Search results for: statistical estimation problem

Authors: Anano Tenieshvili, Teona Lodia

Abstract:

Social anxiety disorder (SAD) is one of the most common mental health problems not only in adults but also in adolescents. Individuals with SAD exhibit difficulties in interpersonal relationships, understanding emotions, and regulating them as well. For social and emotional adaptation, it is crucial to identify, understand, accept and manage emotions correctly. Researchers actively learn those factors that contribute to the development and maintenance of this condition. Therefore, the main purpose of this study is to acquire knowledge about the association between social anxiety and individual characteristics, such as theory of mind (ToM), verbal irony comprehension, and personal traits. 112 adolescents aged from 12 to 18 were selected for this research. 15 of them are diagnosed with Social anxiety disorder. Statistical analysis was performed on the entire sample, and furthermore, two groups, adolescents with and without social anxiety disorder, were compared separately. Social anxiety and personal traits were assessed by questionnaires. Theory of mind and comprehension of verbal irony were measured using tests. Statistical analysis indicated a positive relationship between social anxiety and comprehension of ironic criticism. Moreover, social anxiety was significantly positively correlated with neuroticism and isolation tendency, whereas it was negatively related to extraversion and frustration tolerance. On top of that, statistical analysis revealed a positive relationship between ToM and verbal irony comprehension. However, the relationship between social anxiety and ToM was not statistically significant. In conclusion, the current research expands knowledge about social anxiety and supports the results of some previous studies.

Keywords: personal traits, social anxiety, theory of mind, verbal irony comprehension

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Authors: Anano Tenieshvili, Teona Lodia

Abstract:

Social anxiety disorder (SAD) is one of the most common mental health problems not only in adults but also in adolescents. Individuals with SAD exhibit difficulties in interpersonal relationships, understanding emotions and regulating them as well. For social and emotional adaptation, it is crucial to identify, understand, accept and manage emotions correctly. Researchers actively learn those factors that contribute to the development and maintenance of this condition. Therefore, the main purpose of this study is to acquire knowledge about the association between social anxiety and individual characteristics, such as the theory of mind (ToM), verbal irony comprehension and personal traits. 112 adolescents aged from 12 to 18 were selected for this research. 15 of them are diagnosed with Social anxiety disorder. Statistical analysis was performed on the entire sample and furthermore, two groups, adolescents with and without a social anxiety disorder, were compared separately. Social anxiety and personal traits were assessed by questionnaires. Theory of mind and comprehension of verbal irony was measured using tests. Statistical analysis indicated a positive relationship between social anxiety and comprehension of ironic criticism. Moreover, social anxiety was significantly positively correlated with neuroticism and isolation tendency, whereas it was negatively related to extraversion and frustration tolerance. On top of that, statistical analysis revealed a positive relationship between ToM and verbal irony comprehension. However, the relationship between social anxiety and ToM was not statistically significant. In conclusion, the current research expands knowledge about social anxiety and supports the results of some previous studies.

Keywords: personal traits, social anxiety, theory of mind, verbal irony comprehension

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Authors: Maryam Abata, Moulhime El Bekkali, Said Mazer, Catherine Algani, Mahmoud Mehdi

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One major problem of most electronic systems operating in the millimeter wave band is the signal generation with a high purity and a stable carrier frequency. This problem is overcome by using the combination of a signal with a low frequency local oscillator (LO) and several stages of frequency multipliers. The use of these frequency multipliers to create millimeter-wave signals is an attractive alternative to direct generation signal. Therefore, the isolation problem of the local oscillator from the other stages is always present, which leads to have various mechanisms that can disturb the oscillator performance, thus a buffer amplifier is often included in oscillator outputs. In this paper, we present the study and design of a buffer amplifier in the mm-wave band using a 0.15μm pHEMT from UMS foundry. This amplifier will be used as a part of a frequency quadrupler at 60 GHz.

