Computing

In many cases poor information quality appears mainly due to in-effectiveness of information management including information production and delivery. Where this situation poses a certain risk. A holistic information risk management model has been previously proposed. But the model has some limitations especially on risk calculation and risk priority ranking as the model does not consider existing control effectiveness. In this paper, a new risk assessment method is proposed in order to improve the model of total impact of risks and to improve the accuracy of risk priority ranking by modifying the extended risk matrix approach (RMA) where we take into account the existing control effectiveness. Using our approach by adding a new dimension on extended RMA. We are able to improve the accuracy (7.15%) and reduced the ambiguity (1.34) of assessment results on real cases illustration.

Open source software (OSS) in academia can have multiple types of implementations and positive returns. This paper explores the use of OSS as a method to teach entrepreneurship concepts and practices to Science, Technology, Engineering, and Mathematics (STEM) majors. OSS allows for individuals to contribute and provide support services for applications. This will allow students to gain expertise in low level design, software project management, and software consulting services in order to successfully deploy their own spin off company. Covered in this submission will be examples of how the Linux software project development groups, mobile application development, video game design, and support services can be used in the classroom. These examples will serve as the base for any additions or changes in curriculum development, and design to aid institutions in deploying innovative programs in technology entrepreneurship to STEM students.

Motivated by some recent research on the terminal (reduced) distance matrix, we consider the terminal Wiener index (T W ) of trees, equal to the sum of distances between all pairs of pendent vertices. A simple formula for computing T W is obtained and the trees with minimum and maximum T W are characterized.

Until now, Augmented Reality was mainly associated with visual augmentation which was often reduced to superimposing a virtual object on to a real world. We present in this document a vibro-tactile system called HaptiNav, which illustrates the concept of Haptic Augmented Reality. We use the haptic feedback method to send users information about their direction, thus enabling them to reach their destination. To do so, we use a turn by turn metaphor which consists of dividing the route into many reference points. In order to assess the performances of the HaptiNav system, we carry out an experimental study in which we compare it to both Google Maps Audio and Pocket Navigator systems. The results show that there is no significant difference between HaptiNav and Google Maps Audio in terms of performance, physical load and time. However, statistical analysis of the mental load, frustration and effort highlights the advantages of HaptiNav compared to two other systems. In the light of the...

A Computational Study of Redundancy in Randomly Generated Polytopes. In this paper we first survey a number of principles used to randomly generate linear programming problems. Three major classes of LP generators are identified and :on that basis five generators for further study are defined. In a series of tests the average degree of redundancy of problems generated by these generators is determined. The evaluation of the results also develops an indicator for the expected degree of redundancy of a problem.

We survey and extend the work on the paradigm called "computing by observing". Its central feature is that one considers the behavior of an evolving system as the result of a computation. To this purpose an external observer records this behavior. In this way, several computational trade-offs between the observer and the observed system can be determined. It has turned out that the observed behavior of computationally simple systems can be very complex, when an appropriate observer is used. For example, a restricted version of context-free grammars with regular observers suffices to obtain computational completeness. As a second instantiation presented here, we apply an observer to sticker systems, an abstract model of DNA computing. Finally, we introduce and investigate the case where the observers can read only one measure of the observed system (e.g., mass or temperature) modeling in this way, limitations in the observation of real physical systems. Finally a research perspective on the topic is presented.

The mapping algorithms address the problem of acquiring spatial models of physical environments using mobile robots. We will focus on using the indoor exploration algorithms to construct a map for such environment. Therefore, the problem under consideration lies ...

El presente artículo pretende brindar luces acerca de la importancia de la Psicología Organizacional en el ámbito laboral y ayudarnos a comprender cómo ésta puede resolver conflictos en la organización complementándose con diferentes ámbitos profesionales. Los autores, no psicólogos, que cursan el último semestre de la Maestría con mención en Psicología Organizacional de la UNMSM, expondrán la utilidad que la Psicología Organizacional les brinda en su quehacer profesional aplicado en las organizaciones donde ellos se desempeñan.

