learning in the classroom. Metacognitive thinking teachers include the use of metacognitive knowledge which consists of different types of knowledge: declarative, procedural and conditional. The ability of the teachers to plan, monitor and evaluate the teaching process can also be determined. This study was conducted on 377 graduate teachers in Klang Valley, Malaysia. The stratified sampling method was selected for the purpose of this study. The metacognitive teaching inventory consisting of 24 items is called InKePMG (Teacher Indicators of Effectiveness Meta-Teaching). The results showed the level of mean is high for two components of metacognitive knowledge; declarative knowledge (mean = 4.16) and conditional (mean = 4.11) whereas, the mean of procedural knowledge is 4.00 (moderately high). Similarly, the level of knowledge in monitoring (mean = 4.11), evaluating (mean = 4.00) which indicate high score and planning (mean = 4.00) are moderately high score among teachers. In conclusion, this study shows that the planning and procedural knowledge is an important element in improving the quality of teachers teaching in the classroom. Thus, the researcher recommended that further studies should focus on training programs for teachers on metacognitive skills and also on developing creative thinking among teachers.

Keywords: Metacognitive thinking skills, procedural knowledge, conditional knowledge, declarative knowledge, meta-teaching and regulation of cognitive.

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Authors: G.Mehdiyeva, M.Imanova, V.Ibrahimov

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Beginning from the creator of integro-differential equations Volterra, many scientists have investigated these equations. Classic method for solving integro-differential equations is the quadratures method that is successfully applied up today. Unlike these methods, Makroglou applied hybrid methods that are modified and generalized in this paper and applied to the numerical solution of Volterra integro-differential equations. The way for defining the coefficients of the suggested method is also given.

Keywords: Integro-differential equations, initial value problem, hybrid methods, predictor-corrector method

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Authors: Vladyslav Povoroznyuk, Larysa Martynyuk, Iryna Syzonenko, Liliya Martynyuk

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Osteoporosis is one of the important problems in postmenopausal women due to an increased risk of sudden and unexpected fractures. This study is aimed to determine the connection between bone mineral density (BMD) and trabecular bone score (TBS) in Ukrainian women suffering from metabolic syndrome. Participating in the study, 566 menopausal women aged 50-79 year-old were examined and divided into two groups: Group A included 336 women with no obesity (BMI ≤ 29.9 kg/m²), and Group B – 230 women with metabolic syndrome (diagnosis according to IDF criteria, 2005). Dual-energy X-ray absorptiometry was used for measuring of lumbar spine (L1-L4), femoral neck, total body and forearm BMD and bone quality indexes (last according to Med-Imaps installation). Data were analyzed using Statistical Package 6.0. A significant increase of lumbar spine (L1-L4), femoral neck, total body and ultradistal radius BMD was found in women with metabolic syndrome compared to those without obesity (p < 0.001) both in their totality and in groups of 50-59 years, 60-69 years, and 70-79 years. TBS was significantly higher in non-obese women compared to metabolic syndrome patients of 50-59 years and in the general sample (p < 0.05). Analysis showed significant positive correlation between body mass index (BMI) and BMD at all levels. Significant negative correlation between BMI and TBS (L1-L4) was established. Despite the fact that BMD indexes were significantly higher in women with metabolic syndrome, the frequency of vertebral and non-vertebral fractures did not differ significantly in the groups of patients.

Keywords: Bone mineral density, trabecular bone score, metabolic syndrome, fracture.

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Authors: Jitendra Jain, Cassandra Hidajat, Hansraj Riteesh Bookun

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Graft patency underpins long-term prognosis after coronary artery bypass grafting surgery (CABG). The benefits of the combined use of only the left internal mammary artery and radial artery, referred to as total arterial revascularisation (TAR), on long-term clinical outcomes and quality of life are relatively unknown. The aim of this study was to identify whether there were differences in long term clinical outcomes between recipients of TAR compared to a cohort of mostly arterial revascularization involving the left internal mammary, at least one radial artery and at least one saphenous vein graft. A retrospective analysis was performed on all patients who underwent TAR or were re-vascularized with supplementary saphenous vein graft from February 1996 to December 2004. Telephone surveys were conducted to obtain clinical outcome parameters including major adverse cardiac and cerebrovascular events (MACCE) and Short Form (SF-36v2) Health Survey responses. A total of 176 patients were successfully contacted to obtain postop follow up results. The mean follow-up length from time of surgery in our study was TAR 12.4±1.8 years and conventional 12.6±2.1. PCS score was TAR 45.9±8.8 vs LIMA/Rad/ SVG 44.9±9.2 (p=0.468) and MCS score was TAR 52.0±8.9 vs LIMA/Rad/SVG 52.5±9.3 (p=0.723). There were no significant differences between groups for NYHA class 3+ TAR 9.4% vs. LIMA/Rad/SVG 6.6%; or CCS 3+ TAR 2.35% vs. LIMA/Rad/SVG 0%.

