Search results for: tourist automated plan

Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: Ananth Malali, Rohan Prasad, Ananth Revankar, Chiranth Hulgur

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This paper aims to show evidence that value creation by sustainable methods is achieved when a relation is shared with a sustainability attribute between two or more companies in every stage of the supply chain. The pillars of this paper, the value creation factors, attributes of sustainability and various relations that exist between firms in a horizontally integrated supply chain are defined. Further, a relational analysis was done using a simple analysis tool built based on research. Couple of case studies from the German manufacturing and Australian retail sectors were considered for the intra industry analysis and comparison. Taking the analysis ahead, for inter-industry comparison, the same cases were scrutinised in order to understand how the sustainability attributes change across each industry. Concluding, this paper gives an overview of how companies can plan their strategies to attain sustainability through horizontal integration.

Keywords: horizontal integration, value creation, sustainable supply chain

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Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

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We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

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Authors: Alireza Lohrasbi, Alireza Lavaei, Mohammadali M. Shahlaei

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The liquid flow and the free surface shape during the initial stage of dam breaking are investigated. A numerical scheme is developed to predict the wave of an unsteady, incompressible viscous flow with free surface. The method involves a two dimensional finite element (2D), in a vertical plan. The Naiver-Stokes equations for conservation of momentum and mass for Newtonian fluids, continuity equation, and full nonlinear kinematic free-surface equation were used as the governing equations. The mapping developed to solve highly deformed free surface problems common in waves formed during wave propagation, transforms the run up model from the physical domain to a computational domain with Arbitrary Lagrangian Eulerian (ALE) finite element modeling technique.

Keywords: dam break, Naiver-Stokes equations, free-surface flows, Arbitrary Lagrangian-Eulerian

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Authors: Vishnu Pratap Singh Kirar, Madhuri Saxena

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Advancement in sequence data generation technologies is churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. With so much data available, the use of machine learning methods and tools to make novel inferences has become obvious. Machine learning methods have been successfully applied to a lot of disciplines, including computational biology and bioinformatics. Researchers in computational biology are interested to develop novel machine learning frameworks to classify the huge amounts of biological data. In this proposal, it plan to employ novel machine learning approaches to aid the understanding of how apparently innocuous mutations (in intergenic DNA and at synonymous sites) cause diseases. We are also interested in discovering novel functional sites in the genome and mutations in which can affect a phenotype of interest.

Keywords: genome wide association studies (GWAS), next generation sequencing (NGS), deep learning, omics

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Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

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Nowadays, illegal logging has been causing much effect to our forest. Some of it causes a flash flood, avalanche, global warming, and etc. This comprehensibly makes us wonder why, what, and who has made it happened. Often, it already has been too late after we have known the cause of it. Even the Malaysian Royal Belum forest has not been spared from land clearing or illegal activity by the natives although this area has been gazetted as a protected area preserved for future generations. Furthermore, because of its sizeable and wide area, these illegal activities are difficult to monitor and to maintain. A critical action must be called upon to prevent all of these unhealthy activities from recurrence. Therefore, a remote monitoring device must be developed in order to capture critical real-time data such as temperature, humidity, gaseous, fire, and rain detection which indicates the current and preserved natural state and habitat in the forest. Besides, this device location can be detected via GPS by showing the latitudes and longitudes of its current location and then to be transmitted by SMS via GSM system. All of its readings will be sent in real-time for data management and analysis. This result will be benefited to the monitoring bodies or relevant authority in keeping the forest in the natural habitat. Furthermore, this research is to gather a unified data and then will be analysed for its comparison with an existing method.

