Search results for: latent variables

Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain subgroups of time series data with normal distribution from the inflow into wastewater treatment plant data, composed of several groups differing by mean value. Two simple algorithms, K-mean and EM, were chosen as a clustering method. The Rand index was used to measure the similarity. After simple meta-clustering, a regression model was performed for each subgroups. The final model was a sum of the subgroups models. The quality of the obtained model was compared with the regression model made using the same explanatory variables, but with no clustering of data. Results were compared using determination coefficient (R2), measure of prediction accuracy- mean absolute percentage error (MAPE) and comparison on a linear chart. Preliminary results allow us to foresee the potential of the presented technique.

Keywords: Clustering, Data analysis, Data mining, Predictive models.

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Authors: Antonis Skouloudis, Georgios Deligiannakis, Panagiotis Vouros, Konstantinos Evangelinos, Ioannis Nikolaou

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On November 15th, 2017, a catastrophic flash flood devastated the city of Mandra in Central Greece, resulting in 24 fatalities and extensive damages to the built environment and infrastructure. It was Greece’s deadliest and most destructive flood event for the past 40 years. In this paper, we examine the consequences of this event to small and medium-sized enterprises (SMEs) operating in Mandra during the flood event, which were affected by the floodwaters to varying extents. In this context, we conducted semi-structured interviews with business owners-managers of 45 SMEs located in flood inundated areas and are still active nowadays, based on an interview guide that spanned 27 topics. The topics pertained to the disaster experience of the business and business owners-managers, knowledge and attitudes towards climate change and extreme weather, aspects of disaster preparedness and related assistance needs. Our findings reveal that the vast majority of the affected businesses experienced heavy damages in equipment and infrastructure or total destruction, which resulted in business interruption from several weeks up to several months. Assistance from relatives or friends helped for the damage repairs and business recovery, while state compensations were deemed insufficient compared to the extent of the damages. Most interviewees pinpoint flooding as one of the most critical risks, and many connect it with the climate crisis. However, they are either not willing or unable to apply property-level prevention measures in their businesses due to cost considerations or complex and cumbersome bureaucratic processes. In all cases, the business owners are fully aware of the flood hazard implications, and since the recovery from the event, they have engaged in basic mitigation measures and contingency plans in case of future flood events. Such plans include insurance contracts whenever possible (as the vast majority of the affected SMEs were uninsured at the time of the 2017 event) as well as simple relocations of critical equipment within their property. The study offers fruitful insights on latent drivers and barriers of SMEs’ resilience capacity to flash flooding. In this respect, findings such as ours, highlighting tensions that underpin behavioural responses and experiences, can feed into: a) bottom-up approaches for devising actionable and practical guidelines, manuals and/or standards on business preparedness to flooding, and, ultimately, b) policy-making for an enabling environment towards a flood-resilient SME sector.

Keywords: Flash flood, small and medium-sized enterprises, organisational resilience capacity, disaster preparedness, qualitative study.

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Authors: K. Diwakar, K. Aanandha Saravanan, C. Senthilpari

Abstract:

Higher order ΔΣ Modulator (DSM) is basically an unstable system. The approximate conditions for stability cannot be used for the design of a DSM for industrial applications where risk is involved. The existing second order, single stage, single bit, unity feedback gain , discrete DSM cannot be used for the normalized full range (-1 to +1) of an input signal since the DSM becomes unstable when the input signal is above ±0.55. The stability is also not guaranteed for input signals of amplitude less than ±0.55. In the present paper, the above mentioned second order DSM is modified with input signal dependent forward path gain. The proposed DSM is suitable for industrial applications where one needs the digital representation of the analog input signal, during each sampling period. The proposed DSM can operate almost for the full range of input signals (-0.95 to +0.95) without causing instability, assuming that the second integrator output should not exceed the circuit supply voltage, ±15 Volts.

Keywords: DSM, stability, SNR, state variables.

