Search results for: elliptic curve digital signature algorithm

Authors: B. G. Patel, A. K. Desai, S. G. Shah

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The main of objective of this paper is to develop new measurement technique without touching the object. DIC is advance measurement technique use to measure displacement of particle with very high accuracy. This powerful innovative technique which is used to correlate two image segments to determine the similarity between them. For this study, nine geometrically similar beam specimens of different sizes with (steel fibers and glass fibers) and without fibers were tested under three-point bending in a closed loop servo-controlled machine with crack mouth opening displacement control with a rate of opening of 0.0005 mm/sec. Digital images were captured before loading (unreformed state) and at different instances of loading and were analyzed using correlation techniques to compute the surface displacements, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It was seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Keywords: Digital Image Correlation, fibres, self compacting concrete, size effect

Procedia PDF Downloads 389

Authors: Volkan Uygun, H. Birkan Yilmaz, Tuna Tugcu

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This study focuses on the development and use of algorithms that address the issue of resource management in response to emergency and disaster situations. The presented system, named Disaster Management Platform (DMP), takes the data from the data sources of service providers and distributes the incoming requests accordingly both to manage load balancing and minimize service time, which results in improved user satisfaction. Three different resource management algorithms, which give different levels of importance to load balancing and service time, are proposed for the study. The first one is the Minimum Distance algorithm, which assigns the request to the closest resource. The second one is the Minimum Load algorithm, which assigns the request to the resource with the minimum load. Finally, the last one is the Hybrid algorithm, which combines the previous two approaches. The performance of the proposed algorithms is evaluated with respect to waiting time, success ratio, and maximum load ratio. The metrics are monitored from simulations, to find the optimal scheme for different loads. Two different simulations are performed in the study, one is time-based and the other is lambda-based. The results indicate that, the Minimum Load algorithm is generally the best in all metrics whereas the Minimum Distance algorithm is the worst in all cases and in all metrics. The leading position in performance is switched between the Minimum Distance and the Hybrid algorithms, as lambda values change.

Keywords: emergency and disaster response, resource management algorithm, disaster situations, disaster management platform

Procedia PDF Downloads 338

Authors: Bagus Hanindhito, Fariz Azmi Pratama, Ulfah Nadiya

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Nowadays, digital system including, but not limited to, computer and internet have penetrated the education system widely. Critical information such as students’ academic records is stored in a server off- or on-campus. Although several countermeasures have been taken to protect the vital resources from outsider attack, the defense from insiders threat is not getting serious attention. At the end of 2017, a security incident that involved academic information system in one of the most respected universities in Indonesia affected not only the reputation of the institution and its academia but also academic integrity in Indonesia. In this paper, we will explain our efforts in investigating this security incident where we have implemented a novel rapid evidence remote acquisition method in high-availability server and storage system thus our data collection efforts do not disrupt the academic information system and can be conducted remotely minutes after incident report has been received. The acquired evidence is analyzed during digital forensic by constructing the model of the system in an isolated environment which allows multiple investigators to work together. In the end, the suspect is identified as a student (insider), and the investigation result is used by prosecutors to charge the suspect as an academic crime.

Keywords: academic information system, academic crime, digital forensic, high-availability server and storage, rapid evidence remote acquisition, security incident

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Authors: Daphne Dean C. Arenos, Glorificacion L. Quinopez

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This study has been conducted to describe the digitized stories authored by a Grade 1 pupil struggling in reading. The main goal was to find out the effect of authoring digital stories on the reading skill of a grade 1 pupil in terms of vocabulary and sequencing skills. To be able to explicate the data collected, a case study approach has been chosen. This case study focused on a 6 years old Filipino child born and raised in Spain and has just transferred to a private school a year ago. The pupil’s struggles in reading, as well as her experiences with digitized stories, were further described. The findings revealed that authoring digital stories facilitate the reading progress of a struggling pupil. The presence of literary elements in the pupil’s stories built her vocabulary and sequencing skills. Hence, authoring digital stories serve as an appropriate and effective scaffold for struggling readers.