Keywords: remote monitoring system, forest data, GSM, GPS, wireless sensor

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Authors: Marc Polo, Núria Arbonés Arán

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Amsterdam is considered one of the great European capitals, which concentrates the headquarters of various multinational companies and which, in addition, enjoys a huge tourist attraction. Its typical residential buildings next to the canals, the museums, or its striking "Red Light District" are a great focus of attraction. In 2019 almost 9 million tourists visited it, but few of them traveled to the farthest neighborhood in the city: Amsterdam-Zuidoost (Amsterdam-Southeast). This neighborhood is geographically separated from the urban core, which makes it an exclave of Amsterdam as it does not border any of the other boroughs. Bijlmermeer neighborhood is the largest of the Amsterdam-Zuidoost, and it was born in the 1960s with the expectations of becoming the city of the future. Its main architect, Siegfried Nassuth, was inspired by the Swiss Le Corbusier to design nearly 18,000 homes, most of which were in high-rise tower blocks and built together, forming a recognizable "honeycombed" pattern. For more than 40 years, a series of infrastructure and social vicissitudes have made the neighborhood outline quite different as it was expected to be. It helped also varied elements such as ethnicity, demolitions, or unoccupied apartments. The called “city of the future” became home to immigrants, drug addicts, and vandals, and the conflicts denigrated the Amsterdam-Zuidoost. This work analyzes the evolution of the Bijlmermeer from its origins and illustrates relevant international referents able to help the area. The purpose of the work is to show how different variations along the recent history didn't help enough, but how there are positive perspectives for the future taking advantage of the food as a creative issue. The research, based on academic literature, existing material in different stadiums, plus the analysis of the city imaginaries, will help to concrete relevant elements in terms of innovation, creativity, and disruption. Despite of radical renewal that is taking place, the research will demonstrate that there are still new opportunities for the old Bijlmermeer.

Keywords: amsterdam, bijlmermeer, creativity, food

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Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

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Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

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Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

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Authors: Mehmet Sinan Erguven

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Modern art is relatively new but a popular area in Turkish art society. Modern art museums are mainly located in big cities like Istanbul and Ankara where cultural life is more dynamic. Odunpazarı Modern Museum (OMM) will open its doors on September 2019 and be the only modern art museum located in a small town in Turkey. OMM executives declare the mission of the museum as; art must go beyond the metropolises of the world, give a new lease of life to cities that make a difference with their cultural texture, and reach a greater audience through that expansion. So OMM will not only serve as a museum but a landmark for regenerating the city brand of Eskişehir like the Guggenheim in Bilbao. OMM is located in the Odunpazarı area, the heart of Eskişehir. Named after the historical timber market it once hosted, Odunpazarı is a nominated site for the UNESCO Intangible Cultural Heritage List, and is Eskişehir’s first area of settlement. This study focuses on the complex nature of opening a modern art museum in a small town. The management and marketing dynamics of OMM are discussed in the study. Content analysis technique is used on local and national news to display the perception differences before and after the opening of OMM. In depth interviews with the executives of the museum are conducted in order to enlighten the insights of opening a modern art museum in a small town. Early findings of the content analysis point out that, the comments on the national press are mostly positive. On the other hand, different views occur on the local press. The location OMM is constructed and grandness of the museum building are criticized by some of the local newspapers. OMM’s potential as a tourist attraction is agreed by most of the media. OMM executives stated the most challenging task as reaching the different target audiences on international, national and local levels. These early findings will be improved and compared shortly before and after the opening of the museum.

Keywords: management, marketing, Odunpazarı modern museum, small town

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: Radia Guerza

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Tutoring at the Algerian University has been an issue of great controversy and debate. Henceforth, the current paper is an attempt to shed light on the issue of tutoring at Algerian University. It aims to set a plan for tutoring that might meet the student's needs and challenges. It endeavors to explore the following query: “what is the role of tutoring in the Algerian university between “The CAN DO” and “The HAVE TO”? To equate with the addressed research question, an exploratory small-scale study has been carried out at Batna 2 University using questionnaires and interviews with fifty (50) teachers. Results indicate that Algerian University is still lagging behind because of the huge lack of infrastructure means, human resources, and even pedagogical resources. In addition, the majority of our teachers are reluctant to adhere to the tutorial policy due to the lack of incentives; next to that, the increasing yearly number of students and students high ratio would hardly permit any tutoring sessions. Finally, this paper is the first attempt, to our best knowledge, towards raising the awareness of our institution, staff members, teachers, and students towards the importance of tutoring and how to adopt it.

