Search results for: power system protection

Authors: Ewa Rusak, Sebastian Seget, Aleksandra Mroskowiak, Mirosław Partyka, Ewa Samulska, Julia Strózik, Anna Wilk, Przemysława Jarosz-Chobot

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Introduction: Various infections can affect children suffering from Type 1 Diabetes (T1D) because of dysfunctions of the immune system. The urinary tract and urethra of these children can be easily infected areas because of glycosuria. Aim: The microflora assessment of the urethra area of children with newly diagnosed T1D. Methods: The materials of the study were swabs taken prospectively from the urethral area of 63 children at the time of diagnosis of T1D (37 boys), then the results were correlated to the clinical parameters. In the statistical analysis, there were T student, Chi square, and U Mann-Whitney tests used. Results: The mean age was 9.4 years (6 months-17.4 years). The mean HbA1c value was 12.1% (5,6% - 20.1%). The mean value of glycosuria was 4463.2 mg/dl (0 - 9770 mg/dl). Ketoacidosis was diagnosed in 29 children (49%). The following microbial species were isolated in the collected materials: Staphylococcus epidermidis in 18 children (28.6%), Enterococcus faecalis in 17 children (27%), Candida albicans in 15 children (23.8%), coagulase-negative staphylococciin 11 children (17.5%), group B Streptococcus beta-hemolysis in 10 children (15.9%), S. aureus, E. coli, S. anginosus, C. glucuronolyticum, and A. urinae in 7 children each (11.1%), group B Streptococcus beta-hemolysis and S. hominis in 6 children each (9.5%), L. gasseri in 5 children (7.5%), C. dubliniensis in 4 children (6.3) and other, isolated cases. 2 of diagnosed patients were cultured negatively (3.2%). There were statistical correlations between the type of colonisation and patients’ sex and HbA1C value. Conclusions: It is extremely important to examine the urethral area at the time of diagnosis of T1D in order to detect inflammation and to undertake the appropriate and effective intervention.

Keywords: diabetology, skin disorders, microbiology, microflora

Procedia PDF Downloads 141

Authors: Torsten Mielitz, Dietmar Schulz, York C. Roth

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Market forecasts show a significant increase in the demand for aircraft within the next two decades and production rates will be adapted accordingly. Improvements and optimizations in the industrial system are becoming more important to cope with future challenges in manufacturing and assembly. Highest quality standards have to be met for aerospace parts, whereas cost effective production in industrial systems and methodologies are also a key driver. A look at other industries like e.g., automotive shows well established processes to streamline existing manufacturing systems. In this paper, the implementation of 'PULL' principles in an existing manufacturing process chain for a large scale composite part is presented. A nonlinear extrapolation based on 'Little's Law' showed a risk of a significant increase of parts needed in the process chain to meet future demand. A project has been set up to mitigate the risk whereas the methodology has been changed from a traditional milestone approach in the beginning towards an agile way of working in the end in order to facilitate immediate benefits in the shop-floor. Finally, delivery rates could be increased avoiding more semi-finished parts in the process chain (work in progress & inventory) by the successful implementation of the 'PULL' philosophy in the shop-floor between the work stations. Lessons learned during the running project as well as implementation and operations phases are discussed in order to share best practices.

Keywords: aerospace composite part manufacturing, PULL principles, shop-floor implementation, lessons learned

Procedia PDF Downloads 167

Authors: Souhir Chelly, Chahida Harizi, Aicha Hechaichi, Sihem Aissaoui, Leila Ben Ayed, Maha Bergaoui, Mohamed Kouni Chahed

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Introduction: The International Classification of Primary Care (ICPC) is part of the morbidity classification system. It had 17 chapters, and each is coded by an alphanumeric code: the letter corresponds to the chapter, the number to a paragraph in the chapter. The objective of this study is to show the utility of this classification in the coding of the reasons for demand for care in Primary health care (PHC), its advantages and limits. Methods: This is a cross-sectional descriptive study conducted in 4 PHC in Ariana district. Data on the demand for care during 2 days in the same week were collected. The coding of the information was done according to the CISP. The data was entered and analyzed by the EPI Info 7 software. Results: A total of 523 demands for care were investigated. The patients who came for the consultation are predominantly female (62.72%). Most of the consultants are young with an average age of 35 ± 26 years. In the ICPC, there are 7 rubrics: 'infections' is the most common reason with 49.9%, 'other diagnoses' with 40.2%, 'symptoms and complaints' with 5.5%, 'trauma' with 2.1%, 'procedures' with 2.1% and 'neoplasm' with 0.3%. The main advantage of the ICPC is the fact of being a standardized tool. It is very suitable for classification of the reasons for demand for care in PHC according to their specificity, capacity to be used in a computerized medical file of the PHC. Its current limitations are related to the difficulty of classification of some reasons for demand for care. Conclusion: The ICPC has been developed to provide healthcare with a coding reference that takes into account their specificity. The CIM is in its 10th revision; it would gain from revision to revision to be more efficient to be generalized and used by the teams of PHC.