Keywords: literary elements, reading skill, scaffold, sequencing skill, vocabulary

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Authors: Umar Javed, Kristen Blann, Philip Adalikwu, Maryam Sahraei, John McMaine

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The soil conservation service curve number (SCS-CN) is a widely used method to assess direct runoff depth based on specific rainfall events. “Actual” estimated runoff depth was estimated by subtracting the change in soil moisture from the depth of precipitation for each discrete rain event during the growing seasons from 2021 to 2023. Fields under investigation were situated in a HUC-12 watershed in southeastern South Dakota selected for a common soil series (Nora-Crofton complex and Moody-Nora complex) to minimize the influence of soil texture on soil moisture. Two soil moisture probes were installed from May 2021 to October 2023, with exceptions during planting and harvest periods. For each field, “Textbook” CN estimates were derived from the TR-55 table based on corresponding mapped land use land cover LULC class and hydrologic soil groups from web soil survey maps. The TR-55 method incorporated HSG and crop rotation within the study area fields. These textbook values were then compared to actual CN values to determine the impact of tillage practices on CN and runoff. Most fields were mapped as having a textbook C or D HSG, but the HSG of actual CNs was that of a B or C hydrologic group. Actual CNs were consistently lower than textbook CNs for all management practices, but actual CNs in conventionally tilled fields were the highest (and closest to textbook CNs), while actual CNs in no-till fields were the lowest. Preliminary results suggest that no-till practice reduces runoff compared to conventional till. This research highlights the need to use CNs that incorporate agricultural management to more accurately estimate runoff at the field and watershed scale.

Keywords: curve number hydrology, hydrologic soil groups, runoff, tillage practices

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: S. H. Borghei, E. Teymourian, M. Mobin, G. M. Komaki, S. Sheikh

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Imperialist competitive algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population based algorithm which has achieved a great performance in comparison to other meta-heuristics. This study is about developing enhanced ICA approach to solve the cell formation problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Keywords: cell formation problem, group technology, imperialist competitive algorithm, sequence data

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Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

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Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

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Authors: Davood Rajabi, Mojgan Yazdani

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Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.

Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood

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Authors: A. Yazdanmehr, H. Jahed

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Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

Keywords: large strain, compression-tension, loading-unloading, Mg alloys

Procedia PDF Downloads 238

Authors: Suparman

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This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

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Authors: Patrick Nurse, Professor Neil Sebire, Polly Livermore

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The use of digital systems in healthcare is now highly prevalent. With further advancement of technology, these systems will become increasingly utilised within the healthcare sector. Therefore understanding how clinicians (for example, doctors, nurses) interact with technology and digital systems is critical to making care safer. Seven members from the Parent/Carers’ Research Advisory Group and the Young-Persons’ Research Group at a healthcare Trust in London and three staff members contributed to an engagement workshop to assess the impact of digital systems on the practice of nurses. The group also advised on the viability of a research study to investigate this further. A wide range of issues within digital system implementation in healthcare were raised, such as ‘workarounds’, system’s training, and upkeep and regulation of usage, which all emerged as early themes during the discussion. Further discussion focused on the subject of escalation of issues, ‘workarounds’, and problem solving. While challenging to implement, digital systems are hugely beneficial to healthcare providers. The workshop indicated that there is scope for investigation of the prevalence, nature, and escalation of ‘workarounds’, this was of key interest to the advisory group. An interesting concern of the group was their worry from a patient and parental perspective regarding how nurses might feel when needing to complete a ‘workaround’ during a busy shift. This is especially relevant if the reasons to complete the ‘workaround’ were outside the nurse’s control, driven by clinical need and urgency of care. This showed the level of insight that those using healthcare services have into the reality of workflows of those providing care. Additionally, it reflects the desire for patients and families to understand more about the administration and methodology of their care. Future study should be dedicated to understanding why nurses deploy ‘workarounds’, as well as their perspective and experience of them and subsequent escalation through leadership hierarchies

Keywords: patient engagement/involvement, workarounds, medication-administration, digital systems

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Authors: Luay Alsalmi

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Background: Facial filler is the most common type of cosmetic surgery next to botox. Permanent filler is preferred nowadays due to the low cost brought about by non-recurring injection appointments. However, such fillers pose a higher risk for complications, with even greater adverse effects when the procedure is done using unknown dermal filler injections. AIM: This study aimed to establish an algorithm to categorize and manage patients that receive permanent fillers. Materials and Methods: Twelve participants were presented to the service through emergency or as outpatient from November 2015 to May 2021. Demographics such as age, sex, date of injection, time of onset, and types of complications were collected. After examination, all cases were managed based on an algorithm established. FACE-Q was used to measure overall satisfaction and psychological well-being. Results: The algorithm to diagnose and manage these patients effectively with a high satisfaction rate was established in this study. All participants were non-smoker females with no known medical comorbidities. The algorithm presented determined the treatment plan when faced with complications. Results revealed high appearance-related psychosocial distress was observed prior to surgery, while it significantly dropped after surgery. FACE-Q was able to establish evidence of satisfactory ratings among patients prior to and after surgery. Conclusion: This treatment algorithm can guide the surgeon in formulating a suitable plan with fewer complications and a high satisfaction rate.

