Abstract: Today, the mankind is in the stage of development, every day comes with new proposal of technology, in order to secure these types of technology, we also prepare high yielding security modules to conserve these resources. The capacity of human brain to recognize anything is far more than any species; this is all due to our developing cycle of curiosity. In this paper, we proposed a scheme based on graphical password using QR Code which provides more security to the recent online system. It also contains a supportive sound signature. In this system, authentication is done using sequence of images in QR code form. Users select one click-point per image with the help of QR scanner or recognizer. The encoded phrase in a QR code emphasizes the minimum probability of attacking via shoulder surfing or other attacks.
Abstract: In recent few decades, business process management (BPM) has been in focus of a great number of researchers and organizations. There are many benefits derived from the implementation of BPM in organizations. However, there has been also noticed that lately traditional BPM faces some difficulties in terms of the divide between models and their execution, lost innovations, lack of information fusioning and so on. As a result, there has been a new discipline, called social BPM, which incorporates principles of social software into the BPM. On the other hand, many researchers indicate organizational culture as a vital part of the BPM success and maturity. Therefore, the goal of this study is to investigate the current state of BPM maturity and the usage of social BPM among the organizations from Croatia, Slovenia and Austria, with the regards to the organizational culture as well. The paper presents the results of a survey conducted as part of the PROSPER project (IP-2014-09-3729), financed by Croatian Science Foundation. The results indicate differences in the level of BPM maturity, the usage of social BPM and the dominant organizational culture in the observed organizations from different countries. These differences are further discussed in the paper.
Abstract: With this contribution, we want to show how the AiRT system could change the future way of working of a part of the creative industry and what new economic opportunities could arise for them. Remotely Piloted Aircraft Systems (RPAS), also more commonly known as drones, are now essential tools used by many different companies for their creative outdoor work. However, using this very flexible applicable tool indoor is almost impossible, since safe navigation cannot be guaranteed by the operator due to the lack of a reliable and affordable indoor positioning system which ensures a stable flight, among other issues. Here we present our first results of a European project, which consists of developing an indoor drone for professional footage especially designed for the creative industries. One of the main achievements of this project is the successful implication of the end-users in the overall design process from the very beginning. To ensure safe flight in confined spaces, our drone incorporates a positioning system based on ultra-wide band technology, an RGB-D (depth) camera for 3D environment reconstruction and the possibility to fully pre-program automatic flights. Since we also want to offer this tool for inexperienced pilots, we have always focused on user-friendly handling of the whole system throughout the entire process.
Abstract: Open Multiagent Systems (MASs) are societies in
which heterogeneous and independently designed entities (agents)
work towards similar, or different ends. Software agents are
autonomous and the diversity of interests among different members
living in the same society is a fact. In order to deal with this
autonomy, these open systems use mechanisms of social control
(norms) to ensure a desirable social order. This paper considers the
following types of norms: (i) obligation — agents must accomplish
a specific outcome; (ii) permission — agents may act in a particular
way, and (iii) prohibition — agents must not act in a specific way. All
of these characteristics mean to encourage the fulfillment of norms
through rewards and to discourage norm violation by pointing out the
punishments. Once the software agent decides that its priority is the
satisfaction of its own desires and goals, each agent must evaluate
the effects associated to the fulfillment of one or more norms before
choosing which one should be fulfilled. The same applies when agents
decide to violate a norm. This paper also introduces a framework
for the development of MASs that provide support mechanisms
to the agent’s decision-making, using norm-based reasoning. The
applicability and validation of this approach is demonstrated applying
a traffic intersection scenario.
Abstract: Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.
Abstract: Egypt suffers from a severe shortage of data and charts concerning the physical dimensions, measurements, qualities and consumer behavior. The shortage of needed information and appropriate methods has forced the Egyptian designer to use any other foreign standard when designing a product for the Egyptian consumer which has led to many problems. The urgently needed database concerning the physical specifications, measurements of the Egyptian consumers, as well as the need to support the Ergonomics given courses in many colleges and institutes with the latest technologies, is stated as the research problem. Descriptive analytical method relying on the compiling, comparing and analyzing of information and facts in order to get acceptable perceptions, ideas and considerations is the used methodology by the researcher. The research concludes that: 1. Good interaction relationship between users and products shows the success of that product. 2. An integration linkage between the most prominent fields of science specially Ergonomics, Interaction Design and Ethnography should be encouraged to provide an ultimately updated database concerning the nature, specifications and environment of the Egyptian consumer, in order to achieve a higher benefit for both user and product. 3. Chinese economic policy based on the study of market requirements long before any market activities should be emulated. 4. Using Ethnography supports the design activities creating new products or updating existent ones through measuring the compatibility of products with their environment and user expectations, While contracting a joint cooperation between military colleges, sports education institutes from one side, and design institutes from the other side to provide an ultimately updated (annually updated) database concerning some specifications about students of both sexes applying in those institutes (height, weight, etc.) to provide the Industrial designer with the needed information when creating a new product or updating an existing one concerning that category is recommended by the researcher.