Keywords: international classification of primary care, medical file, primary health care, Tunisia

Procedia PDF Downloads 258

Authors: Wanida Suwunniponth

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This research paper aimed to developing a causal relationship model of success factors of customer relationship management of tourism in Thailand and to investigating relationships among the potential factors that facilitate the success of customer relationship management (CRM). The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. The questionnaire was used in collecting the data from 250 management staff in the hotels located within Bangkok area. Sampling techniques used in this research included cluster sampling according to the service quality and simple random sampling. The data input was analyzed by use of descriptive analysis and System Equation Model (SEM). The research findings demonstrated important factors accentuated by most respondents towards the success of CRM, which were organization, people, information technology and the process of CRM. Moreover, the customer relationship management of tourism business in Thailand was found to be successful at a very significant level. The hypothesis testing showed that the hypothesis was accepted, as the factors concerning with organization, people and information technology played an influence on the process and the success of customer relationship management, whereas the process of customer relationship management factor manipulated its success. The findings suggested that tourism business in Thailand with the implementation of customer relationship management should opt in improvement approach in terms of managerial structure, corporate culture building with customer- centralized approach accentuated, and investment of information technology and customer analysis, in order to capacitate higher efficiency of customer relationship management process that would result in customer satisfaction and retention of service.

Keywords: customer relationship management, casual relationship model, tourism, Thailand

Procedia PDF Downloads 327

Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

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In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

Procedia PDF Downloads 208

Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

Procedia PDF Downloads 229

Authors: Mustapha Kamel Mihoubi, Mohamed Essadik Kerkar

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Probabilistic risk analysis models are used to provide a better understanding of the reliability and structural failure of works, including when calculating the stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of reliability analysis methods including the methods used in engineering. It is in our case, the use of level 2 methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type first order risk method (FORM) and the second order risk method (SORM). By way of comparison, a level three method was used which generates a full analysis of the problem and involves an integration of the probability density function of random variables extended to the field of security using the Monte Carlo simulation method. Taking into account the change in stress following load combinations: normal, exceptional and extreme acting on the dam, calculation of the results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities, thus causing a significant decrease in strength, shear forces then induce a shift that threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case the increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit-state, monte-carlo, reliability, probability, simulation, sliding, taylor

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Tracey Bone

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Deaf inmates, whose first or preferred language is a Signed Language, experience barriers to accessing the necessary two-way communication with correctional staff, and the educational and social programs that will enhance their eligibility for conditional release from the federal prison system in Canada. The development of visual content to enhance the knowledge and skill development of correctional staff is a contemporary strategy intended to significantly improve the correctional experience for deaf inmates. This presentation reports on the development of two distinct training videos created to enhance staff’s understanding of the needs of deaf inmates; one a two-part simulation of an interaction with a deaf inmate, the second an interview with a deaf academic. Part one of video one demonstrates the challenges and misunderstandings inherent in communicating across languages without a qualified sign language interpreter; the second part demonstrates the ease of communication when communication needs are met. Video two incorporates the experiences of a deaf academic to provide the cultural grounding necessary to educate staff in the unique experiences associated with being a visual language user. Lack of staff understanding or awareness of deaf culture and language must not be acceptable reasons for the inadequate treatment of deaf visual language users in federal prisons. This paper demonstrates a contemporary approach to meeting the human rights and needs of this unique and often ignored inmate subpopulation. The deaf community supports this visual approach to enhancing staff understanding of the unique needs of this population. A study of its effectiveness is currently underway.