Keywords: Mm-wave band, local oscillator, frequency quadrupler, buffer amplifier

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Salinee Thumronglaohapun

Abstract:

The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: location-allocation problem, stochastic demand, local search, genetic algorithm

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Authors: Hesham Shaalan

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Senior design projects teach students many important skills. One of the major goals is to prepare students to apply effective problem-solving techniques to a problem that represents a real-world situation. This includes the ability to define the problem, compare alternative solutions, identify the best solution, and design the system. This paper describes the design of a shipboard power plant as a senior project in the Marine Engineering program at the U.S. Merchant Marine Academy. The design project was supervised by faculty members who guided a multidisciplinary group of seniors. The research project was sponsored by the Office of Naval Research. Each group of seniors focused on one of the main design aspects of the project, including the electric power system, nuclear power plant, ship hull design, and economics.

Keywords: senior design project, shipboard power system, engineering education, marine engineering

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Abdulkerim Ilgun, Ahmad Javid Zia

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In developing countries, the urban populations are increasing rapidly and with this increment the residential areas are experiencing major problems. Construction of high-rise buildings in confined spaces is one of the most practical solutions for this problem. However, by living in high-rise buildings and sharing common residential areas, residents will face many problems. Irritating sound problem which is known as noise is one of the major problems mentioned above. The second most important problem is the weight of the high-rise buildings which makes the structure more vulnerable to earthquakes. To decrease earthquake loads it’s very important to decrease the weight of the buildings. To solve the problem of noise and keep the building weight at minimum level, experimentally designed soundproof gypsum partition wall which has optimum thickness has been used in high-rise story building and the results have been compared with ordinary brick partition walls. In this compression the effect of weights of soundproof gypsum walls and ordinary brick walls in accordance to structural engineering have been investigated.

Keywords: cellubor, gypsum board, gypsum partition walls, light partition walls, noise, sound

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Authors: Mohand Kessal, Rachid Boucetta, Mourad Tikobaini, Mohammed Zamoum

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Leakage problem of two-component fluids flow is modeled for a transient one-dimensional homogeneous bubbly flow and developed by taking into account the effect of a leak located at the middle point of the pipeline. The corresponding three conservation equations are numerically resolved by an improved characteristic method. The obtained results are explained and commented in terms of physical impact on the flow parameters.

Keywords: fluid transients, pipelines leaks, method of characteristics, leakage problem

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Authors: L. Della Ragione, G. Meccariello

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In recent years the progress of the automobile industry in Italy in the field of reduction of emissions values is very remarkable. Nevertheless, their evaluation and reduction is a key problem, especially in the cities, which account for more than 50% of world population. In this paper we dealt with the problem of describing a quantitative approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars.

Keywords: air pollution, driving cycles, GPS signal, vehicle location

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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Authors: Kari Saarelainen, Marko Jantti

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IT service trending of root causes of service incidents and problems is an important part of proactive problem management and service improvement. Human error related root causes are an important root cause category also in IT service management, although it’s proportion among root causes is smaller than in the other industries. The research problem in this study is: How root causes of incidents related to human errors should be categorized in an ITSM organization to effectively support service improvement. Categorization based on IT service management processes and based on Human Factors Analysis and Classification System (HFACS) taxonomy was studied in a case study. HFACS is widely used in human error root cause categorization across many industries. Combining these two categorization models in a two dimensional matrix was found effective, yet impractical for daily work.

Keywords: IT service management, ITIL, incident, problem, HFACS, swiss cheese model

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Authors: Waratthaya Maneerattana, Piyarat Dornbundit

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The study aimed to develop flipped classroom in Chemistry on ‘acid-base’ for high school students and study efficiency of students on academic achievement and problem-solving skills. The evaluating result from the experts showed that developed flipped classroom was ranked in high score level. The flipped classroom efficiency E1/E2 was higher than the criteria of 70/70. The flipped classroom was used by 24 students in grade 11 in the second semester of the academic year 2016 at Bodindecha (Sing Singhaseni) School. Sampling group was chosen using a purposive sampling approach. The results revealed that academic achievement and problem solving skills of students after studying flipped classroom was significantly higher at .05 level.