Keywords: attitudes, higher education, perceptions, tutoring

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Vilani Sachitra, Udari Bandara

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Self-efficacy beliefs provide the foundation for human motivation, well-being, and personal accomplishment. This study measured the levels of academic self-efficacy of undergraduates and also examined whether there any differences in academic self-efficacy with respect to gender and academic year. A structured questionnaire was employed to collect data from undergraduates who enrolled the Bachelor of Commerce degree programme at the University of Sri Jayewardenepura. The outcome of the study revealed that undergraduates lacked the confidence to ask and answer questions, seek help from lecturers, have a study plan and engage in academic discussion and note-taking. However, the findings also demonstrated that undergraduates were not hesitant about seeking help from friends, had confidence on meeting the deadlines and completing the degree within four years. Interestingly, females displayed higher academic self-efficacy than males. Specifically, the data were supported to conclude that there were significant differences in academic self-efficacy with respect to academic years.

Keywords: academic year, bachelor of commerce undergraduates, gender, self-efficacy

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: Rashmi Malik, Videep Mishra

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The practice of generative design has become a transformative approach for an efficient way of generating multiple iterations for any design project. The conventional way of modeling the game elements is very time-consuming and requires skilled artists to design. A 3D modeling tool like 3D S Max, Blender, etc., is used traditionally to create the game library, which will take its stipulated time to model. The study is focused on using the generative design tool to increase the efficiency in game development at the stage of prop and environment generation. This will involve procedural level and customized regulated or randomized assets generation. The paper will present the system design approach using generative tools like Grasshopper (visual scripting) and other scripting tools to automate the process of game library modeling. The script will enable the generation of multiple products from the single script, thus creating a system that lets designers /artists customize props and environments. The main goal is to measure the efficacy of the automated system generated to create a wide variety of game elements, further reducing the need for manual content creation and integrating it into the workflow of AAA and Indie Games.

Keywords: iterative game design, generative design, gaming asset automation, generative game design

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Authors: Henry Prihanto Nugroho

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This paper suggests education tourism as an option into developing more sustainable mass tourism. Identifying the potential of education tourism and developing a sustainable packages will have an impact on social economic development in the area. Indonesia especially Yogyakarta can increase their tourism earnings by tapping into this growing market phenomenon. Educational tourism, a growing part in the world tourism market, has attracted great attention because of its direct impact on the community and as an alternative strategy for poverty alleviation. Tourism is considered as one of the main industries and sectors highly contributing to economic development in Indonesia especially in Yogyakarta, this region can be an ideal case for studying the issue of educational tourism in Universitas Gadjah Mada. This paper tries to introduce the educational tourism as an important alternative source of the economy accelerator in the context of Yogyakarta Indonesia. This paper also aims to discuss the education tourism potential at the University of Gadjah Mada, Yogyakarta Indonesia then to create and established an Education Tourism package at Gadjah Mada University. Education Tourism is a means to empower academics, local community, local businesses, and to improve the economic welfare. Methods: Focus group discussions, direct observation, survey and best practice method. Conclusion: There is a positive relationship between attitude, environmental impact, economic impact, and socio-cultural impacts and practice in the field when the potential is seized. The findings incorporate insights into the socio-cultural and economic potential of education tourism and practices related to community development at the University of Gadjah Mada, Yogyakarta Indonesia by creating an Education Tourism Packages that will suit the needs of the tourist. Educational tourism can create sustainable development for local communities, academic society, universities, and stakeholders.

