Search results for: anti-wear ability.

Authors: Bernardo C. P. Albuquerque, Darym J. F. Campos

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Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Keywords: Statistical slope stability analysis, Skew distributions, Probability of failure, Functions of random variables.

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Authors: Herath MPC Jayaweera, Samer Hanoun

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Path planning for on-time obstacle avoidance is an essential and challenging task that enables drones to achieve safe operation in any application domain. The level of challenge increases significantly on the obstacle avoidance technique when the drone is following a ground mobile entity (GME). This is mainly due to the change in direction and magnitude of the GMEs velocity in dynamic and unstructured environments. Force field techniques are the most widely used obstacle avoidance methods due to their simplicity, ease of use and potential to be adopted for three-dimensional dynamic environments. However, the existing force field obstacle avoidance techniques suffer many drawbacks including their tendency to generate longer routes when the obstacles are sideways of the drones route, poor ability to find the shortest flyable path, propensity to fall into local minima, producing a non-smooth path, and high failure rate in the presence of symmetrical obstacles. To overcome these shortcomings, this paper proposes an on-time three-dimensional obstacle avoidance method for drones to effectively and efficiently avoid dynamic and static obstacles in unknown environments while pursuing a GME. This on-time obstacle avoidance technique generates velocity waypoints for its obstacle-free and efficient path based on the shape of the encountered obstacles. This method can be utilize on most types of drones that have basic distance measurement sensors and autopilot supported flight controllers. The proposed obstacle avoidance technique is validated and evaluated against existing force field methods for different simulation scenarios in Gazebo and ROS supported PX4-SITL. The simulation results show that the proposed obstacle avoidance technique outperforms the existing force field techniques and is better suited for real-world applications.

Keywords: Drones, force field methods, obstacle avoidance, path planning.

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Authors: Daniel Alati

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Recent high-profile terrorist events in Canada, the United Kingdom and Europe – the London Bridge attacks, the terrorist attacks in Nice, France and Barcelona, Spain, the 2014 Ottawa Parliament attacks and the 2017 attacks in Edmonton – have all raised levels of public and academic concern with so-called “lone-wolf” and “radicalized” terrorism. Similarly, several countries outside of the “Western” world have been dealing with radicalization to violent extremism for several years. Many South East Asian countries, including Indonesia, Malaysia, Singapore and the Philippines have all had experience with what might be described as ISIS or extremist-inspired acts of terrorism. Indeed, it appears the greatest strength of groups such as ISIS has been their ability to spread a global message of violent extremism that has led to radicalization in markedly different jurisdictions throughout the world. These markedly different jurisdictions have responded with counter-radicalization strategies that warrant further comparative analysis. This paper utilizes an inter-disciplinary legal methodology. In doing so, it compares legal, political, cultural and historical aspects of the counter-radicalization strategies employed by Canada, the United Kingdom and several South East Asian countries (Indonesia, Malaysia, Singapore and the Philippines). Whilst acknowledging significant legal and political differences between these jurisdictions, the paper engages in these analyses with an eye towards understanding which best practices might be shared between the jurisdictions. In doing so, it presents valuable findings of a comparative nature that are useful to both academic and practitioner audiences in several jurisdictions.

Keywords: Canada, United Kingdom, South East Asia, comparative law and politics, radicalization to violent extremism, terrorism.

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modeling has constantly been a challenge through history for human beings. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: Auto-calibration, Gilan, Large-Scale Water Resources, Simulation.

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Authors: Vinod B. Suryawanshi, Ajit D. Kelkar

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Composite materials, due to their unique properties such as high strength to weight ratio, corrosion resistance, and impact resistance have huge potential as structural materials in automotive, construction and transportation applications. However, these properties often come at higher cost owing to complex design methods, difficult manufacturing processes and raw material cost. Traditionally, tapered laminated composite structures are manufactured using autoclave manufacturing process by ply drop off technique. Autoclave manufacturing though very powerful suffers from high capital investment and higher energy consumption. As per the current trends in composite manufacturing, Out of Autoclave (OoA) processes are looked as emerging technologies for manufacturing the structural composite components for aerospace and defense applications. However, there is a need for improvement among these processes to make them reliable and consistent. In this paper, feasibility of using out of autoclave process to manufacture the variable thickness cantilever beam is discussed. The minimum weight design for the composite beam is obtained using constant stress beam concept by tailoring the thickness of the beam. Ply drop off techniques was used to fabricate the variable thickness beam from glass/epoxy prepregs. Experiments were conducted to measure bending stresses along the span of the cantilever beam at different intervals by applying the concentrated load at the free end. Experimental results showed that the stresses in the bean at different intervals were constant. This proves the ability of OoA process to manufacture the constant stress beam. Finite element model for the constant stress beam was developed using commercial finite element simulation software. It was observed that the simulation results agreed very well with the experimental results and thus validated design and manufacturing approach used.