Keywords: accommodations, American Sign Language (ASL), deaf inmates, sensory deprivation

Procedia PDF Downloads 146

Authors: Raffaello Furlan

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In the 21st century, the sustainable urban development of GCC-cities is challenged by inhabitants’ over-dependency on private-use vehicles. In turn, this habit has generated problems of urban inefficiency, contributing to traffic congestion, pollution, urban sprawling, fragmentation of the urban fabric, and various environmental and social challenges. In the context of Doha, the capital city of the State of Qatar, the over-dependency on private-use vehicles is justified by the lack of alternative public modes of transportation that support the need to connect fragmented urban districts and provide an effective solution to urban sprawl. Therefore, the current construction of the Qatar Metro Rail is offering the potential for investigating and defining a strategy for the sustainable urban development and/or urban regeneration of transit villages (TODs) in Qatar. Namely, the aim of this research study is (i) to investigate the development of transit villages (TODs) in the cultural-heritage district of Msheireb, Downtown Doha, (ii) to explore how the introduction of the new public transport system of Doha Metro can be effectively utilized as means of urban regeneration of the cultural core of the city, (iii) to propose a masterplan for TOD suitable for the district, suiting and responding to regional cultural and societal values. The findings reveal that the strategies for the sustainable urban regeneration of Msheireb are based on (i) the integration of land-use and multimodal transportation systems, (ii) the implementation of the public realm, and (iii) conservation of culture and urban identity.

Keywords: sustainable urbanism, smart growth, TODs, cultural district, Msheireb Downtown Doha

Procedia PDF Downloads 232

Authors: Diaa Othman, Muhammad Adil Khan, Muhammad Riaz

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Without an early intervention to correct the unilateral complete cleft lip and palate deformity, nasal architecture can progress to an exaggerated cleft nose deformity. We present the results of a modified unilateral cleft rhinoplasty procedure ‘the Gujrat technique’ to correct this deformity. Ninety pediatric and adult patients with non-syndromic unilateral cleft lip underwent primary and secondary composite cleft rhinoplasty using the Gujrat technique as a single stage operation over a 10-year period. The technique involved an open rhinoplasty with Tennison lip repair, and employed a combination of three autologous cartilage grafts, seven cartilage-molding sutures and a prolene mesh graft for alar base support. Post-operative evaluation of nasal symmetry was undertaken using the validated computer program ‘SymNose’. Functional outcome and patient satisfaction were assessed using the NOSE scale and ROE (rhinoplasty outcome evaluation) questionnaires. The single group study design used the non-parametric matching pairs Wilcoxon Sign test (p < 0.001), and showed overall good to excellent functional and aesthetic outcomes, including nasal projection and tip definition, and higher scores of the digital SymNose grading system. Objective assessment of the Gujrat cleft rhinoplasty technique demonstrates its aesthetic appeal and functional versatility. Overall it is a simple and reproducible technique, with no significant complications.

Keywords: cleft lip and palate, congenital rhinoplasty, nasal deformity, secondary rhinoplasty

Procedia PDF Downloads 198

Authors: AlHanoof A. Alharbi, Fatima M. Alamoudi, Razan A. Albrahim, Sarah F. Alharbi, Abdullah M Almuhaideb, Norah A. Almubairik, Abdulrahman Alharby, Naya M. Nagy

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Recently, drones received a rapid interest in different industries worldwide due to its powerful impact. However, limitations still exist in this emerging technology, especially privacy violation. These aircrafts consistently threaten the security of entities by entering restricted areas accidentally or deliberately. Therefore, this research project aims to develop drone detection and prevention mechanism to protect the restricted area. Until now, none of the solutions have met the optimal requirements of detection which are cost-effectiveness, high accuracy, long range, convenience, unaffected by noise and generalization. In terms of prevention, the existing methods are focusing on impractical solutions such as catching a drone by a larger drone, training an eagle or a gun. In addition, the practical solutions have limitations, such as the No-Fly Zone and PITBULL jammers. According to our study and analysis of previous related works, none of the solutions includes detection and prevention at the same time. The proposed solution is a combination of detection and prevention methods. To implement the detection system, a passive radar will be used to properly identify the drone against any possible flying objects. As for the prevention, jamming signals and forceful safe landing of the drone integrated together to stop the drone’s operation. We believe that applying this mechanism will limit the drone’s invasion of privacy incidents against highly restricted properties. Consequently, it effectively accelerates drones‘ usages at personal and governmental levels.