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Authors: Sahbi Farhani

Abstract:

This study investigates the relationship between external debt and military spending in case of India over the period of 1970–2012. In doing so, we have applied the structural break unit root tests to examine stationarity properties of the variables. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach is used to test whether cointegration exists in presence of structural breaks stemming in the series. Our results indicate the cointegration among external debt, military spending, debt servicing, and economic growth. Moreover, military spending and debt servicing add in external debt. Economic growth helps in lowering external debt. The Vector Error Correction Model (VECM) analysis and Granger causality test reveal that military spending and economic growth cause external debt. The feedback effect also exists between external debt and debt servicing in case of India.

Keywords: External debt, military spending, ARDL approach, structural breaks, India.

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Authors: A. M. El Ansary, A. A. El Damatty, A. O. Nassef

Abstract:

The aim of the current study is to develop a numerical tool that is capable of achieving an optimum shape and design of hyperbolic cooling towers based on coupling a non-linear finite element model developed in-house and a genetic algorithm optimization technique. The objective function is set to be the minimum weight of the tower. The geometric modeling of the tower is represented by means of B-spline curves. The finite element method is applied to model the elastic buckling behaviour of a tower subjected to wind pressure and dead load. The study is divided into two main parts. The first part investigates the optimum shape of the tower corresponding to minimum weight assuming constant thickness. The study is extended in the second part by introducing the shell thickness as one of the design variables in order to achieve an optimum shape and design. Design, functionality and practicality constraints are applied.

Keywords: B-splines, Cooling towers, Finite element, Genetic algorithm, Optimization

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Authors: R.M.Rani

Abstract:

Chess is one of the indoor games, which improves the level of human confidence, concentration, planning skills and knowledge. The main objective of this paper is to help the chess players to improve their chess openings using data mining techniques. Budding Chess Players usually do practices by analyzing various existing openings. When they analyze and correlate thousands of openings it becomes tedious and complex for them. The work done in this paper is to analyze the best lines of Blackmar- Diemer Gambit(BDG) which opens with White D4... using data mining analysis. It is carried out on the collection of winning games by applying association rules. The first step of this analysis is assigning variables to each different sequence moves. In the second step, the sequence association rules were generated to calculate support and confidence factor which help us to find the best subsequence chess moves that may lead to winning position.

Keywords: Blackmar-Diemer Gambit(BDG), Confidence, sequence Association Rules, Support.

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Authors: S. M. H. Karimian, F. S. Salehi, H. Alisadeghi

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A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.

Keywords: Moving mesh, Overset grid, Unsteady Euler, Relative motion.

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Authors: Zuraida Alwadood, Adibah Shuib, Norlida Abd Hamid

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This paper presents the review of past studies concerning mathematical models for rescheduling passenger railway services, as part of delay management in the occurrence of railway disruption. Many past mathematical models highlighted were aimed at minimizing the service delays experienced by passengers during service disruptions. Integer programming (IP) and mixed-integer programming (MIP) models are critically discussed, focusing on the model approach, decision variables, sets and parameters. Some of them have been tested on real-life data of railway companies worldwide, while a few have been validated on fictive data. Based on selected literatures on train rescheduling, this paper is able to assist researchers in the model formulation by providing comprehensive analyses towards the model building. These analyses would be able to help in the development of new approaches in rescheduling strategies or perhaps to enhance the existing rescheduling models and make them more powerful or more applicable with shorter computing time.

Keywords: Mathematical modelling, Mixed-integer programming, Railway rescheduling, Service delays.