Abstract: The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.
Abstract: The selection of specific landmarks for an Unmanned
Aerial Vehicles’ Visual Navigation systems based on Automatic
Landmark Recognition has significant influence on the precision of
the system’s estimated position. At the same time, manual selection
of the landmarks does not guarantee a high recognition rate, which
would also result on a poor precision. This work aims to develop an
automatic landmark selection that will take the image of the flight
area and identify the best landmarks to be recognized by the Visual
Navigation Landmark Recognition System. The criterion to select
a landmark is based on features detected by ORB or AKAZE and
edges information on each possible landmark. Results have shown
that disposition of possible landmarks is quite different from the
human perception.
Abstract: V-notch problem under dynamic loading condition is considered in this paper. In the time domain, the precise time domain expanding algorithm is employed, in which a self-adaptive technique is carried out to improve computing accuracy. By expanding variables in each time interval, the recursive finite element formulas are derived. In the space domain, a Symplectic Analytical Singular Element (SASE) for V-notch problem is constructed addressing the stress singularity of the notch tip. Combining with the conventional finite elements, the proposed SASE can be used to solve the dynamic stress intensity factors (DSIFs) in a simple way. Numerical results show that the proposed SASE for V-notch problem subjected to dynamic loading condition is effective and efficient.
Abstract: This work compares the results of multidimensional
function approximation using two algorithms: the classical Particle
Swarm Optimization (PSO) and the Quantum Particle Swarm
Optimization (QPSO). These algorithms were both tested on three
functions - The Rosenbrock, the Rastrigin, and the sphere functions
- with different characteristics by increasing their number of
dimensions. As a result, this study shows that the higher the function
space, i.e. the larger the function dimension, the more evident the
advantages of using the QPSO method compared to the PSO method
in terms of performance and number of necessary iterations to reach
the stop criterion.
Abstract: This work approaches the automatic planning of paths
for Unmanned Aerial Vehicles (UAVs) through the application of the
Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm.
RRT*-Smart is a sampling process of positions of a navigation
environment through a tree-type graph. The algorithm consists of
randomly expanding a tree from an initial position (root node) until
one of its branches reaches the final position of the path to be
planned. The algorithm ensures the planning of the shortest path,
considering the number of iterations tending to infinity. When a
new node is inserted into the tree, each neighbor node of the
new node is connected to it, if and only if the extension of the
path between the root node and that neighbor node, with this new
connection, is less than the current extension of the path between
those two nodes. RRT*-smart uses an intelligent sampling strategy
to plan less extensive routes by spending a smaller number of
iterations. This strategy is based on the creation of samples/nodes
near to the convex vertices of the navigation environment obstacles.
The planned paths are smoothed through the application of the
method called quintic pythagorean hodograph curves. The smoothing
process converts a route into a dynamically-viable one based on the
kinematic constraints of the vehicle. This smoothing method models
the hodograph components of a curve with polynomials that obey
the Pythagorean Theorem. Its advantage is that the obtained structure
allows computation of the curve length in an exact way, without the
need for quadratural techniques for the resolution of integrals.
Abstract: This paper presents the estimation of the key parameters of a double fed induction machine (DFIM) by the use of the moving horizon estimator (MHE) for control and monitoring purpose. A study was conducted on the behavior of this observer in the presence of some faults which can occur during the operation of the machine. In the first case a stator phase has been suppressed. In the second case the rotor resistance has been multiplied by a factor. The results show a good estimation of different parameters such as rotor flux, rotor speed, stator current with a very small estimation error. The robustness of the observer was also tested in the practical case of DFIM by using another model different from the real one at a constant close. The very small estimation error makes the MHE a good software sensor candidate for monitoring purpose for the DFIM.
