Abstract: Systems transforming solar energy into electrical power have emerged as a viable source of clean, renewable energy. Solar power tower technology is a good example of this type of system, which consists of several mobile mirrors, called heliostats, which reflect the sun's radiation to the same point, located on top of a tower at the center of heliostat field, for collection or transformation into another type of energy. The so-called Hermosillo’s Solar Platform (Plataforma Solar de Hermosillo, PSH, in Spanish) is a facility constituted with several heliostats, its aim and scope is for research purposes. In this paper, the implementation of a wireless communication system based on intelligent nodes is proposed in order to allow the communication and control of the heliostats in PSH. Intelligent nodes transmit information from one point to another, and can perform other actions that allow them to adapt to the conditions and limitations of a field of heliostats, thus achieving effective communication system. After deployment of the nodes in the heliostats, tests were conducted to measure the effectiveness of the communication, and determine the feasibility of using the proposed technologies. The test results were always positive, exceeding expectations held for its operation in the field of heliostats. Therefore, it was possible to validate the efficiency of the wireless communication system to be implemented in PSH, allowing communication and control of the heliostats.
Abstract: Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.
Abstract: Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.
Abstract: The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.
Abstract: Younger and younger children are now using a smartphone, a device which has become ‘a must have’ and the life of children would be almost ‘unthinkable’ without one. Devices are becoming lighter and lighter but offering an array of options and applications as well as the unavoidable access to the Internet, without which it would be almost unusable. Numerous features such as taking of photographs, listening to music, information search on the Internet, access to social networks, usage of some of the chatting and messaging services, are only some of the numerous features offered by ‘smart’ devices. They have replaced the alarm clock, home phone, camera, tablet and other devices. Their use and possession have become a part of the everyday image of young people. Apart from the positive aspects, the use of smartphones has also some downsides. For instance, free time was usually spent in nature, playing, doing sports or other activities enabling children an adequate psychophysiological growth and development. The greater usage of smartphones during classes to check statuses on social networks, message your friends, play online games, are just some of the possible negative aspects of their application. Considering that the age of the population using smartphones is decreasing and that smartphones are no longer ‘foreign’ to children of pre-school age (smartphones are used at home or in coffee shops or shopping centers while waiting for their parents, playing video games often inappropriate to their age), particular attention must be paid to a very sensitive group, the teenagers who almost never separate from their ‘pets’. This paper is divided into two sections, theoretical and empirical ones. The theoretical section gives an overview of the pros and cons of the usage of smartphones, while the empirical section presents the results of a research conducted in three elementary schools regarding the usage of smartphones and, specifically, their usage during classes, during breaks and to search information on the Internet, check status updates and 'likes’ on the Facebook social network.
Abstract: Formulation of a low oil-water ratio drilling mud with vegetable oil continuous phase without adversely affecting the mud rheology and stability has been a major challenge. A low oil-water ratio is beneficial in producing low fluid loss which is essential for wellbore stability. This study examined the possibility of 50/50 oil-water ratio invert emulsion drilling mud using a vegetable oil continuous phase. Jatropha oil was used as continuous phase. 12 ml of egg yolk which was separated from the albumen was added as the primary emulsifier additive. The rheological, stability and filtration properties were examined. The plastic viscosity and yield point were found to be 36cp and 17 Ib/100 ft2 respectively. The electrical stability at 48.9ºC was 353v and the 30 minutes fluid loss was 6ml. The results compared favourably with a similar formulation using 70/30 oil - water ratio giving plastic viscosity of 31cp, yield point of 17 Ib/100 ft2, electrical stability value of 480v and 12ml for the 30 minutes fluid loss. This study indicates that with a good mud composition using guided empiricism, 50/50 oil-water ratio invert emulsion drilling mud is feasible with a vegetable oil continuous phase. The choice of egg yolk as emulsifier additive is for compatibility with the vegetable oil and environmental concern. The high water content with no fluid loss additive will also minimise the cost of mud formulation.
Abstract: In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.
Abstract: Background: Plantar pressure measurement is an effective method for assessing plantar loading and can be applied to evaluating movement performance of the foot. The purpose of this study is to explore the sprint athletes’ plantar loading characteristics and pain profiles in static standing. Methods: Experiments were undertaken on 80 first-division college sprint athletes and 85 healthy non-sprinters. ‘JC Mat’, the optical plantar pressure measurement was applied to examining the differences between both groups in the arch index (AI), three regional and six distinct sub-regional plantar pressure distributions (PPD), and footprint characteristics. Pain assessment and self-reported health status in sprint athletes were examined for evaluating their common pain areas. Results: Findings from the control group, the males’ AI fell into the normal range. Yet, the females’ AI was classified as the high-arch type. AI values of the sprint group were found to be significantly lower than the control group. PPD were higher at the medial metatarsal bone of both feet and the lateral heel of the right foot in the sprint group, the males in particular, whereas lower at the medial and lateral longitudinal arches of both feet. Footprint characteristics tended to support the results of the AI and PPD, and this reflected the corresponding pressure profiles. For the sprint athletes, the lateral knee joint and biceps femoris were the most common musculoskeletal pains. Conclusions: The sprint athletes’ AI were generally classified as high arches, and that their PPD were categorized between the features of runners and high-arched runners. These findings also correspond to the profiles of patellofemoral pain syndrome (PFPS)-related plantar pressure. The pain profiles appeared to correspond to the symptoms of high-arched runners and PFPS. The findings reflected upon the possible link between high arches and PFPS. The correlation between high-arched runners and PFPS development is worth further studies.