An Internet of Things (IoT) middleware can solve interoperability problem among "things" in IoT infrastructure by collecting data. However, the sensor nodes' data that is collected by the middleware cannot be directly delivered to cloud applications since the sensor nodes and the middleware are located in intranet. A solution to this problem is an Internet Gateway Device (IGD) that retrieves data from the middleware in intranet then forwards them to cloud applications in the internet. In this study, an IGD based on cellular network is proposed to provide wide-coverage internet connectivity. Two test scenarios were conducted to measure delay and throughput between the IGD and the cloud application; using data from DHT22 sensor and image sensor respectively. The results of the first test scenario using DHT22 sensor show that the average delay is under 5 seconds and the maximum throughput is 120 bps, while the second one using image sensor concludes that the average delay is 595 seconds and the maximum throughput is 909 bps.

Automation of several payment processes from start to end is a challenging task, particularly when multiple payments from online and offline billers are involved. In this paper, we introduced a new aggregator system to combine all billing system types, in which it is possible to pay invoices electronically. The proposed aggregator system was designed to be employed in a cloud-based billers hub (CBBH) developed by the central banks. Furthermore, many applications can be realized such as; deposit e-money, withdrawal e-money, and other applications. A Gateway translator is used to apply authentication rules, security, and privacy. The proposed system was employed in the Jordanian payment gateway and successfully fulfills its purpose.

Recently, both companion-matrix methods and subdivision algorithms have been developed for finding the zeros of a truncated spectral series. Since the Chebyshev or Legendre coefficients of derivatives of a function f (x) can be computed by trivial recurrences from those of the function itself, it follows that finding the maxima, minima and inflection points of a truncated Chebyshev or Fourier series f N (x) is also a problem of finding the zeros of a polynomial when written in truncated Chebyshev series form, or computing the roots of a trigonometric polynomial. Widely scattered results are reviewed and a few previously unpublished ideas sprinkled in. There are now robust zerofinders for all species of spectral series. A transcendental function f (x) can be approximated arbitrarily well on a real interval by a truncated Chebyshev series f N (x) of sufficiently high degree N. It follows that through Chebyshev interpolation and Chebyshev rootfinders, it is now possible to easily find all the real roots on an interval for any smooth transcendental function.

This paper proposes Cognitive Artificial Intelligence (CAI) method for Dissolved Gas Analysis (DGA) interpretation adopting Doernenburg Ratio method. CAI works based on Knowledge Growing System (KGS) principle and is capable of growing its own knowledge. Data are collected from sensors, but they are not the information itself, and thus, data needs to be processed to extract information. Multiple information are then fused in order to obtain new information with Degree of Certainty (DoC). The new information is used to identify faults occurred at a single observation. The proposed method is tested using the previously published dataset and compared with Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Experiment shows CAI implementation on Doernenburg Ratio performs 115 out of 117 accurate identification, followed by Fuzzy Inference System 94.02% and ANN 78.6%. CAI works well even with small amount of data and does not require trainings.

Computers have a direct impact on our lives nowadays. Human's interaction with the computer has modified with the passage of time as improvement in technology occurred the better the human computer interaction became. Today we are facilitated by the operating system that has reduced all the complexity of hardware and we undergo our computation in a very convenient way irrespective of the process occurring at the hardware level. Though the human computer interaction has improved but it's not done yet. If we come to the future the computer's role in our lives would be a lot more rather our life would be of the artificial intelligence. In our future the biggest resource would be component of time and wasting time for a key board entry or a mouse input would be unbearable so the need would be of the computer interaction environment that along with the complexity reduction also minimizes the time wastage in the human computer interaction. Accordingly in our future the computation would also be increased it would not be a simple operating system limited to a computer it would be computers managing our entire life activities hence fall out of domain of present computers electronic based architecture .In this research paper we propose a model that shall be meeting the future human computer interaction needs possessing linguistic human computer interference environment based on surface technology, automation and photonic computing, which would be reliable, efficient and quicker satisfying all the future artificial intelligence pre requisites.

Document Standard Operating Procedures (SOP) can manage business processes and employee performance in an organization. This study aims to develop a system that can publish SOP documents automatically distributed to employees. In this study, an analysis of the relationship between SOP documents and employees is carried out so that it can be directly allocated to employees according to the position. Knowledge analysis of the relationship between SOP documents and employees is done using semantic network analysis. Semantic networks are used to analyze components of knowledge and the relationship between SOP documents and employees. The results of the report of the elements of knowledge and the relationship between SOP documents found 25 SOP documents were consisting of 6 types of central nodes with 156 child nodes and had 7 types of relations containing 207 relations. SOP knowledge management system is connected to the personnel information system (SIPEG) so that it makes it easier for users to find, accommodate, and manage the knowledge contained in SOP documents. System implementation is done using PHP programming language with CodeIgniter framework, Rest API, and MySQL database.