Abstract: Food contaminated with biological, chemical and physical hazards usually leads to foodborne illnesses which in turn increase the disease burden of developing and developed economies. Restaurants play a key role in the food service industry and violations in application of standardized food safety management systems in these establishments have been associated with foodborne disease outbreaks. This study was undertaken to assess the level of compliance to the Code of practice that was developed and implemented after conducting needs assessment of the food safety management systems employed by the Food Service Establishments in Ghana. Data on pre-licence inspections were reviewed to assess the compliance of the Food Service Establishments. During the period under review (2012-2016), 74.52% of the food service facilities in the hospitality industry were in compliance with the FDA’s code of practice. Main violations observed during the study bordered on facility layout and fabrication (61.8%) and this is because these facilities may not have been built for use as a food service establishment. Another fact that came to the fore was that the redesigning of the facilities to bring them into compliance required capital intensive investments, which some establishments are not prepared for. Other challenges faced by the industry regarded issues on records and documentations, personnel facilities and hygiene, raw materials acquisition, storage and control, and cold storage.
Abstract: Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.
Abstract: In this paper, a Silicon Controlled Rectifier (SCR)-based Electrostatic Discharge (ESD) protection circuit with high holding voltage and high robustness characteristics is proposed. Unlike conventional SCR, the proposed circuit has low trigger voltage and high holding voltage and provides effective ESD protection with latch-up immunity. In addition, the TCAD simulation results show that the proposed circuit has better electrical characteristics than the conventional SCR. A stack technology was used for voltage-specific applications. Consequentially, the proposed circuit has a trigger voltage of 17.60 V and a holding voltage of 3.64 V.
Abstract: The global warming and its impact on climate change is one of main challenges for current century. Global warming is mainly due to the emission of greenhouse gases (GHG) and carbon dioxide (CO2) is known to be the major contributor to the GHG emission profile. Whilst the energy sector is the primary source for CO2 emission, Carbon Capture and Storage (CCS) are believed to be the solution for controlling this emission. Oxyfuel combustion (Oxy-combustion) is one of the major technologies for capturing CO2 from power plants. For gas turbines, several Oxy-combustion power cycles (Oxyturbine cycles) have been investigated by means of thermodynamic analysis. NetPower cycle is one of the leading oxyturbine power cycles with almost full carbon capture capability from a natural gas fired power plant. In this manuscript, sensitivity analysis of the heat exchanger design in NetPower cycle is completed by means of process modelling. The heat capacity variation and supercritical CO2 with gaseous admixtures are considered for multi-zone analysis with Aspen Plus software. It is found that the heat exchanger design has a major role to increase the efficiency of NetPower cycle. The pinch-point analysis is done to extract the composite and grand composite curve for the heat exchanger. In this paper, relationship between the cycle efficiency and the minimum approach temperature (∆Tmin) of the heat exchanger has also been evaluated. Increase in ∆Tmin causes a decrease in the temperature of the recycle flue gases (RFG) and an overall decrease in the required power for the recycled gas compressor. The main challenge in the design of heat exchangers in power plants is a tradeoff between the capital and operational costs. To achieve lower ∆Tmin, larger size of heat exchanger is required. This means a higher capital cost but leading to a better heat recovery and lower operational cost. To achieve this, ∆Tmin is selected from the minimum point in the diagrams of capital and operational costs. This study provides an insight into the NetPower Oxy-combustion cycle’s performance analysis and operational condition based on its heat exchanger design.
Abstract: Obesity is a low-grade inflammatory disease and may lead to health problems such as hypertension, dyslipidemia, diabetes. It is also associated with important risk factors for cardiovascular diseases. This requires the detailed evaluation of obesity, particularly in children. The aim of this study is to enlighten the potential associations between lipid ratios and obesity indices and to introduce those with discriminating features among children with obesity and metabolic syndrome (MetS). A total of 408 children (aged between six and eighteen years) participated in the scope of the study. Informed consent forms were taken from the participants and their parents. Ethical Committee approval was obtained. Anthropometric measurements such as weight, height as well as waist, hip, head, neck circumferences and body fat mass were taken. Systolic and diastolic blood pressure values were recorded. Body mass index (BMI), diagnostic obesity notation model assessment index-II (D2 index), waist-to-hip, head-to-neck ratios were calculated. Total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDLChol), low-density lipoprotein cholesterol (LDLChol) analyses were performed in blood samples drawn from 110 children with normal body weight, 164 morbid obese (MO) children and 134 children with MetS. Age- and sex-adjusted BMI percentiles