Keywords: Beams, Composites, Constant Stress, Structures.

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Authors: Mitansha, Suzanne Wilkinson, Regan Potangaroa

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The built environment is designed, maintained, operated, and decommissioned by construction organisations, which play a significant role in providing physical resources and rebuilding infrastructures during major crises and disasters. It is evident that enhancing the resilience of construction organisations allows better responding ability and speedy recovery from disasters and acts as a boon for the nation in the face of significant disruptions. As individuals are the integral component of any organisation, hence, individual resilience is considered a critical aspect, which may boost organisational resilience of construction sector. It has been observed that individual resilience is indirectly supported by organisation’s citizenship behaviour, job performance, and career success. Not only this, it also tends to hold a directly proportional relation with job satisfaction, physical and emotional well-being affected by organisation’s work culture, whereas the resilience of organisation increases as a result of positive adaption, growth and collective learning of the employees as an entity. Moreover, indicators like situation awareness in staff and crisis related issues, effective vulnerability management, organisational leadership and culture ensured by approachable, encouraging and people-oriented leaders, are prominent for achieving organisational resilience. It, thus, becomes perceptible that both, organisational and individual resiliencies, have the potential to influence each other. Consequently, it arises a major question that how these characteristics are associated and tend to behave with respect to each other. The study, thus, aims to explore the overlapping dimensions of organisational and individual resilience to determine the impact boundaries. The research methodology of the paper would be based on systematic literature review specifically focused on the resilience of construction industry. This would provide a direct comparison of characteristics influencing individual and organisational resilience and will present the most significant indicators of individual resilience that can eventually help to enhance the resilience of construction organisations amidst any disaster or crisis.

Keywords: Construction industry, individual resilience, organisational resilience, overlapping dimension.

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Authors: Sareh Rajabi, Taha Anjamrooz, Salwa Bheiry

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Sustainability of construction projects is an important issue to be addressed since the sector will continue to be developed in the coming years, especially in developing countries. Thus, it is significant to discover approaches and solutions for improving sustainability. Currently, the construction industry is the largest consumer of natural resources. This is the same in other countries in the Gulf region, and the United Arab Emirates (UAE) has limited natural resources such as water, electricity, etc. Recently, the UAE has taken several actions in order to implement sustainable initiatives within its construction industry. Within the industry, the contractors’ role is significant in promoting sustainable development by taking the responsibility to minimize their negative impacts on the environment and society, and maximize their economic distribution. In this research, sustainability will be studied as an important key to bring competitive advantages to contracting organizations. The contractors should understand the need to improve their sustainable performance in order to expand their business competitiveness. Competitiveness at the construction project level refers to a contractor’s ability to compete for a project. There is less focus on how to improve contractors’ competitiveness by implementing sustainable construction practices. Based on an inclusive literature review on the relationship between sustainability performance and business competitiveness, this research will conduct a study of sustainable practice in the construction industry and the relationship between sustainability performance and business competitiveness in order to develop a framework for evaluating how contractors can improve their competitiveness in terms of more efficient processes, enhancements in productivity, and lower costs of compliance in order to reduce the initial project cost and obtain market opportunities in the UAE. The research findings will provide a framework that can be a useful guideline for contractors to develop their sustainability policy, strategy and practice for meeting the increased requirements for sustainable development in construction.

Keywords: Sustainable construction practice, sustainability, competitiveness, construction industry, contractors.

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Authors: Eva Tvrdá, Boris Botman, Marek Halenár, Tomáš Slanina, Norbert Lukáč

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In vitro storage and processing of animal semen represents a risk factor to spermatozoa vitality, potentially leading to reduced fertility. A variety of substances isolated from natural sources may exhibit protective or antioxidant properties on the spermatozoon, thus extending the lifespan of stored ejaculates. This study compared the ability of different concentrations of the Salvia officinalis extract on the motility, mitochondrial activity, viability and reactive oxygen species (ROS) production by bovine spermatozoa during different time periods (0, 2, 6 and 24 h) of in vitro culture. Spermatozoa motility was assessed using the Computer-assisted sperm analysis (CASA) system. Cell viability was examined using the metabolic activity MTT assay, the eosin-nigrosin staining technique was used to evaluate the sperm viability and ROS generation was quantified using luminometry. The CASA analysis revealed that the motility in the experimental groups supplemented with 0.5-2 µg/mL Salvia extract was significantly lower in comparison with the control (P<0.05; Time 24 h). At the same time, a long-term exposure of spermatozoa to concentrations ranging between 0.05 µg/mL and 2 µg/mL had a negative impact on the mitochondrial metabolism (P<0.05; Time 24 h). The viability staining revealed that 0.001-1 µg/mL Salvia extract had no effects on bovine male gametes, however 2 µg/mL Salvia had a persisting negative effect on spermatozoa (P<0.05). Furthermore 0.05-2 µg/mL Salvia exhibited an immediate ROS-promoting effect on the sperm culture (P>0.05; Time 0 h and 2 h), which remained significant throughout the entire in vitro culture (P<0.05; Time 24 h). Our results point out to the necessity to examine specific effects the biomolecules present in Salvia officinalis may have individually or collectively on the in vitro sperm vitality and oxidative profile.