Load balancing functionalities are crucial for best Grid performance and utilization. Accordingly,this paper presents a new meta-scheduling method called TunSys. It is inspired from the natural phenomenon of heat propagation and thermal equilibrium. TunSys is based on a Grid polyhedron model with a spherical like structure used to ensure load balancing through a local neighborhood propagation strategy. Furthermore, experimental results compared to FCFS, DGA and HGA show encouraging results in terms of system performance and scalability and in terms of load balancing efficiency.

Imaging spectrometry, or hyperspectral imaging as it is now called, has had a long history of development and measured acceptance by the scientific community. The impetus for the development of imaging spectrometry came in the 1970's from field spectral measurements in support of Landsat-1 data analysis. Progress required developments in electronics, computing and software throughout the 1980's and into the 1990's before a larger segment of the Earth observation community would embrace the technique. The hardware development took place at NASA/JPL beginning with the Airborne Imaging Spectrometer (AIS) in 1983. The airborne visible/infrared imaging spectrometer (AVIRIS) followed in 1987 and has proved to this day to be the prime provider of high-quality hyperspectral data for the scientific community. Other critical elements for the exploitation of this data source have been software, primarily ENVI, and field spectrometers such as those produced by Analytical Spectral Devices Inc. In addition, atmospheric correction algorithms have made it possible to reduce sensor radiance to spectral reflectance, the quantity required in all remote sensing applications. The applications cover the gambit of disciplines in Earth observations of the land and water. The further exploitation of hyperspectral imaging on a global basis awaits the launch of a high performance imaging spectrometer and more researchers with sufficient resources to take advantage of the vast information content inherent in the data.

In this paper, we consider smooth words over 2-letter alphabets {a, b}, where a, b are integers having same parity, with 0 < a < b. We show that all are recurrent and that the closure of the set of factors under reversal holds for odd alphabets only. We provide a linear time algorithm computing the extremal words, w.r.t. lexicographic order. The minimal word is an infinite Lyndon word if and only if either a = 1 and b are odd, or a, b are even. A connection is established between generalized Kolakoski words and maximal infinite smooth words over even 2-letter alphabets revealing new properties for some of the generalized Kolakoski words. Finally, the frequency of letters in extremal words is 1/2 for even alphabets, and for a = 1 with b odd, the frequency of b's is 1/( √ 2b − 1 + 1).

The concept of the Internet of Things (IoT) is closely related to the concepts of Cyber-Physical System (CPS) and Cyber-Physical-Social System (CPSS). A key feature of these technologies is the integration of the virtual and physical world. In this paper, an environment for ambient-oriented modeling called AmbiNet is presented. The environment AmbiNet is implemented as a component of the reference architecture known as Virtual Physical Space (ViPS) that can be adapted for CPSS applications in various domains, for example a smart city, a personal touristic guide, or education. The need for virtualization of things from the physical world in a formal way is also considered. In the paper, the usability of the environment is demonstrated by modeling of services delivered to tourists in an intelligent city. The architecture of ViPS is also briefly described. Furthermore, the virtualization and modeling of spatial aspects through the AmbiNet formalism is demonstrated by an example.

Interpolants for Runge-Kutta-Nystriim Methods. Hermite interpolation polynomials arc developed for use with low order Runge-Kutta-Nystr6m methods in producing continuous approximate solutions to second order initial value problems, polynomials of degrees five and four, which interpolate te solution and derivative components, respectively, are easily computable and require no extra stages. Interpolants of the next higher orders are obtained at the cost of two additional stages per integration step. The interpolation procedure is demonstrated using two recently developed Runge-Kutta-Nystr6m methods. Numerical experimentation reveals some aspects of the performance of these interpolants.

Both Governments and people around the world have started appreciating the ability of Information and Communications Technology (ICT) to stimulate critical sectors of the economy. These technological innovations provide speedy, inexpensive and convenient means of communications. The adoption of these innovative technologies in many countries by different sectors of the economy has been found to have direct positive impact on the nation's efficiency, productivity and have led to a rapid development.