Keywords: CABG, MACCEs, quality of life, total arterial revascularization.

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Authors: Hicham Benamirouche, Oum Elkheir Moussi

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The purpose of the study is to examine the dynamics of Algeria’s natural gas exports through the Autoregressive Distributed Lag (ARDL) bounds testing approach with break points. The analysis was carried out for the period from 1967 to 2015. Based on imperfect substitution specification, the ARDL approach reveals a long-run equilibrium relationship between Algeria’s Natural gas exports and their determinant factors (Algeria’s gas reserves, Domestic gas consumption, Europe’s GDP per capita, relative prices, the European gas production and the market share of competitors). All the long-run elasticities estimated are statistically significant with a large impact of domestic factors, which constitute the supply constraints. In short term, the elasticities are statistically significant, and almost comparable to those of the long term. Furthermore, the speed of adjustment towards long-run equilibrium is less than one year because of the little flexibility of the long term export contracts. Two break points have been estimated when we employ the domestic gas consumption as a break variable; 1984 and 2010, which reflect the arbitration policy between the domestic gas market and gas exports.

Keywords: Natural gas exports, elasticity, ARDL bounds testing, break points, Algeria.

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Authors: Jai Raj, Jito Vanualailai, Bibhya Sharma, Shonal Singh

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This paper proposes a solution to the motion planning and control problem of car-like mobile robots which is required to move safely to a designated target in a priori known workspace cluttered with swarm of boids exhibiting collective emergent behaviors. A generalized algorithm for target convergence and swarm avoidance is proposed that will work for any number of swarms. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws are demonstrated via computer simulations of an emergent behavior.

Keywords: Swarm, practical stability, motion planning, emergent.

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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Authors: Okwan Frank

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Maternal health outcome is one of the major population development challenges in Sub-Saharan Africa. The region has the highest maternal mortality ratio, despite the progressive economic growth in the region during the global economic crisis. It has been hypothesized that increase in economic growth will reduce the level of maternal mortality. The purpose of this study is to investigate the existence of the negative relationship between health outcome proxy by maternal mortality ratio and economic growth in Sub-Saharan Africa. The study used the Pooled Mean Group estimator of ARDL Autoregressive Distributed Lag (ARDL) and the Kao test for cointegration to examine the short-run and long-run relationship between maternal mortality and economic growth. The results of the cointegration test showed the existence of a long-run relationship between the variables considered for the study. The long-run result of the Pooled Mean group estimates confirmed the hypothesis of an inverse relationship between maternal health outcome proxy by maternal mortality ratio and economic growth proxy by Gross Domestic Product (GDP) per capita. Thus increasing economic growth by investing in the health care systems to reduce pregnancy and childbirth complications will help reduce maternal mortality in the sub-region.

Keywords: Economic growth, maternal mortality, pool mean group, Sub-Saharan Africa.

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Authors: Lv Yuhua

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In this paper, by constructing a special cone and using fixed point theorem and fixed point index theorem of cone, we get the existence of positive solution for a class of singular eigenvalue value problems with p-Laplace operator, which improved and generalized the result of related paper.

Keywords: Cone, fixed point index, eigenvalue problem, p-Laplace operator, positive solutions.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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In this paper, some new nonlinear generalized Gronwall-Bellman-Type integral inequalities with mixed time delays are established. These inequalities can be used as handy tools to research stability problems of delayed differential and integral dynamic systems. As applications, based on these new established inequalities, some p-stable results of a integro-differential equation are also given. Two numerical examples are presented to illustrate the validity of the main results.

Keywords: Gronwall-Bellman-Type integral inequalities, integrodifferential equation, p-exponentially stable, mixed delays.

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Authors: Li Xiguang

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In this paper, by constructing a special operator and using fixed point index theorem of cone, we get the sufficient conditions for symmetric positive solution of a class of nonlinear singular boundary value problems with p-Laplace operator, which improved and generalized the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation, p-Laplace operator, symmetric solutions.