Keywords: Bulls, CASA, MTT test, reactive oxygen species, sage, Salvia officinalis, spermatozoa.

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Authors: Salma H. Abu Hafsa, A. Mendonca, B. Brehm-Stecher, A. A. Hassan, S. A. Ibrahim

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Enterococci are important inhabitants of the animal intestine and are widely used in probiotic products. A probiotic strain is expected to possess several desirable properties in order to exert beneficial effects. Therefore, the objective of this study was to isolate, characterize and identify Enterococcus sp. from chicken cecal and fecal samples to determine potential probiotic properties. Enterococci were isolated from chicken ceca and feces of thirty three clinically healthy chickens from a local farm. In vitro studies were performed to assess antibacterial activity of the isolated LAB (using agar well diffusion and cell free supernatant broth technique against Salmonella enterica serotype Enteritidis), survival in acidic conditions, resistance to bile salts, and their survival during simulated gastric juice conditions at pH 2.5. Isolates were identified by biochemical carbohydrate fermentation patterns using an API 50 CHL kit and API ZYM kits and by sequenced 16S rDNA. An isolate belonging to E. faecium species exhibited inhibitory effect against S. enteritidis. This isolate producing a clear zone as large as 10.30 mm or greater and was able to grow in the coculture medium and at the same time, inhibited the growth S. enteritidis. In addition, E. faecium exhibited significant resistance under highly acidic conditions at pH 2.5 for 8 h and survived well in bile salt at 0.2% for 24 h and showing ability to survive in the presence of simulated gastric juice at pH 2.5. Based on these results, E. faecium isolate fulfills some of the criteria to be considered as a probiotic strain and therefore, could be used as a feed additive with good potential for controlling S. Enteritidis in chickens. However, in vivo studies are needed to determine the safety of the strain.

Keywords: Acid tolerance, antimicrobial activity, Enterococcus faecium, probiotic.

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Authors: Alonggot Limcharoen, Jintana Wannarat, Vorawat Panich

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This study aims to investigate the balancing of the number of operators (Line Balancing technique) in the production line of hard disk drive components in order to increase efficiency. At present, the trend of using hard disk drives has continuously declined leading to limits in a company’s revenue potential. It is important to improve and develop the production process to create market share and to have the ability to compete with competitors with a higher value and quality. Therefore, an effective tool is needed to support such matters. In this research, the Arena program was applied to analyze the results both before and after the improvement. Finally, the precedent was used before proceeding with the real process. There were 14 work stations with 35 operators altogether in the RA production process where this study was conducted. In the actual process, the average production time was 84.03 seconds per product piece (by timing 30 times in each work station) along with a rating assessment by implementing the Westinghouse principles. This process showed that the rating was 123% underlying an assumption of 5% allowance time. Consequently, the standard time was 108.53 seconds per piece. The Takt time was calculated from customer needs divided by working duration in one day; 3.66 seconds per piece. Of these, the proper number of operators was 30 people. That meant five operators should be eliminated in order to increase the production process. After that, a production model was created from the actual process by using the Arena program to confirm model reliability; the outputs from imitation were compared with the original (actual process) and this comparison indicated that the same output meaning was reliable. Then, worker numbers and their job responsibilities were remodeled into the Arena program. Lastly, the efficiency of production process enhanced from 70.82% to 82.63% according to the target.

Keywords: Hard disk drive, line balancing, simulation, Arena program.