Keywords: facial filler, FACE-Q, psycho-social stress, botox, treatment algorithm

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Authors: M. Samadzadeh Mahabadi, J. Shanbehzadeh

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This paper presents a hybrid digital image-watermarking scheme, which is robust against varieties of attacks and geometric distortions. The image content is represented by important feature points obtained by an image-texture-based adaptive Harris corner detector. These feature points are extracted from LL2 of 2-D discrete wavelet transform which are obtained by using the Harris-Laplacian detector. We calculate the Fourier transform of circular regions around these points. The amplitude of this transform is rotation invariant. The experimental results demonstrate the robustness of the proposed method against the geometric distortions and various common image processing operations such as JPEG compression, colour reduction, Gaussian filtering, median filtering, and rotation.

Keywords: digital watermarking, geometric distortions, geometrical attack, Harris Laplace, important feature points, rotation, scale invariant feature

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Authors: Safiqul Islam, Anamul Haque, Mohammad Amran Hossain

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Aim: To compare the dosimetric parameters of the flattened and flattening filter free (FFF) beam and to validate the beam data using anisotropic analytical algorithm (AAA). Materials and Methods: All the dosimetric data’s (i.e. depth dose profiles, profile curves, output factors, penumbra etc.) required for the beam modeling of AAA were acquired using the Blue Phantom RFA for 6 MV, 6 FFF, 10MV & 10FFF. Progressive resolution Optimizer and Dose Volume Optimizer algorithm for VMAT and IMRT were are also configured in the beam model. Beam modeling of the AAA were compared with the measured data sets. Results: Due to the higher and lover energy component in 6FFF and 10 FFF the surface doses are 10 to 15% higher compared to flattened 6 MV and 10 MV beams. FFF beam has a lower mean energy compared to the flattened beam and the beam quality index were 6 MV 0.667, 6FFF 0.629, 10 MV 0.74 and 10 FFF 0.695 respectively. Gamma evaluation with 2% dose and 2 mm distance criteria for the Open Beam, IMRT and VMAT plans were also performed and found a good agreement between the modeled and measured data. Conclusion: We have successfully modeled the AAA algorithm for the flattened and FFF beams and achieved a good agreement with the calculated and measured value.

Keywords: commissioning of a Flattening Filter Free (FFF) , using an Anisotropic Analytical Algorithm (AAA), flattened beam, parameters

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Authors: Han Bing, Yin Zhenjie

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In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

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Authors: Ramdan B. A. Koad, Ahmed F. Zobaa

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Since the output characteristics of Photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum Power Point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a Maximum Power Point Tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), and Particle Swarm Optimization (PSO) algorithm for (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods.

Keywords: photovoltaic systems, maximum power point tracking, perturb and observe method, incremental conductance, methods and practical swarm optimization algorithm

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Authors: Honggang Qu, Yong Xu, Rongmei Liu, Zhenji Gao, Bin Wang

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Today's mining industry is advancing gradually toward digital and visual direction. The three-dimensional visualization geological modeling of mine is the digital characterization of mineral deposits and is one of the key technology of digital mining. Three-dimensional geological modeling is a technology that combines geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in a three-dimensional environment with computer technology and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between the distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provides scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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Authors: Pooja Seth, Shruti Aggarwal

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The Europium (Eu) doped (0.02-0.1 wt %) lithium fluoride (LiF) crystal in the form of multicrystalline sheet was gown by the edge defined film fed growth (EFG) technique. Crystals were grown in argon gas atmosphere using graphite crucible and stainless steel die. The systematic incorporation of Eu inside the host LiF lattice was confirmed by X-ray diffractometry. Thermoluminescence (TL) glow curve was recorded on annealed (AN) crystals after irradiation with a gamma dose of 15 Gy. The effect of different concentration of Eu in enhancing the thermoluminescence (TL) intensity of LiF was studied. The normalized peak height of the Eu-doped LiF crystal was nearly 12 times that of the LiF crystals. The optimized concentration of Eu in LiF was found to be 0.05wt% at which maximum TL intensity was observed with main TL peak positioned at 185 °C. At higher concentration TL intensity decreases due to the formation of precipitates in the form of clusters or aggregates. The nature of the energy traps in Eu doped LiF was analysed through glow curve deconvolution. The trap depth was found to be in the range of 0.2 – 0.5 eV. These results showed that doping with Eu enhances the TL intensity by creating more defect sites for capturing of electron and holes during irradiation which might be useful for dosimetry application.