Keywords: detection, drone, jamming, prevention, privacy, RF, radar, UAV

Procedia PDF Downloads 203

Authors: Khaled M. Ali, M. A. Abdel-Hamid, Ayman A. Mostafa

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Objective: Safety and efficacy of Ahmed glaucoma valve implantation for the management of uveitis induced glaucoma evaluated on the five dogs with uncontrollable glaucoma. Materials and Methods: Ahmed Glaucoma Valve (AGV®; New World Medical, Rancho Cucamonga, CA, USA) is a flow restrictive, non-obstructive self-regulating valve system. Preoperative ocular evaluation included direct ophthalmoscopy and measurement of the intraocular pressure (IOP). The implant was examined and primed prior to implantation. The selected site of the valve implantation was the superior quadrant between the superior and lateral rectus muscles. A fornix-based incision was made through the conjunectiva and Tenon’s capsule. A pocket is formed by blunt dissection of Tenon’s capsule from the episclera. The body of the implant was inserted into the pocket with the leading edge of the device around 8-10 mm from the limbus. Results: No post operative complications were detected in the operated eyes except a persistent corneal edema occupied the upper half of the cornea in one case. Hyphaema was very mild and seen only in two cases which resolved quickly two days after surgery. Endoscopical evaluation for the operated eyes revealed a normal ocular fundus with clearly visible optic papilla, tapetum and retinal blood vessels. No evidence of hemorrhage, infection, adhesions or retinal abnormalities was detected. Conclusion: Ahmed glaucoma valve is safe and effective implant for treatment of uveitic glaucoma in dogs.

Keywords: Ahmed valve, endoscopy, glaucoma, ocular fundus

Procedia PDF Downloads 576

Authors: Muhammad Yousaf Ali, Shahid Mansoor, Javeria Qazi, Imran Amin, Musarrat Shaheen

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Cotton leaf curl disease (CLCuD) is the major threat to the cotton crop and is transmitted by whitefly (Bemisia tabaci). Since multiple begomoviruses and associated satellites are involved in CLCuD, approaches based on the concept of broad-spectrum resistance are essential for effective disease control. Gro-El and G5 are two proteins from whitefly endosymbiont and M13 bacteriophage origin, respectively. Gro-El encapsulates the virus particle when it enters the whitefly and protects the virus from the immune system of the whitefly as well as prevents viral expression in it. This characteristic of Gro-El can be exploited to get resistance against viruses if expressed in plants. G5 is a single-stranded DNA binding protein, expression of which in transgenic plants will stop viral expression on its binding with ssDNA. The use of tissue-specific promoters is more efficient than constitutive promoters. Transgenics of Nicotiana benthamiana for Gro-El under constitutive promoter and Gro-El under phloem specific promoter were made. In comparison to non-transgenic plants, transgenic plants with Gro-El under NSP promoter showed promising results when challenged against cotton leaf curl Multan virus (CLCuMuV) along with cotton leaf curl Multan beta satellite (CLCuMB), cotton leaf curl Khokhran virus (CLCuKoV) along with cotton leaf curl Multan beta satellite (CLCuMB) and Pedilenthus leaf curl virus (PedLCV) along with Tobacco leaf curl beta satellite (TbLCB).

Keywords: cotton leaf curl disease, whitefly, endosymbionts, transgenic, resistance

Procedia PDF Downloads 90

Authors: M. N. Khajavi, S. Nasiri, E. Farokhi, M. R. Bavir

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Alcohol fuels are renewable, have low pollution and have high octane number; therefore, they are important as fuel in internal combustion engines. Percentage detection of these alcoholic fuels with gasoline is a complicated, time consuming, and expensive process. Nowadays, these processes are done in equipped laboratories, based on international standards. The aim of this research is to determine percentage detection of different fuels based on vibration analysis of engine block signals. By doing, so considerable saving in time and cost can be achieved. Five different fuels consisted of pure gasoline (G) as base fuel and combination of this fuel with different percent of ethanol and methanol are prepared. For example, volumetric combination of pure gasoline with 10 percent ethanol is called E10. By this convention, we made M10 (10% methanol plus 90% pure gasoline), E30 (30% ethanol plus 70% pure gasoline), and M30 (30% Methanol plus 70% pure gasoline) were prepared. To simulate real working condition for this experiment, the vehicle was mounted on a chassis dynamometer and run under 1900 rpm and 30 KW load. To measure the engine block vibration, a three axis accelerometer was mounted between cylinder 2 and 3. After acquisition of vibration signal, eight time feature of these signals were used as inputs to an Adaptive Neuro Fuzzy Inference System (ANFIS). The designed ANFIS was trained for classifying these five different fuels. The results show suitable classification ability of the designed ANFIS network with 96.3 percent of correct classification.