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Authors: M. Ghasemi-Varnamkhasti, S. H. Yoosefian, A. Mohammad-Razdari

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This study investigated the effects of Ag nanoparticle polyethylene film and active modified atmosphere on the postharvest quality of tomatoes stored at 6 ºC. The atmosphere composition used in the packaging was 7% O₂ + 7% CO₂ + 86% N₂, and synthetic air (control). The variables measured were weight loss, firmness, color and respiration rate over 21 days. The results showed that the combination of Ag nanoparticle polyethylene film and modified atmosphere could extend the shelf life of tomatoes to 21 days and could influence the postharvest quality of tomatoes. Also, existence of Ag nanoparticles caused preventing from increasing weight loss, a*, b*, Chroma, Hue angle and reducing firmness and L*. As well as, tomatoes at Ag nanoparticle polyethylene films had lower respiration rate than Polyethylene and paper bags to 13.27% and 23.50%, respectively. The combination of Ag nanoparticle polyethylene film and active modified atmosphere was effective with regard to delaying maturity during the storage period, and preserving the quality of tomatoes.

Keywords: Ag nanoparticles, modified atmosphere, polyethylene film, tomato.

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Authors: Tithdanin Chav, Phichhang Ou

Abstract:

The study is about the e-banking consumer behavior of five major banks in Cambodia. This work aims to examine the relationships among job relevance, trust, mobility, perceived ease of use, perceived usefulness, attitude toward using, and intention to use of internet banking and apps. Also, the research develops and tests a conceptual model of intention to use internet banking by integrating the Technology Acceptance Model (TAM) and job relevance, trust, and mobility which were supported by Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). The proposed model was tested using Structural Equation Modeling (SEM), which was processed by using SPSS and AMOS with a sample size of 250 e-banking users. The results showed that there is a significant positive relationship among variables and attitudes toward using internet banking, and apps are the most factor influencing consumers’ intention to use internet banking and apps with the importance level in SEM 0.82 accounted by 82%. Significantly, all six hypotheses were accepted.

Keywords: Bank Apps, consumer intention, internet banking, technology acceptance model.

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Authors: Quratulain N. Rajput, Sajjad Haider

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This paper applies Bayesian Networks to support information extraction from unstructured, ungrammatical, and incoherent data sources for semantic annotation. A tool has been developed that combines ontologies, machine learning, and information extraction and probabilistic reasoning techniques to support the extraction process. Data acquisition is performed with the aid of knowledge specified in the form of ontology. Due to the variable size of information available on different data sources, it is often the case that the extracted data contains missing values for certain variables of interest. It is desirable in such situations to predict the missing values. The methodology, presented in this paper, first learns a Bayesian network from the training data and then uses it to predict missing data and to resolve conflicts. Experiments have been conducted to analyze the performance of the presented methodology. The results look promising as the methodology achieves high degree of precision and recall for information extraction and reasonably good accuracy for predicting missing values.

Keywords: Information Extraction, Bayesian Network, ontology, Machine Learning

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Authors: N. Mpofu, M. Sears

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In this paper, we propose a novel algorithm for delineating the endocardial wall from a human heart ultrasound scan. We assume that the gray levels in the ultrasound images are independent and identically distributed random variables with different Rician Inverse Gaussian (RiIG) distributions. Both synthetic and real clinical data will be used for testing the algorithm. Algorithm performance will be evaluated using the expert radiologist evaluation of a soft copy of an ultrasound scan during the scanning process and secondly, doctor’s conclusion after going through a printed copy of the same scan. Successful implementation of this algorithm should make it possible to differentiate normal from abnormal soft tissue and help disease identification, what stage the disease is in and how best to treat the patient. We hope that an automated system that uses this algorithm will be useful in public hospitals especially in Third World countries where problems such as shortage of skilled radiologists and shortage of ultrasound machines are common. These public hospitals are usually the first and last stop for most patients in these countries.

Keywords: Endorcardial Wall, Rician Inverse Distributions, Segmentation, Ultrasound Images.

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Authors: Madhukar Nagare, Pankaj Dutta, Amey Kambli

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Perishable goods constitute a large portion of retailer inventory and lose value with time due to deterioration and/or obsolescence. Retailers dealing with such goods required considering the factors of short shelf life and the dependency of sales on inventory displayed in determining optimal procurement policy. Many retailers follow the practice of using two bins - primary bin sales fresh items at a list price and secondary bin sales unsold items at a discount price transferred from primary bin on attaining certain age. In this paper, mathematical models are developed for primary bin and for secondary bin that maximizes profit with decision variables of order quantities, optimal review period and optimal selling price at secondary bin. The demand rates in two bins are assumed to be deterministic and dependent on displayed inventory level, price and age but independent of each other. The validity of the model is shown by solving an example and the sensitivity analysis of the model is also reported.