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Authors: W. Thepsuwan, N. Monmaturapoj

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Calcium phosphate cement (CPC) is one of the most attractive bioceramics due to its moldable and shape ability to fill complicated bony cavities or small dental defect positions. In this study, CPC was produced by using mixture of tetracalcium phosphate (TTCP, Ca4O(PO4)2) and dicalcium phosphate anhydrous (DCPA, CaHPO4) in equimolar ratio (1/1) with aqueous solutions of acetic acid (C2H4O2) and disodium hydrogen phosphate dehydrate (Na2HPO4.2H2O) in combination with sodium alginate in order to improve theirs moldable characteristic. The concentration of the aqueous solutions and sodium alginate were varied to investigate the effect of different aqueous solutions and alginate on properties of the cements. The cement paste was prepared by mixing cement powder (P) with aqueous solution (L) in a P/L ratio of 1.0g/0.35ml. X-ray diffraction (XRD) was used to analyses phase formation of the cements. Setting time and compressive strength of the set CPCs were measured using the Gilmore apparatus and Universal testing machine, respectively. The results showed that CPCs could be produced by using both basic (Na2HPO4.2H2O) and acidic (C2H4O2) solutions. XRD results show the precipitation of hydroxyapatite in all cement samples. No change in phase formation among cements using difference concentrations of Na2HPO4.2H2O solutions. With increasing concentration of acidic solutions, samples obtained less hydroxyapatite with a high dicalcium phosphate dehydrate leaded to a shorter setting time. Samples with sodium alginate exhibited higher crystallization of hydroxyapatite than that of without alginate as a result of shorten setting time in a basic solution but a longer setting time in an acidic solution. The stronger cement was attained from samples using the acidic solution with sodium alginate; however the strength was lower than that of using the basic solution.

Keywords: Calcium phosphate cements, TTCP, DCPA, hydroxyapatite, properties.

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Authors: Ludk Benada, Jindika Sedova

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The current situation in the eurozone raises a number of topics for discussion and to help in finding an answer to the question of whether a common currency is a more suitable means of coping with the impact of the financial crisis or whether national currencies are better suited to this. The economic situation in the EU is now considerably volatile and, due to problems with the fulfilment of the Maastricht convergence criteria, it is now being considered whether, in their further development, new member states will decide to distance themselves from the euro or will, in an attempt to overcome the crisis, speed up the adoption of the euro. The Czech Republic is one country with little interest in adopting the euro, justified by the fact that a better alternative to dealing with this crisis is an independent monetary policy and its ability to respond flexibly to the economic situation not only in Europe, but around the world. One attribute of the crisis in the Czech Republic and its mitigation is the freely floating exchange rate of the national currency. It is not only the Czech Republic that is attempting to alleviate the impact of the crisis, but also new EU member countries facing fresh questions to which theory have yet to provide wholly satisfactory answers. These questions undoubtedly include the problem of inflation targeting and the choice of appropriate instruments for achieving financial stability. The difficulty lies in the fact that these objectives may be contradictory and may require more than one means of achieving them. In this respect we may assume that membership of the euro zone might not in itself mitigate the development of the recession or protect the nation from future crises. We are of the opinion that the decisive factor in the development of any economy will continue to be the domestic economic policy and the operability of market economic mechanisms. We attempt to document this fact using selected countries as examples, these being the Czech Republic, Poland, Hungary, and Slovakia.

Keywords: Currency exchange rate, Maastricht convergence criteria, monetary union, public finances.

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

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Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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The applications of composite materials within the aviation industry has been increasing at a rapid pace.  However, the growing applications of composite materials have also led to growing demand for more tooling to support its manufacturing processes. Tooling and tooling maintenance represents a large portion of the composite manufacturing process and cost. Therefore, the industry’s adaptability to new techniques for fabricating high quality tools quickly and inexpensively will play a crucial role in composite material’s growing popularity in the aviation industry. One popular tool fabrication technique currently being developed involves additive manufacturing such as 3D printing. Although additive manufacturing and 3D printing are not entirely new concepts, the technique has been gaining popularity due to its ability to quickly fabricate components, maintain low material waste, and low cost. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite compression mold. A 3D printed composite compression mold was fabricated by 3D scanning a steel valve cover of an aircraft reciprocating engine. The 3D printed composite compression mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The 3D printed composite compression mold was evaluated for its performance, durability, and dimensional stability while the fabricated carbon fiber valve covers were evaluated for its accuracy and quality. The results and data gathered from this study will determine the effectiveness of the 3D printed composite compression mold in a mass production environment and provide valuable information for future understanding, improvements, and design considerations of 3D printed composite molds.

Keywords: Additive manufacturing, carbon fiber, composite tooling, molds.