Keywords: flipped classroom, acid-base, academic achievement, problem solving skill

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

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In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: multivariate control chart, statistical process control, one-class classification method, non-normal data

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Authors: JungYeon Park, Jooyong Park

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Brainstorming and discussion are widely used around the world as formal techniques of collaborative creative problem solving. This study investigated whether a web-based peer review system would improve collaborative creative problem solving. In order to assess the efficiency of using web-based peer review system before brainstorming and discussion, we conducted a between-group design study for two conditions (a web-based peer review system vs. face-to-face brainstorming only) using two different scenarios. One hundred and twenty participants were divided into teams of four and randomly assigned to one of the four conditions. The participants were given problems for them to solve. The participants in the experimental group first generated ideas independently for 20 minutes and wrote down their ideas. Afterwards, they reviewed the list of ideas of their peers and gave and received feedback for 10 minutes. These activities were performed on-line. The last activity was face-to-face brain-storming and discussion for 30 minutes. In contrast, the control group participated in brainstorming and discussion for 60 minutes. The quantity and the quality of ideas were measured as dependent variables of creative problem solving. Two evaluators rated the quantity and quality of the proposed ideas. Inter-rater agreement rate was good or strong. The results showed that both the average number of unique ideas and the average quality of ideas generated for the experimental condition were significantly higher than those for the control condition in both scenarios. The results of this study support the hypothesis that collaborative creative problem solving is enhanced when individuals write their thoughts individually and review ideas written by peers before face-to-face brainstorming and discussion. The present study provides preliminary evidence that a web-based peer review system can be instrumental in improving creative problem solving for teams. This system also offers an effective means to quantify the contribution of each member in collaborative team activity. We are planning to replicate these results in real-life situations.

Keywords: brainstorming, creative problem solving, peer-review, team efficiency

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Authors: Mustafa Metin Donma

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Metabolic syndrome (MetS) is characterized, in the first instance, by central obesity accompanied by disturbed blood pressure, glucose, and certain lipid fractions. Pediatric MetS is the predictor of MetS in adulthood and is commonly associated with cardiovascular diseases (CVDs). Since MetS is such a complicated health problem, attempts have been made to eliminate this problem. For this, many formulas have been developed. However, most of them require sophisticated mathematical expressions, which makes their usage in clinics difficult. Out of the overall complications, the most important problem which drew attention was the possibility of developing CVDs. Alanine aminotransferase-to-aspartate aminotransferase (ALT-to-AST) ratio is proven to be linked to cardiometabolic risk. The aim of this study was to introduce the possible association of an easily applicable formula with the ALT-to-AST ratio. The study population was composed of eighty-eight morbid obese (MO) children. The first group was the MO group; the second group was the MetS group. Each group consisted of forty-four children. Ethics committee approval and informed consent forms were taken. World Health Organization obesity criteria and international diabetes federation metabolic syndrome criteria were used for the selection of the participants in groups. Blood pressure values were determined. Routine laboratory tests were performed. Alanine aminotransferase-to-aspartate aminotransferase ratio (ALT/AST), homeostatic model assessment for insulin resistance (HOMA-IR), metabolic syndrome insulin resistance index (MetS-IR), diagnostic obesity notation model assessment metabolic syndrome index (DMetSI) were calculated. Statistical evaluation of the data was performed. All indices exhibited increased values in the MetS group compared to those calculated for the MO group. The increase in the median values for MetS-IR in the MetS group was less than two-fold. On the other hand, about a three-fold increase was observed for DMetSI in the MetS group in comparison with the value obtained in the MO group. The correlation between ALT/AST ratio and DMetSI was stronger than the correlation between ALT/AST and MetS-IR. Besides, DMetSI had no sophisticated mathematical expressions in the formula. In conclusion, two indices, MetS-IR and DMetSI, which were found to be much higher in the MetS group, and associations of both with ALT/AST ratio have indicated their potential as the tools for use in the differential diagnosis of MO and MetS. However, much higher association with ALT/AST, both an insulin resistance as well as a cardiometabolic ratio, easily applicable nature of the equation, and striking difference between median values of groups suggested that DMetSI showed much higher performance during the selection of MetS cases from MO population of children than the other index.