tabulated by World Health Organization were used to classify groups; normal body weight, MO and MetS. 15th-to-85th percentiles were used to define normal body weight children. Children, whose values were above the 99th percentile, were described as MO. MetS criteria were defined. Data were evaluated statistically by SPSS Version 20. The degree of statistical significance was accepted as p≤0.05. Mean±standard deviation values of BMI for normal body weight children, MO children and those with MetS were 15.7±1.1, 27.1±3.8 and 29.1±5.3 kg/m2, respectively. Corresponding values for the D2 index were calculated as 3.4±0.9, 14.3±4.9 and 16.4±6.7. Both BMI and D2 index were capable of discriminating the groups from one another (p≤0.01). As far as other obesity indices were considered, waist-to hip and head-to-neck ratios did not exhibit any statistically significant difference between MO and MetS groups (p≥0.05). Diagnostic obesity notation model assessment index-II was correlated with the triglycerides-to-HDL-C ratio in normal body weight and MO (r=0.413, p≤0.01 and r=0.261, (p≤0.05, respectively). Total cholesterol-to-HDL-C and LDL-C-to-HDL-C showed statistically significant differences between normal body weight and MO as well as MO and MetS (p≤0.05). The only group in which these two ratios were significantly correlated with waist-to-hip ratio was MetS group (r=0.332 and r=0.334, p≤0.01, respectively). Lack of correlation between the D2 index and the triglycerides-to-HDL-C ratio was another important finding in MetS group. In this study, parameters and ratios, whose associations were defined previously with increased cardiovascular risk or cardiac death have been evaluated along with obesity indices in children with morbid obesity and MetS. Their profiles during childhood have been investigated. Aside from the nature of the correlation between the D2 index and triglycerides-to-HDL-C ratio, total cholesterol-to-HDL-C as well as LDL-C-to- HDL-C ratios along with their correlations with waist-to-hip ratio showed that the combination of obesity-related parameters predicts better than one parameter and appears to be helpful for discriminating MO children from MetS group.
Abstract: A mathematical model for knowledge acquisition in
teaching and learning is proposed. In this study we adopt the
mathematical model that is normally used for disease modelling
into teaching and learning. We derive mathematical conditions which
facilitate knowledge acquisition. This study compares the effects
of dropping out of the course at early stages with later stages of
learning. The study also investigates effect of individual interaction
and learning from other sources to facilitate learning. The study fits
actual data to a general mathematical model using Matlab ODE45
and lsqnonlin to obtain a unique mathematical model that can be
used to predict knowledge acquisition. The data used in this study
was obtained from the tutorial test results for mathematics 2 students
from the Central University of Technology, Free State, South Africa
in the department of Mathematical and Physical Sciences. The study
confirms already known results that increasing dropout rates and
forgetting taught concepts reduce the population of knowledgeable
students. Increasing teaching contacts and access to other learning
materials facilitate knowledge acquisition. The effect of increasing
dropout rates is more enhanced in the later stages of learning
than earlier stages. The study opens up a new direction in further
investigations in teaching and learning using differential equations.
Abstract: The Jalovchat intrusive is built up of hornblende gabbros, gabbro-norites and norites. Within the intrusive hornblende-bearing gabbro-pegmatites are widespread. That is a coarse-grained rock with gigantic hornblende crystals. By its unusual composition, the Jalovchat intrusive has no analogue in the Caucasus. However, petrologically and geochemically, the intrusive rocks were studied insufficiently. For comprehensive investigations, the authors applied appropriate methodologies: Microscopic study of thin sections, petro- and geochemical analyses of the samples and also different petrogenic, rare and rare earth elements diagrams and spidergrams. Analytical study established that the Jalovchat intrusive by its composition corresponds mainly to the mid-ocean ridge basalts and according to geodynamic type belongs to the subduction type. In general, it is an anomalous phenomenon, as in the rocks of such composition crystallization of hornblende and especially of its gigantic crystals is atypical. The authors believe that the water-rich magma reservoir, which was necessary for the crystallization of gigantic hornblende crystals, appeared as a result of melting of water-rich mid-ocean ridge basaltic rocks during the subduction process in Bajocian time.
Abstract: Emergency Core Coolant Bypass (ECC Bypass) has been regarded as an important phenomenon to peak cladding temperature of large-break loss-of-coolant-accidents (LBLOCA) in nuclear power plants (NPP). A modeling scheme to address the ECC Bypass phenomena and the calculation of LBLOCA using that scheme are discussed in the present paper. A hydraulic form loss coefficient (HFLC) from the reactor vessel downcomer to the broken cold leg is predicted by the computational fluid dynamics (CFD) code with a variation of the void fraction incoming from the downcomer. The maximum, mean, and minimum values of FLC are derived from the CFD results and are incorporated into the LBLOCA calculation using a system thermal-hydraulic code, MARS-KS. As a relevant parameter addressing the ECC Bypass phenomena, the FLC to the break and its range are proposed.