Search results for: time based DNA codes

Authors: Adibah Shuib, Zati Aqmar Zaharudin

Abstract:

Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances to be allocated at these locations. The model aims at maximizing the expected demand coverage based on probability of reaching the emergency location within targetted time, and minimizing the ambulance busyness likelihood value. Among the benefits of the model is the increased accessibility and availability of ambulances, thus, enhanced quality of the EMS ambulance services.

Keywords: Optimization, Ambulance Location, Location facilities.

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: Biometric characters, facial recognition, neural network, OpenCV.

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Authors: J. A. López, C.I. López, J.E. Olguín, C. Camargo, J. M. López

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The institutions seek to improve their performance and quality of service, so that their patients are satisfied. This research project aims, conduct a time study program in the area of gynecological surgery, to determine the current level of capacity and optimize the programming time in order to adequately respond to demand. The system is analyzed by waiting lines and uses the simulation using ARENA to evaluate proposals for improvement and optimization programming time each of the surgeries.

Keywords: Time study, waiting lines, reducing time, simulation.

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Authors: Julio Molleda, Daniel F. García, Juan C. Granda, Francisco J. Suárez

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One of the main trouble in a steel strip manufacturing line is the breakage of whatever weld carried out between steel coils, that are used to produce the continuous strip to be processed. A weld breakage results in a several hours stop of the manufacturing line. In this process the damages caused by the breakage must be repaired. After the reparation and in order to go on with the production it will be necessary a restarting process of the line. For minimizing this problem, a human operator must inspect visually and manually each weld in order to avoid its breakage during the manufacturing process. The work presented in this paper is based on the Bayesian decision theory and it presents an approach to detect, on real-time, steel strip defective welds. This approach is based on quantifying the tradeoffs between various classification decisions using probability and the costs that accompany such decisions.

Keywords: Classification, Pattern Recognition, ProbabilisticReasoning, Statistical Data Analysis.

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Authors: Siriwan Saksiriruthai

Abstract:

This paper develops models to analyze the relationship between leisure time and wage change. Using Thailand-s Time Use Survey and Labor Force Survey data, the estimation of wage changes in response to leisure time change indicates that media receiving, personal care and social participation and volunteer activities are the ones that significantly raise hourly wages. Thus, the finding suggests the stimulation in time use for media access to enhance knowledge and productivity, personal care for attractiveness and healthiness in order to raise productivity, and social activities to develop connections for possible future opportunities including wage increase. These activities should be promoted for productive leisure time and for welfare improvement.

Keywords: Leisure, wage, time use, Thailand.

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Authors: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

Abstract:

Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R²) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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Authors: Rudolf Csikja, Janos Toth

Abstract:

Methods to detect and localize time singularities of polynomial and quasi-polynomial ordinary differential equations are systematically presented and developed. They are applied to examples taken form different fields of applications and they are also compared to better known methods such as those based on the existence of linear first integrals or Lyapunov functions.

Keywords: blow up, finite escape time, polynomial ODE, singularity, Lotka–Volterra equation, Painleve analysis, Ψ-series, global existence

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: Brain Computer Interface (BCI), Electroencephalogram (EEG), EEGLab, BCILab, Emotiv, Emotions, Interval features, Spectral features, Artificial Neural Network, Control applications.

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Authors: J. Barbarán, M. Díaz, I. Esteve, D. Garrido, L. Llopis, B. Rubio

Abstract:

Wireless Sensor and Actor Networks (WSANs) constitute an emerging and pervasive technology that is attracting increasing interest in the research community for a wide range of applications. WSANs have two important requirements: coordination interactions and real-time communication to perform correct and timely actions. This paper introduces a methodology to facilitate the task of the application programmer focusing on the coordination and real-time requirements of WSANs. The methodology proposed in this model uses a real-time component model, UM-RTCOM, which will help us to achieve the design and implementation of applications in WSAN by using the component oriented paradigm. This will help us to develop software components which offer some very interesting features, such as reusability and adaptability which are very suitable for WSANs as they are very dynamic environments with rapidly changing conditions. In addition, a high-level coordination model based on tuple channels (TC-WSAN) is integrated into the methodology by providing a component-based specification of this model in UM-RTCOM; this will allow us to satisfy both sensor-actor and actor-actor coordination requirements in WSANs. Finally, we present in this paper the design and implementation of an application which will help us to show how the methodology can be easily used in order to achieve the development of WSANs applications.