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Authors: Esmeralda Hysenbelliu

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The aim of this paper is to present the QoE (Quality of Experience) IPTV SDN-based media streaming server enhanced architecture for configuring, controlling, management and provisioning the improved delivery of IPTV service application with low cost, low bandwidth, and high security. Furthermore, it is given a virtual QoE IPTV SDN-based topology to provide an improved IPTV service based on QoE Control and Management of multimedia services functionalities. Inside OpenFlow SDN Controller there are enabled in high flexibility and efficiency Service Load-Balancing Systems; based on the Loading-Balance module and based on GeoIP Service. This two Load-balancing system improve IPTV end-users Quality of Experience (QoE) with optimal management of resources greatly. Through the key functionalities of OpenFlow SDN controller, this approach produced several important features, opportunities for overcoming the critical QoE metrics for IPTV Service like achieving incredible Fast Zapping time (Channel Switching time) < 0.1 seconds. This approach enabled Easy and Powerful Transcoding system via FFMPEG encoder. It has the ability to customize streaming dimensions bitrates, latency management and maximum transfer rates ensuring delivering of IPTV streaming services (Audio and Video) in high flexibility, low bandwidth and required performance. This QoE IPTV SDN-based media streaming architecture unlike other architectures provides the possibility of Channel Exchanging between several IPTV service providers all over the word. This new functionality brings many benefits as increasing the number of TV channels received by end –users with low cost, decreasing stream failure time (Channel Failure time < 0.1 seconds) and improving the quality of streaming services.

Keywords: Improved QoE, OpenFlow SDN controller, IPTV service application, softwarization.

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Authors: Amit Kr. Happy

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This paper is motivated by the importance of multi-sensor image fusion with specific focus on Infrared (IR) and Visible image (VI) fusion for various applications including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like Visible camera & IR Thermal Imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (IR) that may be reflected or self-emitted. A digital color camera captures the visible source image and a thermal IR camera acquires the thermal source image. In this paper, some image fusion algorithms based upon Multi-Scale Transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, but they also make it hard to become deployed in system and applications that require real-time operation, high flexibility and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: Image fusion, IR thermal imager, multi-sensor, Multi-Scale Transform.

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Authors: Hamidullah Binol, Abdullah Bal

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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: Food (Ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods.

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Authors: Lena Shulyakovskaya

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Every year, schools aim to develop and adopt new technology and pedagogy as a way to equip today's students with the needed 21st Century skills. However, the field of primary and secondary education may not be as open to embracing change in reality. Despite the drive to reform and innovation, the field of education in Canada is still very much steeped in tradition and uses many of the practices that came into effect over 50 years ago. Among those are employment and retention practices. Millennials are the youngest generation of professionals entering the workplace at this time and the ones leaving their jobs within just a few years. Almost half of new teachers leave Canadian schools within their first five years on the job. This paper discusses one of the contributing factors that lead Canadian millennial teachers to either leave or stay in the profession - standardized education system. Using an exploratory case study approach, in-depth interviews with former and current millennial teachers were conducted to learn about their experiences within the K-12 system. Among the findings were the young teachers' concerns about the constant changes to teaching practices and technological implementations that claimed to advance teaching and learning, and yet in reality only disguised and reiterated the same traditional, outdated, and standardized practices that already existed. Furthermore, while many millennial teachers aspired to be innovative with their curriculum and teaching practices, they felt trapped and helpless in the hands of school leaders who were very reluctant to change. While many new program ideas and technological advancements are being made openly available to teachers on a regular basis, it is important to consider the education field as a whole and how it plays into the teachers' ability to realistically implement changes. By the year 2025, millennials will make up approximately 75% of the North American workforce. It is important to examine generational differences among teachers and understand how millennial teachers may be shaping the future of primary and secondary schools, either by staying or leaving the profession.

Keywords: 21st century skills, millennials, teacher attrition, tradition.

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Authors: C. Ardil

Abstract:

In this paper, the comparison of composite programming and compromise programming for the aircraft selection problem is discussed using the multiple criteria decision analysis method. The decision making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as aircraft selection problems. The proposed technique gives more efficient results by extending the composite programming and compromise programming, which are widely used in modeling multiple criteria decisions. The proposed model is applied to a practical decision problem for evaluating and selecting aircraft problems.A selection of aircraft was made based on the proposed approach developed in the field of multiple criteria decision making. The model presented is solved by using the following methods: composite programming, and compromise programming. The importance values of the weight coefficients of the criteria are calculated using the mean weight method. The evaluation and ranking of aircraft are carried out using the composite programming and compromise programming methods. In order to determine the stability of the model and the ability to apply the developed composite programming and compromise programming approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ and q in the first part. The second part of the sensitivity analysis relates to the application of different multiple criteria decision making methods, composite programming and compromise programming. In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient of the ranks obtained was calculated which confirms the applicability of all the proposed approaches.