Keywords: Retail Inventory, Perishable Products, Two Bin, Profitable Sales.

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Authors: Nassima Cheikh, Abdelmadjid Cheikh, Said Hamou

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The objective of this work which is based on the approach of simultaneous engineering is to contribute to the development of a CIM tool for the synthesis of functional design dimensions expressed by average values and tolerance intervals. In this paper, the dispersions method known as the Δl method which proved reliable in the simulation of manufacturing dimensions is used to develop a methodology for the automation of the simulation. This methodology is constructed around three procedures. The first procedure executes the verification of the functional requirements by automatically extracting the functional dimension chains in the mechanical sub-assembly. Then a second procedure performs an optimization of the dispersions on the basis of unknown variables. The third procedure uses the optimized values of the dispersions to compute the optimized average values and tolerances of the functional dimensions in the chains. A statistical and cost based approach is integrated in the methodology in order to take account of the capabilities of the manufacturing processes and to distribute optimal values among the individual components of the chains.

Keywords: functional tolerances, manufacturing dispersions, simulation, CIM.

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Authors: I. Gokasar, G. Bakioglu

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With the unprecedented rates of technological improvements, people start to solve their problems with the help of technological tools. According to application stores and websites in which people evaluate and comment on the traffic apps, there are more than 100 traffic applications which have different features with respect to their purpose of usage ranging from the features of traffic apps for public transit modes to the features of traffic apps for private cars. This study focuses on the top 30 traffic applications which were chosen with respect to their download counts. All data about the traffic applications were obtained from related websites. The purpose of this study is to analyze traffic applications in terms of their categorical attributes with the help of developing a regression model. The analysis results suggest that negative interpretations (e.g., being deficient) does not lead to lower star ratings of the applications. However, those negative interpretations result in a smaller increase in star rate. In addition, women use higher star rates than men for the evaluation of traffic applications.

Keywords: Traffic App, real–time information, traffic congestion, regression analysis, dummy variables.

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

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Nonstationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based on the interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore, we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables’ interactions.

Keywords: Cardiac diseases, Complex systems theory, ECG analysis, matrix analysis.

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Authors: Olimpia Matarazzo, Lucia Abbamonte

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In two studies we challenged the well consolidated position in regret literature according to which the necessary condition for the emergence of regret is a bad outcome ensuing from free decisions. Without free choice, and, consequently, personal responsibility, other emotions, such as disappointment, but not regret, are supposed to be elicited. In our opinion, a main source of regret is being obliged by circumstance out of our control to chose an undesired option. We tested the hypothesis that regret resulting from a forced choice is more intense than regret derived from a free choice and that the outcome affects the latter, not the former. Besides, we investigated whether two other variables – the perception of the level of freedom of the choice and the choice justifiability – mediated the relationships between choice and regret, as well as the other four emotions we examined: satisfaction, anger toward oneself, disappointment, anger towards circumstances. The two studies were based on the scenario methodology and implied a 2 x 2 (choice x outcome) between design. In the first study the foreseen short-term effects of the choice were assessed; in the second study the experienced long-term effects of the choice were assessed. In each study 160 students of the Second University of Naples participated. Results largely corroborated our hypotheses. They were discussed in the light of the main theories on regret and decision making.

Keywords: Choice, outcome, regret.