Keywords: cardiometabolic risk, childhood, metabolic syndrome, metabolic syndrome index, morbid obesity

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Authors: Forrest Kaatz, Adhemar Bultheel

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We use an informational statistical mechanics approach to study the catalytic thermodynamics of platinum and palladium cuboctahedral nanoclusters. Nanoclusters and their adatoms are viewed as chemical graphs with a nearest neighbor adjacency matrix. We use the Morse potential to determine bond energies between cluster atoms in a coordination type calculation. We use adsorbate energies calculated from density functional theory (DFT) to study the adatom effects on the thermodynamic quantities, which are derived from a Hamiltonian. Oxygen radical and molecular adsorbates are studied on platinum clusters and hydrogen on palladium clusters. We calculate the entropy, free energy, and total energy as the coverage of adsorbates increases from bridge and hollow sites on the surface. Thermodynamic behavior versus adatom coverage is related to the structural distribution of adatoms on the nanocluster surfaces. The thermodynamic functions are characterized using a simple adsorption model, with linear trends as the coverage of adatoms increases. The data exhibits size effects for the measured thermodynamic properties with cluster diameters between 2 and 5 nm. Entropy and enthalpy calculations of Pt-O2 compare well with previous theoretical data for Pt(111)-O2, and our Pd-H results show similar trends as experimental measurements for Pd-H2 nanoclusters. Our methods are general and may be applied to wide variety of nanocluster adsorbate systems.

Keywords: catalytic thermodynamics, palladium nanocluster absorbates, platinum nanocluster absorbates, statistical mechanics

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Authors: Tukeaban Hasanova, Jamila Imamalieva

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By the operational method, the problem on two-dimensional wave propagation in elastic medium excited by the round cylinder is solved. An analytical solution responding to instantaneous application of speed to the inclusion at its subsequent change is constructed. The two-dimensional problem on wave propagation in an elastic medium is considered.

Keywords: cylinder, inclusion, wave, elastic medium, speed

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Authors: V. Makis, L. Jafari

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In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Kasbparast Mehdi, Hassani Zainab

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Aim: The purpose of this research was to investigate the effectiveness of therapeutical sensorimotor exercise. The statistical population of women who were diagnosed with patellofemoral pain syndrome by a doctor and were between the ages of 35 and 45 and registered for the first time in a sports club in the 4th district of Tehran, 30 people by random sampling and according to The include and exclude criteria were selected and divided into 2 equal control and experimental and homogeneous groups (in terms of height, weight and BMI).In both control and experimental groups, the pain was measured using a Visual Analog Scale(VAS) functionality was measured using the step-down test and quality of life was measured using a World Health Organization Quality of Life Scale (WHOQOL-BREF) (pre-test). Then, only the experimental group performed sensorimotor exercises for 12 weeks and 3 sessions each week, a total of 24 sessions and each session for 1 hour, and during this period, the control group only continued their daily activities. After the end of the training period, the desired factors were evaluated again (post-test) in the same way as the pre-test was done for them (experimental group and control group), with the same quality. Findings: The statistical results showed that in the experimental group, the amount of pain, function and quality of life had a statistical improvement (P≤0.05). Conclusion: In general conclusion, it can be stated that using sensorimotor exercises not only improved functionality and quality of life but also reduced the amount of pain in people with patellofemoral pain syndrome.