Keywords: composite programming, compromise programming, additive weighted model, multiplicative weighted model, multiple criteria decision making analysis, MCDMA, aircraft selection

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Authors: Photjanat Phimnom, Haruetai Lohasiriwat

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In today’s world, the LED display has been used for presenting visual information under various circumstances. Such information is an important intermediary in the human information processing. Researchers have been investigated diverse factors that influence this process effectiveness. The letter size is undoubtedly one major factor that has been tested and recommended by many standards and guidelines. However, viewing information on the display from direct perpendicular position is a typical assumption whereas many actual events are required viewing from the angles. This current research aims to study the effect of oblique viewing angle and viewing distance on ability to recognize alphabet, number, and English word. The total of ten participants was volunteered to our 3 x 4 x 4 within subject study. Independent variables include three distance levels (2, 6, and 12 m), four oblique angles (0, 45, 60, 75 degree), and four target types (alphabet, number, short word, and long word). Following the method of constant stimuli our study suggests that the larger oblique angle, ranging from 0 to 75 degree from the line of sight, results in significant higher legibility threshold or larger font size required (p-value < 0.05). Viewing distance factor also shows to have significant effect on the threshold (p-value < 0.05). However, the effect from distance factor is expected to be confounded by the quality of the screen used in our experiment. Lastly, our results show that single alphabet as well as single number are recognized at significant lower threshold (smaller font size) as compared to both short and long words (p-value < 0.05). Therefore, it is recommended that when designs information to be presented on LED display, understanding of all possible ranges of oblique angle should be taken into account in order to specify the preferred letter size. Additionally, the recommendation of letter size for 100% legibility in our tested conditions is provided in the paper.

Keywords: Letter Size, Oblique Angle, Viewing Distance, Legibility Threshold.

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Authors: M. Govindarajan

Abstract:

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In decision tree approach is most useful in classification problem. With this technique, tree is constructed to model the classification process. There are two basic steps in the technique: building the tree and applying the tree to the database. This paper describes a proposed C5.0 classifier that performs rulesets, cross validation and boosting for original C5.0 in order to reduce the optimization of error ratio. The feasibility and the benefits of the proposed approach are demonstrated by means of medial data set like hypothyroid. It is shown that, the performance of a classifier on the training cases from which it was constructed gives a poor estimate by sampling or using a separate test file, either way, the classifier is evaluated on cases that were not used to build and evaluate the classifier are both are large. If the cases in hypothyroid.data and hypothyroid.test were to be shuffled and divided into a new 2772 case training set and a 1000 case test set, C5.0 might construct a different classifier with a lower or higher error rate on the test cases. An important feature of see5 is its ability to classifiers called rulesets. The ruleset has an error rate 0.5 % on the test cases. The standard errors of the means provide an estimate of the variability of results. One way to get a more reliable estimate of predictive is by f-fold –cross- validation. The error rate of a classifier produced from all the cases is estimated as the ratio of the total number of errors on the hold-out cases to the total number of cases. The Boost option with x trials instructs See5 to construct up to x classifiers in this manner. Trials over numerous datasets, large and small, show that on average 10-classifier boosting reduces the error rate for test cases by about 25%.

Keywords: C5.0, Error Ratio, text mining, training data, test data.

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Authors: S. Lemoussu, J. C. Chaudemar, R. A. Vingerhoeds

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The aeronautics sector is currently living an unprecedented growth largely due to innovative projects. In several cases, such innovative developments are being carried out by Small and Medium sized-Enterprises (SMEs). For instance, in Europe, a handful of SMEs are leading projects like airships, large civil drones, or flying cars. These SMEs have all limited resources, must make strategic decisions, take considerable financial risks and in the same time must take into account the constraints of safety, cost, time and performance as any commercial organization in this industry. Moreover, today, no international regulations fully exist for the development and certification of this kind of projects. The absence of such a precise and sufficiently detailed regulatory framework requires a very close contact with regulatory instances. But, SMEs do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses additional challenges for those SMEs that have system integration responsibilities and that must provide all the necessary means of compliance to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The final objective of our research is thus to provide a methodological framework supporting SMEs in their development taking into account recent innovation and institutional rules of the sector. We aim to provide a contribution to the problematic by developing a specific Model-Based Systems Engineering (MBSE) approach. Airspace regulation, aeronautics standards and international norms on systems engineering are taken on board to be formalized in a set of models. This paper presents the on-going research project combining Systems Engineering and Project Management process modeling and taking into account the metamodeling problematic.

Keywords: Aeronautics, certification, process modeling, project management, SME, systems engineering.