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Authors: Feddaoui Amina

Abstract:

Income smoothing represents an attempt on the part of the company's management to reduce variations in earnings through the manipulation of the accounting principles. In this study, we aimed to measure income smoothing practices in a sample of 30 French joint stock companies during the period (2007-2009), we used Dummy variables method and “ECKEL” model to measure income smoothing practices and Binomial test accourding to SPSS program, to confirm or refute our hypothesis. This study concluded that there are no significant statistical indicators of income smoothing practices in the sample studied of French companies during the period (2007-2009), so the income series in the same sample studied of is characterized by stability and non-volatility without any intervention of management through accounting manipulation. However, this type of accounting manipulation should be taken into account and efforts should be made by control bodies to apply Eckel model and generalize its use at the global level.

Keywords: Income, smoothing, “Eckel”, French companies.

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Authors: S. Suren, U. Pancharoen

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A double module hollow fiber supported liquid membrane (HFSLM) was applied to selectively separate lead and mercury ions from dilute synthetic produced water. The experiments were investigated on several variables: types of extractants (D2EHPA, Cyanex 471, Aliquat 336, and TOA), concentration of the selected extractant and operating time. The results clearly showed that the double module HFSLM could selectively separate Pb(II) and Hg(II) in feed solution at a very low concentration to less than the regulatory discharge limit of 0.2 and 0.005 mg/L issued by the Ministry of Industry and the Ministry of Natural Resource Environment, Thailand. The highest extractions of lead and mercury ions from synthetic produced water were 96% and 100% using 0.03 M D2EHPA and 0.06 M Aliquat 336 as the extractant for the first and second modules.

Keywords: Hollow fiber, Lead ions, Liquid membrane, Mercury ions, Selective separation

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Authors: José M. Merigó, Montserrat Casanovas

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We present the induced generalized hybrid averaging (IGHA) operator. It is a new aggregation operator that generalizes the hybrid averaging (HA) by using generalized means and order inducing variables. With this formulation, we get a wide range of mean operators such as the induced HA (IHA), the induced hybrid quadratic averaging (IHQA), the HA, etc. The ordered weighted averaging (OWA) operator and the weighted average (WA) are included as special cases of the HA operator. Therefore, with this generalization we can obtain a wide range of aggregation operators such as the induced generalized OWA (IGOWA), the generalized OWA (GOWA), etc. We further generalize the IGHA operator by using quasi-arithmetic means. Then, we get the Quasi-IHA operator. Finally, we also develop an illustrative example of the new approach in a financial decision making problem. The main advantage of the IGHA is that it gives a more complete view of the decision problem to the decision maker because it considers a wide range of situations depending on the operator used.

Keywords: Decision making, Aggregation operators, OWA operator, Generalized means, Selection of investments.

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Authors: Petr Květon, Martin Jelínek

Abstract:

We try to identify the role of various aspects of parenting style in the phenomenon of videogame playing addiction. Relevant self-report questionnaires were part of a wider set of methods focused on the constructs related to videogame playing. The battery of methods was administered in school settings in paper and pencil form. The research sample consisted of 333 (166 males, 167 females) elementary and high school students at the age between 10 and 19 years (m=14.98, sd=1.77). Using stepwise regression analysis, we assessed the influence of demographic variables (gender and age) and parenting styles. Age and gender together explained 26.3% of game addiction variance (F(2,330)=58.81, p<.01). By adding four aspect of parenting styles (inconsistency, involvement, control, and warmth) another 10.2% of variance was explained (∆F(4,326)=13.09, p<.01). The significant predictor was gender of the respondent, where males scored higher on game addiction scale (B=0.70, p<.01), age (β=-0.18, p<.01), where younger children showed higher level of addiction, and parental inconsistency (β=0.30, p<.01), where the higher the inconsistency in upbringing, the more developed game playing addiction.

Keywords: Gender, parenting styles, video games, addiction.