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Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO₂ emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: Co-integration, Elasticity, Granger causality, Malaysia, Residential electricity consumption.

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Authors: M. Moeinaddini, Z. Asadi-Shekari, Z. Sultan, M. Zaly Shah

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Happiness can be related to everything that can provide a feeling of satisfaction or pleasure. This study tries to consider the relationship between land use factors and feeling of happiness at the neighbourhood level. Land use variables (beautiful and attractive neighbourhood design, availability and quality of shopping centres, sufficient recreational spaces and facilities, and sufficient daily service centres) are used as independent variables and the happiness score is used as the dependent variable in this study. In addition to the land use variables, socio-economic factors (gender, race, marital status, employment status, education, and income) are also considered as independent variables. This study uses the Oxford happiness questionnaire to estimate happiness score of more than 300 people living in six neighbourhoods. The neighbourhoods are selected randomly from Skudai neighbourhoods in Johor, Malaysia. The land use data were obtained by adding related questions to the Oxford happiness questionnaire. The strength of the relationship in this study is found using generalised linear modelling (GLM). The findings of this research indicate that increase in happiness feeling is correlated with an increasing income, more beautiful and attractive neighbourhood design, sufficient shopping centres, recreational spaces, and daily service centres. The results show that all land use factors in this study have significant relationship with happiness but only income, among socio-economic factors, can affect happiness significantly. Therefore, land use factors can affect happiness in Skudai more than socio-economic factors.

Keywords: Neighbourhood land use, neighbourhood design, happiness, socio-economic factors, generalised linear modelling.

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Authors: Miin-Shen Yang, Yee-Shan Pan

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Although there have been many researches in cluster analysis to consider on feature weights, little effort is made on sample weights. Recently, Yu et al. (2011) considered a probability distribution over a data set to represent its sample weights and then proposed sample-weighted clustering algorithms. In this paper, we give a sample-weighted version of generalized fuzzy clustering regularization (GFCR), called the sample-weighted GFCR (SW-GFCR). Some experiments are considered. These experimental results and comparisons demonstrate that the proposed SW-GFCR is more effective than the most clustering algorithms.

Keywords: Clustering; fuzzy c-means, fuzzy clustering, sample weights, regularization.

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Authors: Da-Xue Chen, Guang-Hui Liu

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In this paper, we study the oscillation of a class of second-order nonlinear neutral damped variable delay dynamic equations on time scales. By using a generalized Riccati transformation technique, we obtain some sufficient conditions for the oscillation of the equations. The results of this paper improve and extend some known results. We also illustrate our main results with some examples.

Keywords: Oscillation theorem, second-order nonlinear neutral dynamic equation, variable delay, damping, Riccati transformation.

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Authors: Jui-Sheng Lin, Yi-Sung Yang, Meei-Ling Hung, Teh-Lu Liao, Jun-Juh Yan

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The global chaos synchronization for a class of time-delayed power systems is investigated via observer-based approach. By employing the concepts of quadratic stability theory and generalized system model, a new sufficient criterion for constructing an observer is deduced. In contrast to the previous works, this paper proposes a theoretical and systematic design procedure to realize chaos synchronization for master-slave power systems. Finally, an illustrative example is given to show the applicability of the obtained scheme.

Keywords: Chaos, Synchronization, Quadratic stability theory, Observer

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Authors: Dursun Aydın, Bilgin Senel

Abstract:

In this paper, the sum of squares in linear regression is reduced to sum of squares in semi-parametric regression. We indicated that different sums of squares in the linear regression are similar to various deviance statements in semi-parametric regression. In addition to, coefficient of the determination derived in linear regression model is easily generalized to coefficient of the determination of the semi-parametric regression model. Then, it is made an application in order to support the theory of the linear regression and semi-parametric regression. In this way, study is supported with a simulated data example.

Keywords: Semi-parametric regression, Penalized LeastSquares, Residuals, Deviance, Smoothing Spline.

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Authors: Fotis N. Koumboulis, Michael G. Skarpetis, Maria P. Tzamtzi

Abstract:

The problem of robust disturbance rejection (RDR) using a proportional state feedback controller is studied for the case of Left Invertible MIMO generalized state space linear systems with nonlinear uncertain structure. Sufficient conditions for the problem to have a solution are established. The set of all proportional feedback controllers solving the problem subject to these conditions is analytically determined.

Keywords: System theory, uncertain systems, robust control, singular systems.

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