Keywords: Sensor networks, real time and embedded systems.

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Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

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Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, mobile GIS, real-time, REST API.

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Authors: V. Girondel, L. Bonnaud, A. Caplier, M. Rombaut

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This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.

Keywords: Belief theory, classifiers comparison, data fusion, human motion analysis, real-time processing, static posture recognition.

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Authors: K. G. Anilkumar, T. Tanprasert

Abstract:

This paper presents a subjective job scheduler based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy alignment procedure in order formulates a real-life situation. The BPNN estimates critical values of jobs based on the given subjective criteria. The scheduler is formulated in such a way that, at each time period, the most critical job is selected from the job queue and is transferred into a single machine before the next periodic job arrives. If the selected job is one of the oldest jobs in the queue and its deadline is less than that of the arrival time of the current job, then there is an update of the deadline of the job is assigned in order to prevent the critical job from its elimination. The proposed satisfiability criteria indicates that the satisfaction of the scheduler with respect to performance of the BPNN, validity of the jobs and the feasibility of the scheduler.

Keywords: Backpropagation algorithm, Critical value, Greedy alignment procedure, Neural network, Subjective criteria, Satisfiability.

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Authors: Daniel F. Garcia, Julio Molleda, Francisco Gonzalez, Ruben Usamentiaga

Abstract:

The development of many measurement and inspection systems of products based on real-time image processing can not be carried out totally in a laboratory due to the size or the temperature of the manufactured products. Those systems must be developed in successive phases. Firstly, the system is installed in the production line with only an operational service to acquire images of the products and other complementary signals. Next, a recording service of the image and signals must be developed and integrated in the system. Only after a large set of images of products is available, the development of the real-time image processing algorithms for measurement or inspection of the products can be accomplished under realistic conditions. Finally, the recording service is turned off or eliminated and the system operates only with the real-time services for the acquisition and processing of the images. This article presents a systematic performance evaluation of the image compression algorithms currently available to implement a real-time recording service. The results allow establishing a trade off between the reduction or compression of the image size and the CPU time required to get that compression level.

Keywords: Lossless image compression, codec performanceevaluation, grayscale codec comparison, real-time image recording.

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Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami

Abstract:

Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.

Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.

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Authors: Sofien Chtourou, Mohamed Chtourou, Omar Hammami

Abstract:

Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Keywords: Address, data set, memory, prediction, recurrentneural network.

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Authors: Qing Dai, Zhengkui Lin, Jiajia Zhang, Yi Qu

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Based on activity method, this paper focuses on morning commuting behavior when commuters travel with autonomous vehicles (AVs). Firstly, a net utility function of commuters is constructed by the activity utility of commuters at home, in car and at workplace, and the disutility of travel time cost and that of schedule delay cost. Then, this net utility function is applied to build an equilibrium model. Finally, under the assumption of constant marginal activity utility, the properties of equilibrium are analyzed. The results show that, in autonomous driving, the starting and ending time of morning peak and the number of commuters who arrive early and late at workplace are the same as those in manual driving. In automatic driving, however, the departure rate of arriving early at workplace is higher than that of manual driving, while the departure rate of arriving late is just the opposite. In addition, compared with manual driving, the departure time of arriving at workplace on time is earlier and the number of people queuing at the bottleneck is larger in automatic driving. However, the net utility of commuters and the total net utility of system in automatic driving are greater than those in manual driving.

Keywords: Autonomous cars, bottleneck model, activity utility, user equilibrium.

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Authors: Leili Nosrati, Alireza Nemaney Pour

Abstract:

Although e-mail is the most efficient and popular communication method, unwanted and mass unsolicited e-mails, also called spam mail, endanger the existence of the mail system. This paper proposes a new algorithm called Dynamic Weighted Majority Concept Drift Detection (DWM-CDD) for content-based filtering. The design purposes of DWM-CDD are first to accurate the performance of the previously proposed algorithms, and second to speed up the time to construct the model. The results show that DWM-CDD can detect both sudden and gradual changes quickly and accurately. Moreover, the time needed for model construction is less than previously proposed algorithms.

Keywords: Concept drift, Content-based filtering, E-mail, Spammail.