Keywords: internal combustion engine, vibration signal, fuel composition, classification, ANFIS

Procedia PDF Downloads 396

Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 341

Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

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With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: component carrier, carrier aggregation, LTE-advanced, scheduling

Procedia PDF Downloads 193

Authors: Ho-Dae Chong, Jong-Kil Kim

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Collaborative research has become more prevalent and important across disciplines because it stimulates innovation and interaction between scholars. Seeing as existing studies relatively disregarded the institutional conditions triggering collaborative research, this work aims to analyze the changing trend in collaborative work patterns among Korean social scientists. The focus of this research is the performance of social scientists who received research grants through the government’s Social Science Korea (SSK) program. Using quantitative statistical methods, collaborative research patterns in a total of 2,354 papers published under the umbrella of the SSK program in peer-reviewed scholarly journals from 2013 to 2016 were examined to identify changing trends and triggering factors in collaborative research. A notable finding is that the share of collaborative research is overwhelmingly higher than that of individual research. In particular, levels of collaborative research surpassed 70%, increasing much quicker compared to other research done in the social sciences. Additionally, the most common composition of collaborative research was for two or three researchers to conduct joint research as coauthors, and this proportion has also increased steadily. Finally, a strong association between international journals and co-authorship patterns was found for the papers published by SSK program researchers from 2013 to 2016. The SSK program can be seen as the driving force behind collaboration between social scientists. Its emphasis on competition through a merit-based financial support system along with a rigorous evaluation process seems to have influenced researchers to cooperate with those who have similar research interests.

Keywords: coauthorship, collaboration, competition, cooperation, Social Science Korea, policy

Procedia PDF Downloads 222

Authors: Seyyed Kavous Abbasi

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Technical and professional branch is a subcategory of high school educational system. It deals with the programs which have been designed for the promotion of applied science and necessary skill and growth of potential talents in students. The purpose of performance of this branch is preparing of preponderance of in police in different section of industries and service. The aim of this research is the survey of group relation family, economic, educational and individual factors and the student's tendency toward technical professional courses. The method of the study is descriptive survey. 195 subjects were chosen randomly from all the male and female students of technical and professional school in Izeh. Instrument for this research was research-made questionnaire consisting of 22 questions on the base of likers spectrum. The reliability of this questionnaire has been estimated 0.8. Analyses of research data has been performed in two levels of descriptive and inferential statistics. Analyses of data has shown that the family factors with average of 3.12, individual factors 3.95, economic factors 3.92 and educational factors 3.57 more than middle level have more effects , in comparison with the factor of group relation with average of 2.79 less than average level in tendency the technical and professional course . Comparison of effective factors in tendency to technical and professional course has shown that individual factors had the most effects and the group relation factors had the least effects. Comparison between male and female subject's ideas showed that there is a different between their ideas about economics and family factors.

Keywords: high school, relation family, individual factors, analysis interest

Procedia PDF Downloads 241

Authors: Mohammed Sherzad

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The Sahara desert covers third of the total surface of Africa with a quarter of this area within the national boundaries of Algeria. Sand drift and deposition is considered one of the major factors of the desertification process in the area. It is estimated that a third of the world's hot arid lands are covered by aeolian sand deposits, forming extensive sand bedforms. The Gourrara region in the Grand Erg Occidental (west of Algerian Sahara) and the region of Souf in the Grand Erg Oriental (east of Algerian Sahara) have been chosen as case studies. These were significant cultural and trading centers for many centuries despite their remote location and their harsh desert environment particularly solar radiation and sand drift and deposition. The architecture of the sustained vernacular settlements in each of the two regions has unique design features for this environment. So do the irrigation systems used - palm groves and the foggara system for capturing and distributing groundwater. However, the ecological balance which enabled the Saharans to live with the desert has been upset. New buildings often use technology based on models imported or imposed from areas that climatically have little in common. These make the inhabitants live ‘in the desert’ rather than ‘with the desert’. This paper will describe the qualities of the vernacular architecture and demonstrate its effectiveness and adaptability to the region’s harsh desert environment in comparison with contemporary buildings. Developing design guides and approaches based on lessons from the traditional architecture is important to ensure sustained livelihoods of the inhabitants in these areas.