Performance is a key feature of large-scale computing systems. However, the achieved performance when a certain program is executed is significantly lower than the maximal theoretical performance of the large-scale computing system. The model-based performance evaluation may be used to support the performance-oriented program development for large-scale computing systems. In this paper we present a hybrid approach for performance modeling and prediction of parallel and distributed computing systems, which combines mathematical modeling and discrete-event simulation. We use mathematical modeling to develop parameterized performance models for components of the system. Thereafter, we use discreteevent simulation to describe the structure of system and the interaction among its components. As a result, we obtain a highlevel performance model, which combines the evaluation speed of mathematical models with the structure awareness and fidelity of the simulation model. We evaluate empirically our approach with a real-world material science program that comprises more than 15,000 lines of code.

One of the main causes of traffic congestion, especially at intersections, is because traffic lights have not been able to show the right time according to the existing traffic conditions. Time settings based on peak/off-peak traffic lights are not enough to handle unexpected situations. The fuzzy mamdani method makes decisions with several stages, the criteria used are the number of vehicles, the length of the queue and the width of the road to be able to optimize the time settings based on the real-time conditions required so that unwanted green signals (when there is no queue) can be avoided. The purpose of this research is to create a simulator to optimize traffic time management, so that the timers on each track have the intelligence to predict the right time, so that congestion at the intersection can be reduced by adding up to 15 seconds of green light from the previous time in the path of many vehicles.

In mission critical systems a single failure might cause catastrophic consequences. This sets high expectations to timely detection of design faults and runtime failures. By traditional software testing methods the detection of deeply nested faults that occur sporadically is almost impossible. The discovery of such bugs can be facilitated by generating well-targeted test cases where the test scenario is explicitly specified. On the other hand, the excess of implementation details in manually crafted test scripts makes it hard to understand and to interpret the test results. This paper defines high-level test scenario specification language TDLTP for specifying complex test scenarios that are relevant for model-based testing of mission critical systems. The syntax and semantics of TDLTP operators are defined and the transformation rules that map its declarative expressions to executable Uppaal Timed Automata test models are specified. The scalability of the method is demonstrated on ...

The aim of study is to discover outlier of customer data to found customer behaviour. The customer behaviour determined with RFM (Recency, Frequency and Monetary) models with K-Mean and DBSCAN algorithm as clustering customer data. There are six step in this study. The first step is determining the best number of clusters with the dunn index (DN) validation method for each algorithm. Based on the dunn index, the best cluster values were 2 clusters with DN value for DBSCAN 1.19 which were minpts and epsilon value 0.2 and 3 and DN for K-Means was 1.31. The next step was to cluster the dataset with the DBSCAN and K-Means algorithm based on the best cluster that was 2. DBSCAN algorithm had 37 outliers data and K-means algorithm had 63 outliers (cluster 1 are 26 outliers and cluster 2 are 37 outliers). This research shown that outlier in DBSCAN and K-Means in cluster 1 have similarities is 100%. But overal outliers similarities is 67%. Based the outliers shown that the behaviour of customers is a small frequency of spending but high recency and monetary.

The problem of predicting a future value of a time series is considered in this paper. If the series follows a stationary Markov process, this can be done by nonparametric estimation of the autoregression function. Two forecasting algorithms are introduced. They only differ in the nonparametric kernel-type estimator used: the Nadaraya-Watson estimator and the local linear estimator. There are three major issues in the implementation of these algorithms: selection of the autoregressor variables; smoothing parameter selection and computing prediction intervals. These have been tackled using recent techniques borrowed from the nonparametric regression estimation literature under dependence. The performance of these nonparametric algorithms has been studied by applying them to a collection of 43 well-known time series. Their results have been compared to those obtained using classical Box-Jenkins methods. Finally, the practical behaviour of the methods is also illustrated by a detailed analysis of two data sets.

One of the most significant innovation in the Information Technology (IT) industry after the introduction of the personal computer and the internet is Cloud computing. The shift to cloud is a landmark in the IT industry and has raised keen interest both from the industrial community and academia. It is a new virtualization model for the quick provisioning of shared resources, software, applications and services over the internet to fulfill the elastic demand of the customer with minimum effort or interaction with the service provider. Thus cloud computing has become an interesting and increasingly essential trend. This paper presents a detailed review of Cloud Computing. It includes a discussion of the main service model of cloud computing, the general deployment models, the characteristics of Cloud computing and terminologies adopted in cloud computing. The paper also presents the trend of cloud computing and its challenges.