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Authors: Sheroz Khan, I. Adam, A. H. M. Zahirul Alam, Mohd Rafiqul Islam, Othman O. Khalifa

Abstract:

This paper attempts to model and design a simple fuzzy logic controller with Variable Reference. The Variable Reference (VR) is featured as an adaptability element which is obtained from two known variables – desired system-input and actual system-output. A simple fuzzy rule-based technique is simulated to show how the actual system-input is gradually tuned in to a value that closely matches the desired input. The designed controller is implemented and verified on a simple heater which is controlled by PIC Microcontroller harnessed by a code developed in embedded C. The output response of the PIC-controlled heater is analyzed and compared to the performances by conventional fuzzy logic controllers. The novelty of this work lies in the fact that it gives better performance by using less number of rules compared to conventional fuzzy logic controllers.

Keywords: Fuzzy logic controller, Variable reference, Adaptability, Rule-based.

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Authors: Maha BenHamad, Ali Snoussi, Ammar Ben Brahim

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A steady-state analysis of triple-effect thermal vapor compressor desalination unit was performed. A mathematical model based on mass, salinity and energy balances is developed. The purpose of this paper is to develop a connection between process simulator and process optimizer in order to study the influence of several operating variables on the performance and the produced water cost of the unit. A MATLAB program is used to solve the model equations, and Aspen HYSYS is used to model the plant. The model validity is examined against a commercial plant and showed a good agreement between industrial data and simulations results. Results show that the pressures of the last effect and the compressed vapor have an important influence on the produced cost, and the increase of the difference temperature in the condenser decreases the specific heat area about 22%.

Keywords: Steady-state, triple effect, thermal vapor compressor, MATLAB, Aspen HYSYS.

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Authors: Nina Bijedic, Drazena Gaspar, Mirsad Hadzikadic

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Corruption is an influential and widespread problem. One part of it is so-called petty corruption, related to large-scale bribe giving by ordinary citizens trying to influence the works of public administration or public services. As it is with all means of corruption, petty corruption is related to the level of democracy (or administration efficiency) in a society. The developed model captures some of the factors related to corruptive behavior, as well as people’s attitude towards petty corruption. It has four basic elements: user’s perception of corruption in the society of interest, the influence of social interactions, the influence of penalizing mechanism, and influence of campaigns against petty corruption. The model is agent-based, developed in NetLogo, with a lot of random settings that provide a wider scope of responses. Interactions of different settings for variables of elements provide insight into the influence of each element on attitude towards petty corruption, as well as petty corruptive behavior.

Keywords: Agent based model, attitude, influence, petty corruption, society.

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Authors: Xiaofei Hu, Zhiyu Cai, Weian Yao

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V-notch problem under dynamic loading condition is considered in this paper. In the time domain, the precise time domain expanding algorithm is employed, in which a self-adaptive technique is carried out to improve computing accuracy. By expanding variables in each time interval, the recursive finite element formulas are derived. In the space domain, a Symplectic Analytical Singular Element (SASE) for V-notch problem is constructed addressing the stress singularity of the notch tip. Combining with the conventional finite elements, the proposed SASE can be used to solve the dynamic stress intensity factors (DSIFs) in a simple way. Numerical results show that the proposed SASE for V-notch problem subjected to dynamic loading condition is effective and efficient.

Keywords: V-notch, dynamic stress intensity factor, finite element method, precise time domain expanding algorithm.

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Authors: Hoai-Vu Nguyen, Yongsun Choi

Abstract:

Distributed denial-of-service (DDoS) attacks pose a serious threat to network security. There have been a lot of methodologies and tools devised to detect DDoS attacks and reduce the damage they cause. Still, most of the methods cannot simultaneously achieve (1) efficient detection with a small number of false alarms and (2) real-time transfer of packets. Here, we introduce a method for proactive detection of DDoS attacks, by classifying the network status, to be utilized in the detection stage of the proposed anti-DDoS framework. Initially, we analyse the DDoS architecture and obtain details of its phases. Then, we investigate the procedures of DDoS attacks and select variables based on these features. Finally, we apply the k-nearest neighbour (k-NN) method to classify the network status into each phase of DDoS attack. The simulation result showed that each phase of the attack scenario is classified well and we could detect DDoS attack in the early stage.