Keywords: thermoluminescence, defects, gamma radiation, crystals

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Ali Hosseini

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Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

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Authors: Geir Kirkebøen

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Most patients with serious diagnoses want to know their prognosis, in particular their expected survival time. As part of the informed consent process, physicians are legally obligated to communicate such information to patients. However, there is no established (evidence based) ‘best practice’ for how to do this. The two questions explored in this study are: How do physicians communicate expected survival time to patients, and how should it be done? We explored the first, descriptive question in a study with Norwegian oncologists as participants. The study had a scenario and a survey part. In the scenario part, the doctors should imagine that a patient, recently diagnosed with a serious cancer diagnosis, has asked them: ‘How long can I expect to live with such a diagnosis? I want an honest answer from you!’ The doctors should assume that the diagnosis is certain, and that from an extensive recent study they had optimal statistical knowledge, described in detail as a right-skewed survival curve, about how long such patients with this kind of diagnosis could be expected to live. The main finding was that very few of the oncologists would explain to the patient the variation in survival time as described by the survival curve. The majority would not give the patient an answer at all. Of those who gave an answer, the typical answer was that survival time varies a lot, that it is hard to say in a specific case, that we will come back to it later etc. The survey part of the study clearly indicates that the main reason why the oncologists would not deliver the mortality prognosis was discomfort with its uncertainty. The scenario part of the study confirmed this finding. The majority of the oncologists explicitly used the uncertainty, the variation in survival time, as a reason to not give the patient an answer. Many studies show that patients want realistic information about their mortality prognosis, and that they should be given hope. The question then is how to communicate the uncertainty of the prognosis in a realistic and optimistic – hopeful – way. Based on psychological research, our hypothesis is that the best way to do this is by explicitly describing the variation in survival time, the (usually) right skewed survival curve of the prognosis, and emphasize to the patient the (small) possibility of being a ‘lucky outlier’. We tested this hypothesis in two scenario studies with lay people as participants. The data clearly show that people prefer to receive expected survival time as a median value together with explicit information about the survival curve’s right skewedness (e.g., concrete examples of ‘positive outliers’), and that communicating expected survival time this way not only provides people with hope, but also gives them a more realistic understanding compared with the typical way expected survival time is communicated. Our data indicate that it is not the existence of the uncertainty regarding the mortality prognosis that is the problem for patients, but how this uncertainty is, or is not, communicated and explained.

Keywords: cancer patients, decision psychology, doctor-patient communication, mortality prognosis

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Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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Authors: Khadidja Belbachir, Hafida Belbachir

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subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

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Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Introduction: Digital innovations have been useful in supporting a client’s contraceptive user journey from awareness to method initiation. The concept of contraceptive self-care is being promoted globally as a means for achieving universal access to quality contraceptive care; however, information about this approach is limited. An important determinant of the scale of awareness is the message construct, choice of information channel, and an understanding of the socio-epidemiological dynamics within the target audience. Significant gains have been made recently in expanding the awareness base of DMPA-SC -a relatively new entrant into the family planning method mix. The cornerstone of this success is a multichannel promotion campaign themed Discover your Power (DYP). The DYP campaign combines content marketing across select social media platforms, chatbots, Cyber-IPC, Interactive Voice Response (IVR), and radio campaigns. Methodology: During implementation, the project monitored predefined metrics of awareness and intent, such as the number of persons reached with the messages, the number of impressions, and meaningful engagement (link-clicks). Metrics/indicators are extracted through native insight/analytics tools across the various platforms. The project also enlists community mobilizers (CMs) who go door-to-door and engage WRA to advertise DISC’s online presence and support them to engage with IVR, digital companion (chatbot), Facebook page, and DiscoverYourPower website. Results: The result showed that the digital platforms recorded 242 million impressions and reached 82 million users with key DMPA-SC self-injection messaging in the three countries. As many as 3.4 million persons engaged (liked, clicked, shared, or reposted) digital posts -an indication of intention. Conclusion: Digital solutions and innovations are gradually becoming the archetype for the advancement of the self-care agenda. Digital innovations can also be used to increase awareness and normalize contraceptive self-care behavior amongst women of reproductive age if they are made an integral part of reproductive health programming.