Keywords: pain, PFPS, sensori motor training, functionality

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Authors: Mahmoud Owais

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Public Transit (P.T) is very important means to reduce traffic congestion, to improve urban environmental conditions and consequently affects people social lives. Planning, designing and management of P.T are the key issues for offering a competitive mode that can compete with the private transportation. These transportation planning, designing and management issues are addressed in the Transit Network Design Problem (TNDP). It deals with a complete hierarchy of decision making process. It includes strategic, tactical and operational decisions. The main body of TNDP is two stages, namely; route design stage and frequency setting. The TNDP is extensively studied in the last five decades; however the research gate is still widely open due to its many practical and modeling challenges. In this paper, a comprehensive background is given to illustrate the issues and challenges related to the TNDP to help in directing the incoming researches towards the untouched areas of the problem.

Keywords: frequency setting, network design, transit planning, urban planning

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Butta Singh

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This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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Authors: Titinan Pothong, Prasit Wangpakapattanawong, Stephen Elliott

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Shifting cultivation is an indigenous agricultural practice among upland people and has long been one of the major land-use systems in Southeast Asia. As a result, fallows and secondary forests have come to cover a large part of the region. However, they are increasingly being replaced by monocultures, such as corn cultivation. This is believed to be a main driver of deforestation and forest degradation, and one of the reasons behind the recurring winter smog crisis in Thailand and around Southeast Asia. Accurate biomass estimation of trees is important to quantify valuable carbon stocks and changes to these stocks in case of land use change. However, presently, Thailand lacks proper tools and optimal equations to quantify its carbon stocks, especially for secondary evergreen forests, including fallow areas after shifting cultivation and smaller trees with a diameter at breast height (DBH) of less than 5 cm. Developing new allometric equations to estimate biomass is urgently needed to accurately estimate and manage carbon storage in tropical secondary forests. This study established new equations using a destructive method at three study sites: approximately 50-year-old secondary forest, 4-year-old fallow, and 7-year-old fallow. Tree biomass was collected by harvesting 136 individual trees (including coppiced trees) from 23 species, with a DBH ranging from 1 to 31 cm. Oven-dried samples were sent for carbon analysis. Wood density was calculated from disk samples and samples collected with an increment borer from 79 species, including 35 species currently missing from the Global Wood Densities database. Several models were developed, showing that aboveground biomass (AGB) was strongly related to DBH, height (H), and wood density (WD). Including WD in the model was found to improve the accuracy of the AGB estimation. This study provides insights for reforestation management, and can be used to prepare baseline data for Thailand’s carbon stocks for the REDD+ and other carbon trading schemes. These may provide monetary incentives to stop illegal logging and deforestation for monoculture.

Keywords: aboveground biomass, allometric equation, carbon stock, secondary forest

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Authors: Hany Mustafa, Mahmoud Roushdi, Khaled Kheireldin

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Rainfall variability is an important feature of semi-arid climates. Climate change is very likely to increase the frequency, magnitude, and variability of extreme weather events such as droughts, floods, and storms. The Blue Nile Basin is facing extreme climate change-related events such as floods and droughts and its possible impacts on ecosystem, livelihood, agriculture, livestock, and biodiversity are expected. Rainfall variability is a threat to food production in the Blue Nile Basin countries. This study investigates the long-term variations and trends of seasonal and annual precipitation over the Blue Nile Basin for 102-year period (1901-2002). Six statistical trend analysis of precipitation was performed with nonparametric Mann-Kendall test and Sen's slope estimator. On the other hands, four statistical absolute homogeneity tests: Standard Normal Homogeneity Test, Buishand Range test, Pettitt test and the Von Neumann ratio test were applied to test the homogeneity of the rainfall data, using XLSTAT software, which results of p-valueless than alpha=0.05, were significant. The percentages of significant trends obtained for each parameter in the different seasons are presented. The study recommends adaptation strategies to be streamlined to relevant policies, enhancing local farmers’ adaptive capacity for facing future climate change effects.

Keywords: Blue Nile basin, climate change, Mann-Kendall test, trend analysis

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