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Authors: Mohammad Emran, Colton Wayne, Shannon M Koehler, P. Stephen Almond, Haroon Patel

Abstract:

Purpose: Assessment of anastomotic perfusion in Hirschsprung disease using Indocyanine Green (ICG)-near-infrared (NIR) fluorescence angiography. Introduction: Anastomotic stricture and leak are well-known complications of Hirschsprung pull-through procedures. Complications are due to tension, infection, and/or poor perfusion. While a surgeon can visually determine and control the amount of tension and contamination, assessment of perfusion is subject to surgeon determination. Intraoperative use of ICG-NIR enhances this decision-making process by illustrating perfusion intensity and adequacy in the pulled-through bowel segment. This technique, proven to reduce anastomotic stricture and leak in adults, has not been studied in children to our knowledge. ICG, an FDA approved, nontoxic, non-immunogenic, intravascular (IV) dye, has been used in adults and children for over 60 years, with few side effects. ICG-NIR was used in this report to demonstrate the adequacy of perfusion during transanal pullthrough for Hirschsprung’s disease. Method: 8 patients with Hirschsprung disease were evaluated with ICG-NIR technology. Levels of affected area ranged from sigmoid to total colonic Hirschsprung disease. After leveling, but prior to anastomosis, ICG was administered at 1.25 mg (< 2 mg/kg) and perfusion visualized using an NIR camera, before and during anastomosis. Video and photo imaging was performed and perfusion of the bowel was compared to surrounding tissues. This showed the degree of perfusion and demarcation of perfused and non-perfused bowel. The anastomosis was completed uneventfully and the patients all did well. Results: There were no complications of stricture or leak. 5 of 8 patients (62.5%) had modification of the plan based on ICG-NIR imaging. Conclusion: Technologies that enhance surgeons’ ability to visualize bowel perfusion prior to anastomosis in Hirschsprung’s patients may help reduce post-operative complications. Further studies are needed to assess the potential benefits.

Keywords: Colonic anastomosis, fluorescence angiography, Hirschsprung disease, pediatric surgery, SPY, ICG, NIR.

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Authors: Lixin Tian, Wei Xue

Abstract:

Many jobs in society go underground, such as mine mining, tunnel construction and subways, which are vital to the development of society. Once accidents occur in these places, the interruption of traditional wired communication is not conducive to the development of rescue work. In order to realize the positioning, early warning and command functions of underground personnel and improve rescue efficiency, it is necessary to develop and design an emergency ground communication system. It is easy to be subjected to narrowband interference when performing conventional underground communication. Spreading communication can be used for this problem. However, general spread spectrum methods such as direct spread communication are inefficient, so it is proposed to use parallel combined spread spectrum (PCSS) communication to improve efficiency. The PCSS communication not only has the anti-interference ability and the good concealment of the traditional spread spectrum system, but also has a relatively high frequency band utilization rate and a strong information transmission capability. So, this technology has been widely used in practice. This paper presents a PCSS communication model-multiple detection parallel combined spread spectrum (MDPCSS) communication system. In this paper, the principle of MDPCSS communication system is described, that is, the sequence at the transmitting end is processed in blocks and cyclically shifted to facilitate multiple detection at the receiving end. The block diagrams of the transmitter and receiver of the MDPCSS communication system are introduced. At the same time, the calculation formula of the system bit error rate (BER) is introduced, and the simulation and analysis of the BER of the system are completed. By comparing with the common parallel PCSS communication, we can draw a conclusion that it is indeed possible to reduce the BER and improve the system performance. Furthermore, the influence of different pseudo-code lengths selected on the system BER is simulated and analyzed, and the conclusion is that the larger the pseudo-code length is, the smaller the system error rate is.

Keywords: Cyclic shift, multiple detection, parallel combined spread spectrum, PN code.

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Authors: M. A. Rashed, A. S. Mansour, H. Faris, W. Afify

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The calcarenites carbonate rocks of the Quaternary ridges, which extend along the northwestern Mediterranean coastal plain of Egypt, represent an excellent model for the transformation of loose sediments to real sedimentary rocks by the different stages of meteoric diagenesis. The depositional and diagenetic fabrics of the rocks, in addition to the strata orientation, highly affect their ultimate compressive strength and other geotechnical properties.

There is a marked increase in the compressive strength (UCS) from the first to the fourth ridge rock samples. The lowest values are related to the loose packing, weakly cemented aragonitic ooid sediments with high porosity, besides the irregularly distributed of cement, which result in decreasing the ability of these rocks to withstand crushing under direct pressure. The high (UCS) values are attributed to the low porosity, the presence of micritic cement, the reduction in grain size and the occurrence of micritization and calcretization processes.