Keywords: digital transformation, health systems, DMPA-SC, family planning, self-care

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Authors: Hamid R. Lashgarian Azad, Seyed N. Shetab Boushehri

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Wireless sensor networks (WSN) have become progressively popular due to their wide range of applications. Wireless Sensor Network is made of numerous tiny sensor nodes that are battery-powered. It is a very significant problem to maximize the lifetime of wireless sensor networks. In this paper, we propose a two-stage protocol based on an imperialist competitive algorithm (2S-ICA) to solve a sensor network optimization problem. The energy of the sensors can be greatly reduced and the lifetime of the network reduced by long communication distances between the sensors and the sink. We can minimize the overall communication distance considerably, thereby extending the lifetime of the network lifetime through connecting sensors into a series of independent clusters using 2SICA. Comparison results of the proposed protocol and LEACH protocol, which is common to solving WSN problems, show that our protocol has a better performance in terms of improving network life and increasing the number of transmitted data.

Keywords: wireless sensor network, imperialist competitive algorithm, LEACH protocol, k-means clustering

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Authors: Setyarini Sri, Nursalim Agus

Abstract:

Integrating critical thinking and digital based learning is one of demands in teaching English in 21st century. Child-friendly digital storytelling (CFDS) is an innovative learning model to promote young learners’ critical thinking. Therefore, this study aims to (1) investigate how child-friendly digital storytelling is implemented to promote young learners’ critical thinking in speaking English; (2) find out the benefits gained by the students in their learning based on CFDS. Classroom Action Research (CAR) took place in two cycles in which each of the cycle covered four phases namely: Planning, Acting, Observing, and Evaluating. Three classes of seventh graders were selected as the subjects of this study. Data were collected through observation, interview with some selected students as respondents, and document analysis in the form individual recorded storytelling. Sentences, phrases, words found in the transcribed data were identified and categorized based on Bloom taxonomy. The findings from the first cycle showed that the students seemed to speak critically that can be seen from the way they understood the story and related the story to their real life. Meanwhile, the result investigated from the second cycle likely indicated their higher level of critical thinking since the students spoke in English critically through comparing, questioning, analyzing, and evaluating the story by giving arguments, opinions, and comments. Such higher levels of critical thinking were also found in the students’ final project of individual recorded digital story. It is elaborated from the students’ statements in the interview who claimed CFDS offered opportunity to the students to promote their critical thinking because they comprehended the story deeply as they experienced in their real life. This learning model created good learning atmosphere and engaged the students directly so that they looked confident to retell the story in various perspectives. In term of the benefits of child-friendly digital storytelling, the students found it beneficial for some enjoyable classroom activities through watching beautiful and colorful pictures, listening to clear and good sounds, appealing moving motion and emotionally they were involved in that story. In the interview, the students also stated that child-friendly digital storytelling eased them to understand the meaning of the story as they were motivated and enthusiastic to speak in English critically.

Keywords: critical thinking, child-friendly digital storytelling, English speaking, promoting, young learners

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Authors: Abdelhadi Adel, Kadri Ouahab

Abstract:

This paper proposes an improved approach based on MAS Architecture and Heuristic Algorithm for systematic maintenance to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: Misook Ahn

Abstract:

This study examined the Digital Curriculum Repository (DCR) project initiated at Defense Language Institute Foreign Language Center (DLIFLC). The purpose of the DCR is to build a centralized curriculum infrastructure, preserve all curriculum materials, and provide academic service to users (faculty, students, or other agencies). The DCR collection includes core language curriculum materials developed by each language school—foreign language textbooks, language survival kits, and audio files currently in or not in use at the schools. All core curriculum materials with audio and video files have been coded, collected, and preserved at the DCR. The DCR website was designed with MS SharePoint for easy accessibility by the DLIFLC’s faculty and students. All metadata for the collected curriculum materials have been input by language, code, year, book type, level, user, version, and current status (in use/not in use). The study documents digital curriculum preservation planning, actions, and challenges, including collecting, coding, collaborating, designing DCR SharePoint, and policymaking. DCR Survey data is also collected and analyzed for this research. Based on the finding, the study concludes that the mandatory policy for the DCR system and collaboration with school leadership are critical elements of a successful repository system. The sample collected items, metadata, and DCR SharePoint site are presented in the evaluation section.

Keywords: MS share point, digital preservation, repository, policy

Procedia PDF Downloads 159