Keywords: vernacular architecture, desert architecture, hot climate, aeolian sand deposition

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Authors: Christiane Paulus

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Post-Islamism assumes that the Quran should not be viewed in terms of what Lyotard identifies as a ‘meta-narrative'. However, its socio-ethical content can be viewed as critical of power discourse (Foucault). Practicing religion seems to be limited to rites and individual spirituality, taqwa. Alternatively, can we build on Muhammad Abduh's classic-modern reform and develop it through a postmodernist frame? This is the main question of this study. Through his general and vague remarks on the context of the Quran, Abduh was the first to refer to the historical and cultural distance of the text as an obstacle for interpretation. His application, however, corresponded to the modern absolute idea of authentic sharia. He was followed by Amin al-Khuli, who hermeneutically linked the content of the Quran to the theory of evolution. Fazlur Rahman and Nasr Hamid abu Zeid remain reluctant to go beyond the general level in terms of context. The hermeneutic circle, therefore, persists in challenging, how to get out to overcome one’s own assumptions. The insight into and the acceptance of the lasting ambivalence of understanding can be grasped as a postmodern approach; it is documented in Derrida's discovery of the shift in text meanings, difference, also in Lyotard's theory of différend. The resulting mixture of meanings (Wolfgang Welsch) can be read together with the classic ambiguity of the premodern interpreters of the Quran (Thomas Bauer). Confronting hermeneutic difficulties in general, Niklas Luhmann proves every description an attribution, tautology, i.e., remaining in the circle. ‘De-tautologization’ is possible, namely by analyzing the distinctions in the sense of objective, temporal and social information that every text contains. This could be expanded with the Kantian aesthetic dimension of reason (critique of pure judgment) corresponding to the iʽgaz of the Coran. Luhmann asks, ‘What distinction does the observer/author make?’ Quran as a speech from God to the first listeners could be seen as a discourse responding to the problems of everyday life of that time, which can be viewed as the general goal of the entire Qoran. Through reconstructing koranic Lifeworlds (Alfred Schütz) in detail, the social structure crystallizes the socio-economic differences, the enormous poverty. The koranic instruction to provide the basic needs for the neglected groups, which often intersect (old, poor, slaves, women, children), can be seen immediately in the text. First, the references to lifeworlds/social problems and discourses in longer koranic passages should be hypothesized. Subsequently, information from the classic commentaries could be extracted, the classical Tafseer, in particular, contains rich narrative material for reconstructing. By selecting and assigning suitable, specific context information, the meaning of the description becomes condensed (Clifford Geertz). In this manner, the text gets necessarily an alienation and is newly accessible. The socio-ethical implications can thus be grasped from the difference of the original problem and the revealed/improved order/procedure; this small step can be materialized as such, not as an absolute solution but as offering plausible patterns for today’s challenges as the Agenda 2030.

Keywords: postmodern hermeneutics, condensed description, sociological approach, small steps of reform

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Susan P. Teru, Jerome Nyameh

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Many contemporary organizations are placing a greater emphasis on business enterprise systems as a means of generating higher levels of economic development and sustainability. Many business research and literature has also concur that enterprise drive economic development, giving little or no credit to social enterprise, whose profit is reinvest to the community development compare to the business enterprise that share their profit to shareholders. Economic development and corporate sustainability includes economic policies that affect the beneficiaries of the economic entity and how it support corporate sustainability as a multifaceted concept that requires organizational change and adaptation on different levels. In this paper, we provide a closer examination of this suggested link between the social enterprise orientation of an organization and the pursuit of corporate sustainability. We suggest that producing social enterprise increments may be best achieved by orienting social enterprise entrepreneurs system to promote economic development and corporate sustainability, which is the new approach to organizational excellent. To this end, we describe a new approach to the social enterprise process that includes social entrepreneur and the key drivers of economic development and corporate sustainability at each stage. We present a model of social enterprise that incorporates the main ideas of the paper and suggests a new perspective for thinking about how to foster and manage social enterprise to achieve high levels of economic development and corporate sustainability as a new ways of achieving organizational excellence. Specifically, we seek to assess (1) what constitutes a corporate sustainability-oriented organization culture, (2) whether it is possible for organizations to display a unified corporate sustainability as a result of social enterprise (3) whether organizations can become more sustainable through social enterprise change.

Keywords: social enterprise orientation, organization, the pursuit of corporate sustainability, business and management

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Authors: Oxana Vasilyeva

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This paper draws on research in progress focusing on independent art in the Russian Federation. I am using the concept of independent art to mean art free from state control and established restrictive narratives. The Russian state pursues its interests by supporting or forbidding certain forms of art, and art that promotes values in opposition to the official political course is often forbidden. Arguments presented below draw from fieldwork carried out in Russian cities of Moscow and Saint Petersburg in June – August 2019, which included in-depth interviews with artists. This research explores socially engaged artistic works and their effect on socio-political state of affairs. It argues that artistic works entering public places have a potential to challenge autocratic system and inspire civil society to be critically engaged and to be capable to resist state propaganda. I am focusing on those artists who have a critical stance towards the current Russian political regime and analyzing their works in terms of transgression. By using the framework of transgression I aim to demonstrate how artists step across existing norms with their art influencing political and social order. To show the connection between the factors mentioned above, I will turn to two examples of transgressive aesthetics; one is individual and another is collective. The first example is Konstantin Benkovich, an artist who makes his works out of steel rebar, which is considered to be a symbol of the lack of freedom, as it is usually encountered in prison settings. The second example is a collective art practice called Monstration. It combines techniques of a demonstration and a carnival atmosphere. In 2019 Monstration was held in 30 Russian cities, despite the dissatisfaction of the authorities.