The strata orientation has a notable effect on the measured (UCS). The lowest values have been recorded for the samples cored in the inclined direction; whereas the highest values have been noticed in most samples cored in the vertical and parallel directions to bedding plane. In case of the inclined direction, the bedding planes were oriented close to the plane of maximum shear stress. The lowest and highest anisotropy values have been recorded for the first and the third ridges rock samples, respectively, which may attributed to the relatively homogeneity and well sorted grainstone of the first ridge rock samples, and relatively heterogeneity in grain and pore size distribution and degree of cementation of the third ridge rock samples, besides, the abundance of shell fragments with intraparticle pore spaces, which may produce lines of weakness within the rock.

Keywords: Compressive strength, Anisotropy, Calcarenites, Egypt.

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Authors: Yung-Chien Sun, O. Grant Clark

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In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: N. Porzionato, M. Mantiñan, E. Bussi, S. Grinberg, R. Gutierrez, G. Curutchet

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This work sets out to debate the tensions involved in the processes of contamination and self-purification in the urban space, particularly in the streams that run through the Buenos Aires metropolitan area. For much of their course, those streams are piped; their waters do not come into contact with the outdoors until they have reached deeply impoverished urban areas with high levels of environmental contamination. These are peripheral zones that, until thirty years ago, were marshlands and fields. They are now densely populated areas largely lacking in urban infrastructure. The Cárcova neighborhood, where this project is underway, is in the José León Suárez section of General San Martín county, Buenos Aires province. A stretch of José León Suarez canal crosses the neighborhood. Starting upstream, this canal carries pollutants due to the sewage and industrial waste released into it. Further downstream, in the neighborhood, domestic drainage is poured into the stream. In this paper, we formulate a hypothesis diametrical to the one that holds that these neighborhoods are the primary source of contamination, suggesting instead that in the stretch of the canal that runs through the neighborhood the stream’s waters are actually cleaned and the sediments accumulate pollutants. Indeed, the stretches of water that runs through these neighborhoods act as water processing plants for the metropolis. This project has studied the different organic-load polluting contributions to the water in a certain stretch of the canal, the reduction of that load over the course of the canal, and the incorporation of pollutants into the sediments. We have found that the surface water has considerable ability to self-purify, mostly due to processes of sedimentation and adsorption. The polluting load is accumulated in the sediments where that load stabilizes slowly by means of anaerobic processes. In this study, we also investigated the risks of sediment management and the use of the processes studied here in controlled conditions as tools of environmental restoration.

Keywords: Bioremediation, pollutants, sediments, urban streams.

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Authors: Thomas S. Abia II, Citlali Garcia-Saucedo

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A continuous copper precipitation treatment (CCPT) system was conceived at Intel Chandler Site to serve as a first-of-kind (FOK) facility-scale waste copper (Cu), nickel (Ni), and manganese (Mn) co-precipitation facility. The process was designed to treat highly variable wastewater discharged from a substrate packaging research factory. The paper discusses metals co-precipitation induced by internal changes for manufacturing facilities that lack the capacity for hardware expansion due to real estate restrictions, aggressive schedules, or budgetary constraints. Herein, operating parameters such as pH and oxidation reduction potential (ORP) were examined to analyze the ability of the CCPT System to immobilize various waste metals. Additionally, influential factors such as influent concentrations and retention times were investigated to quantify the environmental variability against system performance. A total of 2,027 samples were analyzed and statistically evaluated to measure the performance of CCPT that was internally retrofitted for Mn abatement to meet environmental regulations. In order to enhance the consistency of the influent, a separate holding tank was cannibalized from another system to collect and slow-feed the segregated Mn wastewater from the factory into CCPT. As a result, the baseline influent Mn decreased from 17.2+18.7 mg¹L^-1 at pre-pilot to 5.15+8.11 mg¹L^-1 post-pilot (70.1% reduction). Likewise, the pre-trial and post-trial average influent Cu values to CCPT were 52.0+54.6 mg¹L^-1 and 33.9+12.7 mg¹L^-1, respectively (34.8% reduction). However, the raw Ni content of 0.97+0.39 mg¹L^-1 at pre-pilot increased to 1.06+0.17 mg¹L^-1 at post-pilot. The average Mn output declined from 10.9+11.7 mg¹L^-1 at pre-pilot to 0.44+1.33 mg¹L^-1 at post-pilot (96.0% reduction) as a result of the pH and ORP operating setpoint changes. In similar fashion, the output Cu quality improved from 1.60+5.38 mg¹L^-1 to 0.55+1.02 mg¹L^-1 (65.6% reduction) while the Ni output sustained a 50% enhancement during the pilot study (0.22+0.19 mg¹L^-1 reduced to 0.11+0.06 mg¹L^-1). pH and ORP were shown to be significantly instrumental to the precipitative versatility of the CCPT System.

Keywords: Copper, co-precipitation, industrial wastewater treatment, manganese, optimization, pilot study.

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Authors: A. El Harraj, N. Raissouni

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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