8th International Conference on Computational Science and Engineering (CSE 2020)
focuses on Complex systems, information and computation using mathematics and
engineering techniques. This conference will act as a major forum for the presentation of
innovative ideas, approaches, developments, and research projects in the area of Computation
theory and applications. It will also serve to facilitate the exchange of information between
researchers and industry professionals to discuss the latest issues and advancement in the area
of advanced Computation and its applications will be covered during the conference

This research explores the accessibility issues with regard to the e-commerce websites in developing countries, through a study of Sri Lankan hotel websites. A web survey and a web content analysis were conducted as the methods to elicit data on web accessibility. Factors preventing accessibility were hypothesized as an initial experiment. Affecting design elements are identified through web content analysis, the results of which are utilized to develop specific implications for improving web accessibility. The hypothesis tests show that there is no significant correlation between accessibility and geographical or economic factors. However, physical impairments of users have a considerable influence on the accessibility of web page user interface if it has been designed without full consideration of the needs of all users. Especially, visual and mobility impaired users experience poor accessibility. Poor readability and less navigable page designs are two observable issues, which pose threats to accessibility. The lack of conformance to W3C accessibility guidelines and the poor design process are the specific shortcomings which reduce the overall accessibility. Guidelines aim to improve the accessibility of sites with a strategic focus. Further enhancements are suggested with adherence to principles, user centered design and developing customizable web portals compatible for connections with differing speeds. Re-ordering search results has been suggested as one of the finest step towards making the web content accessible for users with differing needs. A need for developing new design models for differencing user groups and implementing web accessibility strategy are emphasized as vital steps towards effective information dissemination via e-commerce websites in the developing countries.

One of the main challenges students in introductory programming courses face is learning the syntax of a particular programming language, such as C++ or Java, while they simultaneously try to understand the fundamental logic of programming constructs. Visual Logic© (www.visuallogic.org) is an interactive, graphical, flowchart tool that can be used to address this challenge. In this paper, we present three different courses, developed independently at three different colleges, using Visual Logic with completely different approaches. The first course is a General Education CS course introducing algorithmic thinking. The second is a CS0 course which uses Visual Logic for six weeks and then transitions to Python. The third course is a CS1 course which uses Visual Logic as a tool to teach programming concepts and to brainstorm solutions. Visual Logic is not taught separately, but integrated with the various Java control structures. Once students gain an understanding of basic programming logic concepts, the transition to a programming language such as Python or Java, in the same course or the next course, is often much easier for them. Though these are different approaches in three different courses, using Visual Logic has shown an increase in the interest level of the students and enhanced their learning.

Efficient Classes of Runge-Kutta Methods for Two-Point Boundary Value Problems. The standard approach to applying IRK methods in the solution of two-point boundary value problems involves the solution of a non-linear system ofn x s equations in order to calculate the stages of the method, where n is the number of differential equations and s is the number of stages of the implicit Runge-Kutta method. For two-point boundary value problems, we can select a subset of the implicit Runge-Kutta methods that do not require us to solve a non-linear system; the calculation of the stages can be done explicitly, as is the case for explicit Runge-Kutta methods. However, these methods have better stability properties than the explicit Runge-Kutta methods. We have called these new formulas two-point explicit Runge-Kutta (TPERK) methods. Their most important property is that, because their stages can be computed explicitly, the solution of a two-point boundary value problem can be computed more efficiently than is possible using an implicit Runge-Kutta method. We have also developed a symmetric subclass of the TPERK methods, called ATPERK methods, which exhibit a number of useful properties.