Keywords: art, culture, resistance, Russia

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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Authors: Hamad Albadr

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With a rapid influence to sustain the needs for global trends that had arisen for the increasing complexities in health-care provision, the increasing number of health professionals at different levels, and the need to assure more equitable access to health care, the great variation in the levels of initial education for health care professional around the world had been assign bachelor's degree as the minimum point of entry to the health professions. This intent had affected all the health care professions including biomedical engineering. In Saudi Arabia, these challenges add more pressure to retain the global trends for associate degree graduates to upgrade their education to the bachelor's degree or called birding. This paper is to review the reality of biomedical technology programs that offered in Saudi Arabia by Technical Colleges or Community Colleges nationwide and the challenges that face these colleges to run such bridging program to achieve the Bachelor's degree in biomedical engineering and the official requirements by the Ministry of Higher Education and to maintain the international standards. The author will use strategic planning methodology for designing the biomedical engineering bridging of bachelor's program by reviewing the responsibilities of the biomedical engineers in hospitals through their job descriptions to determine the job assessment needs in advance to Developing a Curriculum (DACUM) through Instructional System Design (ISD) approach via five steps: Analysis, Design, Development, Implement, Evaluate (ADDIE).

Keywords: bachelor's degree bridging, biomedical engineering program, Saudi Arabia, Riyadh College of Technology

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Authors: Kawthar F. Albasri, Abdullah M. AlHudaithi, Dana B. AlTurairi, Abdullaziz S. AlQuraini, Adoub Y. AlDerazi, Reem A. Hubail, Haitham A. Jahrami

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Several studies have found that medical students have a significant prevalence of anxiety. The purpose of this review paper is to carefully evaluate the current research on anxiety among medical students in the MENA region and, as a result, estimate the prevalence of these disturbances. Multiple databases, including the CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, Embase, MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, PsycINFO (Psychological Information Database), Scopus, Web of Science, UpToDate, ClinicalTrials.gov, WHO Global Health Library, EbscoHost, ProQuest, JAMA Network, and ScienceDirect, were searched. The retrieved article reference lists were rigorously searched and rated for quality. A random effects meta-analysis was performed to compute estimates. The current meta-analysis revealed an alarming estimated pooled prevalence of anxiety (K = 46, N = 27023) of 52.5% [95%CI: 43.3%–61.6%]. A total of 62.0% [95% CI 42.9%; 78.0%] of the students (K = 18, N = 16466) suffered from anxiety during the COVID-19 pandemic, while 52.5% [95% CI 43.3%; 61.6%] had anxiety before COVID-19. Based on the GAD-7 measure, a total of 55.7% [95%CI 30.5%; 78.3%] of the students (K = 10, N = 5830) had anxiety, and a total of 54.7% of the students (K = 18, N = 12154) [95%CI 42.8%; 66.0%] had anxiety using the DASS-21 or 42 measure. Anxiety is a common issue among medical students, making it a genuine problem. Further research should be conducted post-COVD 19, with a focus on anxiety prevention and intervention initiatives for medical students.