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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Authors: M. Sreedhar Babu, Vishal Garg, S. B. Akella, Shibu Clement, N. K. S Rajan

Abstract:

Producer gas is a biomass derived gaseous fuel which is extensively used in internal combustion engines for power generation application. Unlike the conventional hydrocarbon fuels (Gasoline and Natural gas), the combustion properties of producer gas fuel are much different. Therefore, setting of optimal spark time for efficient engine operation is required. Owing to the fluctuating tendency of producer gas composition during gasification process, the heat release patterns (dictating the power output and emissions) obtained are quite different from conventional fuels. It was found that, valve lift timing is yet another factor which influences the burn rate of producer gas fuel, and thus, the heat release rate of the engine. Therefore, the present study was motivated to estimate the influence of valve lift timing analytically (Wiebe model) on the burn rate of producer gas through curve fitting against experimentally obtained mass fraction burn curves of several producer gas compositions. Furthermore, Wiebe models are widely used in zero-dimensional codes for engine parametric studies and are quite popular. This study also addresses the influence of hydrogen and methane concentration of producer gas on combustion trends, which are known to cause dynamics in engine combustion.

Keywords: Combustion Duration, crank angle, mass fraction burnt, producer gas, wiebe combustion model, wide open throttle.

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Authors: A. Novák, K. Máriás

Abstract:

We examined the effects of the sowing time on the yield production and oil content of the sunflower hybrids in 2010 and 2012. The crop year and the sowing time had both a strong impact on the yield, on the oil- content and yield. By delaying the sowing time both the yield crop result and the oil yield increased. In 2010 in terms of crop yield and oil yield results PR64H42 was the best, in 2012 NK Neoma, in all three sowing times. The oil content of the hybrids was better in 2010. The highest oil content was recorded at early sowing time. We found out that the hybrid had a stronger impact in 2010 on both crop yield result and on oil content than in 2012. The sowing time played a bigger role regarding yield results in 2012. In addition the sowing time influenced oil content development highly.

Keywords: Genotypes, oil content, sowing time, sunflower, yield.

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Authors: Nikolay Nikolaev, Evgueni Smirnov

Abstract:

This paper develops an unscented grid-based filter and a smoother for accurate nonlinear modeling and analysis of time series. The filter uses unscented deterministic sampling during both the time and measurement updating phases, to approximate directly the distributions of the latent state variable. A complementary grid smoother is also made to enable computing of the likelihood. This helps us to formulate an expectation maximisation algorithm for maximum likelihood estimation of the state noise and the observation noise. Empirical investigations show that the proposed unscented grid filter/smoother compares favourably to other similar filters on nonlinear estimation tasks.

Keywords:

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: Amran Hassan, Fatimah Yusooff, Khadijah Alavi

Abstract:

The psychological well-being of a family is a subjective matter for evaluation, all the more when it involves the element of religions, whether Islam, Christianity, Buddhism or Hinduism. Each of these religions emphasises similar values and morals on family psychological well-being. This comparative study is specifically to determine the role of religion on family psychological well-being in Pekan district, Pahang, Malaysia. The study adopts a quantitative and qualitative mixed method design and considers a total of 412 samples of parents and children for the quantitative study, and 21 samples for the qualitative study. The quantitative study uses simple random sampling, whereas the qualitative sampling is purposive. The instrument for quantitative study is Ryff’s Psychological Well-being Scale and the qualitative study involves the construction of a guidelines protocol for in-depth interviews of respondents. The quantitative study uses the SPSS version .19 with One Way Anova, and the qualitative analysis is manual based on transcripts with specific codes and themes. The results show nonsignificance, that is, no significant difference among religions in all family psychological well-being constructs in the comparison of Islam, Christianity, Buddhism and Hinduism, thereby accepting a null hypothesis and rejecting an alternative hypothesis. The qualitative study supports the quantitative study, that is, all 21 respondents explain that no difference exists in psychological wellbeing in the comparison of teachings in all the religious mentioned. These implications may be used as guidelines for government and non-government bodies in considering religion as an important element in family psychological well-being in the long run. 

Keywords: Psychological well-being, comparison of religions, family, Malaysia.

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

Abstract:

Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time.