Meaning is the essence. It is the primary reason for us to keep doing things. Meaning is both significance and the endless unfolding of significance. Visual Meaning is fundamental for visual arts and design processes. One draws, paints, sculpts, throws sponges on the wall, dips one's own body into paint and crawls on the ground or codes to create lines, spots or fields (Knight), all of which are then looked into, perceived and iterated. Vision is so important that Alberti's eye becomes a godly creature with wings that flies among thunderstorms, Kepler's eye becomes a perfect machine through which stars and galaxies leaks (Alpers), Vermeer's eye becomes the ultimate light filter and depicter. Finally Stiny's eye establishes a "unique computational theory: Shape Grammars" (Knight and Stiny). And all this happens in a series of places (Casey), as one wanders through streams of creative visual processes along one's humaning (Ingold). Once I portray the moment of visual discovery as an encounter, the artists and the designer as encounterers and the computer as the counter, I ask: can the ultimate counter [the computer] provide true encounters for creative visual processes? Computing visual meaning -- it really possible? I unfold these questions by introducing a visual-making apparatus around which all scientifically separated players, the encounter, the encounterer and the counter become interwoven in one place. Visual-making, similar to living, requires us to twist, bend, embrace and abandon. The human-be-comput-ing tree grows to introduce a novel model for drawing and painting, for humaning. An uncommon place for discovering and computing visual meanings, the Broadened-Drawing Scape, emerges.

Mathematics is the abstract science of number, quantity, and space, either as abstract concepts (pure mathematics), or as applied to other disciplines such as physics and engineering (applied mathematics). Computing, finance, business, etc., should be included in this definition, in fact I think sciences and commercial should be the key definition. So in my definition I would say mathematics as an easy theoretical or conceptual science of digits, quantity, and space, either as abstract (pure mathematics), or as applied (applied mathematics) to other disciplines such as physics, engineering, computing, geography, etc., (sciences) and business administration, auditing, finance, (commercial). Mathematics may be defined as " the study of relationships among quantities, magnitudes and properties, and also of the logical operations by which unknown quantities, magnitudes, and properties may be deduced " (Microsoft Encarta Encyclopedia), Historically, it was regarded as the science of quantity, whether of magnitudes (as in geometry) or of numbers (as in arithmetic) or of the generalization of these two fields (as in algebra). Some have seen it in terms as simple as a search for patterns (algorithm). We would consider mathematics its significance, benefits and deficiencies in computing sciences and engineering in Nigeria.

The study aims to assess the students' continuance intention (SCI) in using multimedia online learning including students' perceived usefulness (SPU), students' ease of use (SPE), and students' flow experience (SFE). There is no, so far, assessment of students' activity in using multimedia online learning within the extended Technology Acceptance Model (TAM).There were 523 students as the samples. They learned and examined the content of online English learning resources as well as multimedia aspects.TAM was used to predict the SCI. The results indicate that the students' intentions are influenced positively by perceived usefulness, ease of use, and the flow experience. The SPU influenced more students' motivation than SPE. It is recommended that designers of online learning should be more specific in determining target users. The online learners' skill on ICT, pedagogical principles, and technological barrier in different region are among the determinant aspects for receiving positive enduring intention.

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This is an article that was written for the Computer Science Teachers Association (CSTA) of the United States of America journal, entitled The CSTA Voice.  It was published in the May 2017 issue of the journal, Volume 13, Issue 2 and highlights some of the key changes and decisions that affected ICT teachers in the United Kingdom during the period of change between ICT and Computing.  In the article, I discuss my experiences in managing that change as the head of department in a large secondary school and also the strategies employed in order to make the transition as smooth as possible.

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to most related previous work, in this task we are constrained to using low-level, spatio-temporally local motion features only. This particular challenge arises in many semi-automatic surveillance systems which alert a human operator to potential abnormalities in the scene. Low-level, spatio-temporally local motion features are sparse (and thus require comparatively little storage space) and sufficiently powerful in the context of video abnormality detection to reduce the need for human intervention by more than 100-fold. This paper introduces three significant contributions: (i) we describe a dense algorithm for perspective estimation which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) we also present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to derive block-specific motion characteristics and constrain the relationships between these characteristics, with the perspective estimate emerging as a result of a global optimization scheme, and (iii) we report the results of an evaluation using nine large sets acquired using existing close-circuit television (CCTV) cameras, not installed specifically for the purposes of this work. Our findings demonstrate that both of the proposed methods are successful, their accuracy matching that of human labelling using complete visual data (by the constraints of the setup unavailable to our algorithms).

The growth in numbers and capacity of mobile devices such as mobile phones coupled with widespread availability of inexpensive range of biosensors presents an unprecedented opportunity for mobile healthcare applications. In this paper we propose a novel approach for Situation-Aware Adaptive Processing (SAAP) of data streams for smart and real-time analysis of data. The implementation and evaluation of the framework for a health monitoring application is described.