Abstract: Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.
Abstract: Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.
Abstract: Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.
Abstract: In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.
Abstract: This paper compares the findings of two studies conducted to determine the effectiveness of simulation-based, hands-on and feedback mechanism on students learning by answering the following questions: 1). Does the use of simulation improve students’ learning outcomes? 2). How do students perceive the instructional design features embedded in the simulation program such as exploration and scaffolding support in learning new concepts? 3.) What is the effect of feedback mechanisms on students’ learning in the use of simulation-based labs? The paper also discusses the other aspects of findings which reveal that simulation by itself is not very effective in promoting student learning. Simulation becomes effective when it is followed by hands-on activity and feedback mechanisms. Furthermore, the paper presents recommendations for improving student learning through the use of simulation-based, hands-on, and feedback-based teaching methodologies.
Abstract: Fault diagnosis of Linear Parameter-Varying (LPV)
system using an adaptive Kalman filter is proposed. The LPV model
is comprised of scheduling parameters, and the emulator parameters.
The scheduling parameters are chosen such that they are capable of
tracking variations in the system model as a result of changes in the
operating regimes. The emulator parameters, on the other hand,
simulate variations in the subsystems during the identification phase
and have negligible effect during the operational phase. The nominal
model and the influence vectors, which are the gradient of the feature
vector respect to the emulator parameters, are identified off-line from
a number of emulator parameter perturbed experiments. A Kalman
filter is designed using the identified nominal model. As the system
varies, the Kalman filter model is adapted using the scheduling
variables. The residual is employed for fault diagnosis. The
proposed scheme is successfully evaluated on simulated system as
well as on a physical process control system.
Abstract: The sun is an inexhaustible source and harness its potential both for heating and power generation is one of the most promising and necessary alternatives, mainly due to environmental issues. However, it should be noted that this has always been present in the generation of energy on earth, only indirectly, since it is responsible for virtually all other energy sources, such as generating source of evaporation of the water cycle, allowing the impoundment and the consequent generation of electricity (hydroelectric power); winds are caused by atmospheric induction caused by large scale solar radiation; petroleum, coal and natural gas were generated from waste plants and animals that originally derived energy required for their development of solar radiation. This paper presents a study on the feasibility of using solar energy for water heating in homes. A simplified methodology developed for formulation of solar heating operation model of water in alternative systems of solar energy in Brazil, and compared it to that in the international market. Across this research, it was possible to create new paradigms for alternative applications to the use of solar energy.
Abstract: Texture is an important characteristic in real and
synthetic scenes. Texture analysis plays a critical role in inspecting
surfaces and provides important techniques in a variety of
applications. Although several descriptors have been presented to
extract texture features, the development of object recognition is still a
difficult task due to the complex aspects of texture. Recently, many
robust and scaling-invariant image features such as SIFT, SURF and
ORB have been successfully used in image retrieval and object
recognition. In this paper, we have tried to compare the performance
for texture classification using these feature descriptors with k-means
clustering. Different classifiers including K-NN, Naive Bayes, Back
Propagation Neural Network , Decision Tree and Kstar were applied in
three texture image sets － UIUCTex, KTH-TIPS and Brodatz,
respectively. Experimental results reveal SIFTS as the best average
accuracy rate holder in UIUCTex, KTH-TIPS and SURF is
advantaged in Brodatz texture set. BP neuro network works best in the
test set classification among all used classifiers.
Abstract: Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.
Abstract: Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate. This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.
Abstract: Fixed bed adsorption has become a frequently used
industrial application in wastewater treatment processes. Various low
cost adsorbents have been studied for their applicability in treatment
of different types of effluents. In this work, the intention of the study
was to explore the efficacy and feasibility for azo dye, Acid Orange 7
(AO7) adsorption onto fixed bed column of NaOH Treated eggshell
(TES). The effect of various parameters like flow rate, initial dye
concentration, and bed height were exploited in this study. The
studies confirmed that the breakthrough curves were dependent on
flow rate, initial dye concentration solution of AO7 and bed depth.
The Thomas, Yoon–Nelson, and Adams and Bohart models were
analysed to evaluate the column adsorption performance. The
adsorption capacity, rate constant and correlation coefficient
associated to each model for column adsorption was calculated and
mentioned. The column experimental data were fitted well with
Thomas model with coefficients of correlation R2 ≥0.93 at different
conditions but the Yoon–Nelson, BDST and Bohart–Adams model
(R2=0.911), predicted poor performance of fixed-bed column. The
(TES) was shown to be suitable adsorbent for adsorption of AO7
using fixed-bed adsorption column.
Abstract: In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.