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Authors: Zdravka Aljinović, Snježana Pivac, Boško Šego

Abstract:

According to the interaction of inflation and unemployment, expectation of the rate of inflation in Croatia is estimated. The interaction between inflation and unemployment is shown by model based on three first-order differential i.e. difference equations: Phillips relation, adaptive expectations equation and monetary-policy equation. The resulting equation is second order differential i.e. difference equation which describes the time path of inflation. The data of the rate of inflation and the rate of unemployment are used for parameters estimation. On the basis of the estimated time paths, the stability and convergence analysis is done for the rate of inflation.

Keywords: Differencing, inflation, time path, unemployment.

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Authors: E. Golden Julie, S. Tamil Selvi, Y. Harold Robinson

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Many Wireless Sensor Network (WSN) applications necessitate secure multicast services for the purpose of broadcasting delay sensitive data like video files and live telecast at fixed time-slot. This work provides a novel method to deal with end-to-end delay and drop rate of packets. Opportunistic Routing chooses a link based on the maximum probability of packet delivery ratio. Null Key Generation helps in authenticating packets to the receiver. Markov Decision Process based Adaptive Scheduling algorithm determines the time slot for packet transmission. Both theoretical analysis and simulation results show that the proposed protocol ensures better performance in terms of packet delivery ratio, average end-to-end delay and normalized routing overhead.

Keywords: Delay-sensitive data, Markovian Decision Process based Adaptive Scheduling, Opportunistic Routing, Digital Signature authentication.

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Authors: Tirtha S. Das, Ayan K. Sau, Subir K. Sarkar

Abstract:

Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.

Keywords: Spread spectrum modulation, spreading code, signaldecomposition, security, successive bit cancellation

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Authors: Mbaitiga Zacharie

Abstract:

The objective of the presented work is to implement the Kalman Filter into an application that reduces the influence of the environmental changes over the robot expected to navigate over a terrain of varying friction properties. The Discrete Kalman Filter is used to estimate the robot position, project the estimated current state ahead at time through time update and adjust the projected estimated state by an actual measurement at that time via the measurement update using the data coming from the infrared sensors, ultrasonic sensors and the visual sensor respectively. The navigation test has been performed in a real world environment and has been found to be robust.

Keywords: Kalman filter, sensors fusion, robot navigation.

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Authors: Arnaud Nougues

Abstract:

This paper describes a two-stage methodology derived from IMC (Internal Model Control) for tuning a PID (Proportional-Integral-Derivative) controller for levels or other integrating processes in an industrial environment. Focus is ease of use and implementation speed which are critical for an industrial application. Tuning can be done with minimum effort and without the need of time-consuming open-loop step tests on the plant. The first stage of the method applies to levels only: the vessel residence time is calculated from equipment dimensions and used to derive a set of preliminary PI (Proportional-Integral) settings with IMC. The second stage, re-tuning in closed-loop, applies to levels as well as other integrating processes: a tuning correction mechanism has been developed based on a series of closed-loop simulations with model errors. The tuning correction is done from a simple closed-loop step test and application of a generic correlation between observed overshoot and integral time correction. A spin-off of the method is that an estimate of the vessel residence time (levels) or open-loop process gain (other integrating process) is obtained from the closed-loop data.

Keywords: closed-loop model identification, IMC-PID tuning method, integrating process control, on-line PID tuning adaptation

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Authors: Cheng Li, Jie Shen, Yutian Tang

Abstract:

Embracing the upcoming era of urbanization with the challenges of limitation of resources, disappearing cultural identities and conflicts among different groups of stakeholders, new integrated approaches are offered in our urban practice to help decision-makers and stakeholders frame and develop well-conceived, practical strategies for urban developing trajectories to approach urban-level sustainability in multiple social, cultural, ecological dimensions. Through bottom-up participation, we take advantage of tourism and leisure industries as driving forces for urbanization in China to promote integrated sustainable systems, with the hope of approaching both historical and ecological aspects of urban sustainability; and also thanks to top-down participation, we have codes, standards and rules established by the governments to strengthen the implementation of ecological urban sustainability. The results are monitored and evaluated experimentally and multidimensionally and the sustainable systems we constructed with local stakeholder groups turned out to be effective. The presentation of our selected projects would indicate our different focuses on urban sustainability.

Keywords: Urban sustainability, integrated urban strategy, tourism and leisure industries, history, modern technology.

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