Keywords: distributed denial-of-service (DDoS), k-nearestneighbor classifier (k-NN), anti-DDoS framework, DDoS detection.

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Authors: Salaheddin Odeh, Ibrahim O. Adwan

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This interdisciplinary study is an investigation to evaluate user-interfaces in business administration. The study is going to be implemented on two computerized business administration systems with two distinctive user-interfaces, so that differences between the two systems can be determined. Both systems, a commercial and a prototype developed for the purpose of this study, deal with ordering of supplies, tendering procedures, issuing purchase orders, controlling the movement of the stocks against their actual balances on the shelves and editing them on their tabulations. In the second suggested system, modern computer graphics and multimedia issues were taken into consideration to cover the drawbacks of the first system. To highlight differences between the two investigated systems regarding some chosen standard quality criteria, the study employs various statistical techniques and methods to evaluate the users- interaction with both systems. The study variables are divided into two divisions: independent representing the interfaces of the two systems, and dependent embracing efficiency, effectiveness, satisfaction, error rate etc.

Keywords: Evaluation and usability testing, software prototyping, statistical methods, user-interface design.

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Authors: S. Noor, M. W. Siddiqi

Abstract:

This study examines causal link between energy use and economic growth for five South Asian countries over period 1971-2006. Panel cointegration, ECM and FMOLS are applied for short and long run estimates. In short run unidirectional causality from per capita GDP to per capita energy consumption is found, but not vice versa. In long run one percent increase in per capita energy consumption tend to decrease 0.13 percent per capita GDP. i.e. Energy use discourage economic growth. This short and long run relationship indicate energy shortage crisis in South Asia due to increased energy use coupled with insufficient energy supply. Beside this long run estimated coefficient of error term suggest that short term adjustment to equilibrium are driven by adjustment back to long run equilibrium. Moreover, per capita energy consumption is responsive to adjustment back to equilibrium and it takes 59 years approximately. It specifies long run feedback between both variables.

Keywords: Energy consumption, Income, Panel co-integration, Causality.

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Authors: Y. Parvizi, M. Gorji, M.H. Mahdian, M. Omid

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Soil organic carbon (SOC) plays a key role in soil fertility, hydrology, contaminants control and acts as a sink or source of terrestrial carbon content that can affect the concentration of atmospheric CO2. SOC supports the sustainability and quality of ecosystems, especially in semi-arid region. This study was conducted to determine relative importance of 13 different exploratory climatic, soil and geometric factors on the SOC contents in one of the semiarid watershed zones in Iran. Two methods canonical discriminate analysis (CDA) and feed-forward back propagation neural networks were used to predict SOC. Stepwise regression and sensitivity analysis were performed to identify relative importance of exploratory variables. Results from sensitivity analysis showed that 7-2-1 neural networks and 5 inputs in CDA models output have highest predictive ability that explains %70 and %65 of SOC variability. Since neural network models outperformed CDA model, it should be preferred for estimating SOC.

Keywords: Soil organic carbon, modeling, neural networks, CDA.

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Authors: Yuwaraj M. Ghugal, Ajay G. Dahake

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A trigonometric shear deformation theory for flexure of thick beams, taking into account transverse shear deformation effects, is developed. The number of variables in the present theory is same as that in the first order shear deformation theory. The sinusoidal function is used in displacement field in terms of thickness coordinate to represent the shear deformation effects. The noteworthy feature of this theory is that the transverse shear stresses can be obtained directly from the use of constitutive relations with excellent accuracy, satisfying the shear stress free conditions on the top and bottom surfaces of the beam. Hence, the theory obviates the need of shear correction factor. Governing differential equations and boundary conditions are obtained by using the principle of virtual work. The thick cantilever isotropic beams are considered for the numerical studies to demonstrate the efficiency of the. Results obtained are discussed critically with those of other theories.

Keywords: Trigonometric shear deformation, thick beam, flexure, principle of virtual work, equilibrium equations, stress.

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