Keywords: anxiety, medical students, MENA, meta-analysis, prevalence

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Authors: Katherine Maurer

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Background and purpose: Violence that occurs within families is a global social problem. Children who are victims or witness to family violence are at risk for many negative effects both proximally and distally. One of the most disconcerting long-term effects occurs when child victims become adult perpetrators: the intergenerational transmission of family violence (ITFV). Early identification of those children most at risk for ITFV is needed to inform interventions to prevent future family violence perpetration and victimization. Only about 25-30% of child family violence victims become perpetrators of adult family violence (either child abuse, partner abuse, or both). Prior research has primarily been conducted using dichotomous measures of exposure (yes; no) to predict ITFV, given the low incidence rate in community samples. It is often assumed that exposure to greater amounts of violence predicts greater risk of ITFV. However, no previous longitudinal study with a community sample has tested a dose-response model of exposure to physical child abuse and parental physical intimate partner violence (IPV) using count data of frequency and severity of violence to predict adult ITFV. The current study used advanced statistical methods to test if increased childhood exposure would predict greater risk of ITFV. Methods: The study utilized 3 panels of prospective data from a cohort of 15 year olds (N=338) from the Project on Human Development in Chicago Neighborhoods longitudinal study. The data were comprised of a stratified probability sample of seven ethnic/racial categories and three socio-economic status levels. Structural equation modeling was employed to test a hurdle regression model of dose-response to predict ITFV. A version of the Conflict Tactics Scale was used to measure physical violence victimization, witnessing parental IPV and young adult IPV perpetration and victimization. Results: Consistent with previous findings, past 12 months incidence rates severity and frequency of interpersonal violence were highly skewed. While rates of parental and young adult IPV were about 40%, an unusually high rate of physical child abuse (57%) was reported. The vast majority of a number of acts of violence, whether minor or severe, were in the 1-3 range in the past 12 months. Reported frequencies of more than 5 times in the past year were rare, with less than 10% of those reporting more than six acts of minor or severe physical violence. As expected, minor acts of violence were much more common than acts of severe violence. Overall, regression analyses were not significant for the dose-response model of ITFV. Conclusions and implications: The results of the dose-response model were not significant due to a lack of power in the final sample (N=338). Nonetheless, the value of the approach was confirmed for the future research given the bi-modal nature of the distributions which suggest that in the context of both child physical abuse and physical IPV, there are at least two classes when frequency of acts is considered. Taking frequency into account in predictive models may help to better understand the relationship of exposure to ITFV outcomes. Further testing using hurdle regression models is suggested.

Keywords: intergenerational transmission of family violence, physical child abuse, intimate partner violence, structural equation modeling

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Authors: Elisa Silva, Rui Lança, Fátima Farinha, Miguel José Oliveira, Manuel Duarte Pinheiro, Cátia Miguel

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Tourism is one of the global engines of development. With good planning and management, it can be a positive force, bringing benefits to touristic destinations around the world. However, without constrains, boundaries well established and constant survey, tourism can be very harmful and induce destination’s degradation. In the interest of the tourism sector and the community it is important to develop the destination maintaining its sustainability. The OBSERVE project is an instrument for monitoring and evaluating the sustainability of the region of Algarve. Its main priority is to provide environmental, economic, social-cultural and institutional indicators to support the decision-making process towards a sustainable growth. In the pursuit of the objectives, it is being developed a digital platform where the significant indicators will be continuously updated. It is known that the successful development of a touristic region depends from the careful planning with the commitment of central and regional government, industry, services and community stakeholders. Understand the different perspectives of stakeholders is essential to engage them in the development planning. However, actual stakeholders’ engagement process is complex and not easy to accomplish. To create a consistent system of indicators designed to monitor and evaluate the sustainability performance of a touristic region it is necessary to access the local data and the consideration of the full range of values and uncertainties. This paper presents the OBSERVE project and describes the stakeholders´ engagement process highlighting the contributions, ambitions and constraints.

Keywords: sustainable tourism, stakeholders' engagement, OBSERVE project, Algarve region

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Authors: Sajjad Akbar, Rabia Bashir

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With the growth of the number of users, the Internet usage has evolved. Due to its key design principle, there is an incredible expansion in its size. This tremendous growth of the Internet has brought new applications (mobile video and cloud computing) as well as new user’s requirements i.e. content distribution environment, mobility, ubiquity, security and trust etc. The users are more interested in contents rather than their communicating peer nodes. The current Internet architecture is a host-centric networking approach, which is not suitable for the specific type of applications. With the growing use of multiple interactive applications, the host centric approach is considered to be less efficient as it depends on the physical location, for this, Information Centric Networking (ICN) is considered as the potential future Internet architecture. It is an approach that introduces uniquely named data as a core Internet principle. It uses the receiver oriented approach rather than sender oriented. It introduces the naming base information system at the network layer. Although ICN is considered as future Internet architecture but there are lot of criticism on it which mainly concerns that how ICN will manage the most relevant content. For this Web Content Mining(WCM) approaches can help in appropriate data management of ICN. To address this issue, this paper contributes by (i) discussing multiple ICN approaches (ii) analyzing different Web Content Mining approaches (iii) creating a new Internet architecture by merging ICN and WCM to solve the data management issues of ICN. From ICN, Content-Centric Networking (CCN) is selected for the new architecture, whereas, Agent-based approach from Web Content Mining is selected to find most appropriate data.

Keywords: agent based web content mining, content centric networking, information centric networking

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