Keywords: education tourism, Gadjah Mada, sustainable, tourism

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Authors: Georges Bou Ghantous

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This literature review examines the transformative impact of Artificial Intelligence (AI) on higher education, highlighting both the potential benefits and challenges associated with its adoption. The review reveals that AI significantly enhances personalized learning by tailoring educational experiences to individual student needs, thereby boosting engagement and learning outcomes. Automated grading systems streamline assessment processes, allowing educators to focus on improving instructional quality and student interaction. AI's data-driven insights provide valuable analytics, helping educators identify trends in at-risk students and refine teaching strategies. Moreover, AI promotes enhanced instructional innovation through the adoption of advanced teaching methods and technologies, enriching the educational environment. Administrative efficiency is also improved as AI automates routine tasks, freeing up time for educators to engage in research and curriculum development. However, the review also addresses the challenges that accompany AI integration, such as data privacy concerns, algorithmic bias, dependency on technology, reduced human interaction, and ethical dilemmas. This balanced exploration underscores the need for careful consideration of both the advantages and potential hurdles in the implementation of AI in higher education.

Keywords: administrative efficiency, data-driven insights, data privacy, ethical dilemmas, higher education, personalized learning

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Goodarz Sabetian, Sajjad Moshfe

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Control system for hi-tech industries could be realized generally and deeply by a special document. Vast heavy industries such as power plants with a large number of I/O signals are controlled by a distributed control system (DCS). This system comprises of so many parts from field level to high control level, and junior instrument engineers may be confused by this enormous information. The key document which can solve this problem is “control configuration system diagram” for each type of DCS. This is a road map that covers all of activities respect to control system in each industrial plant and inevitable to be studied by whom corresponded. It plays an important role from designing control system start point until the end; deliver the system to operate. This should be inserted in bid documents, contracts, purchasing specification and used in different periods of project EPC (engineering, procurement, and construction). Separate parts of DCS are categorized here in order of importance and a brief description and some practical plan is offered. This article could be useful for all instrument and control engineers who worked is EPC projects.

Keywords: control, configuration, DCS, power plant, bus

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Authors: Claudia Seabra, Elisabeth Kastenholz, José Luís Abrantes, Manuel Reis

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In a world of increasing mobility and global risks, terrorism has, in a perverse way, capitalized on contemporaneous society’s growing interest in travel to explore a world whose national boundaries and distances have decreased. Terrorists have identified the modern tourist flows originated from the economically more developed countries as new appealing targets so as to: i) call attention to the causes they defend and ii) destroy a country’s foundations of tourism, with the final aim of disrupting the economic and consequently social fabric of the affected countries. The present study analyses sensitivity towards risk and travel behaviors in international travel amongst a sample of 600 international tourists from 49 countries travelling by air. Specifically, the sample was segmented according to the Global Peace Index. This index defines country profiles regarding the levels of peace. The indicators used are established over three broad themes: i) ongoing domestic and international conflict; ii) societal safety and security; and iii) militarisation. Tourists were segmented, according to their country of origin, in different levels of peacefulness. Several facets of travel behavior were evaluated, namely motivations, attitude towards trip planning, quality perception and perceived value of the trip. Also factors related with risk perception were evaluated, specifically terrorism risk perception during the trip, unsafety sensation as well as importance attributed to safety in travel. Results contribute to our understanding of the role of previous exposure to the lack of peace and safety at home in the international tourists behaviors, which is further discussed in terms of tourism management and marketing implications which should particularly interest tourism services and destinations more affected by terrorism, war, political turmoil, crime and other safety risks.

Keywords: terrorism, tourism, safety, risk perception

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Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Mahsa Fathollahzadeh

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The quick advancement of nanotechnology necessitates the creation of innovative theoretical approaches to elucidate complex experimental findings and forecast novel capabilities of nanodevices. Therefore, over the past ten years, a difficult task in quantum chemistry has been comprehending electron and spin transport in molecular devices. This thorough evaluation presents a comprehensive overview of current research and its status in the field of molecular electronics, emphasizing the theoretical applications to various device types and including a brief introduction to theoretical methods and their practical implementation plan. The subject matter includes a variety of molecular mechanisms like molecular cables, diodes, transistors, electrical and visual switches, nano detectors, magnetic valve gadgets, inverse electrical resistance gadgets, and electron tunneling exploration. The text discusses both the constraints of the method presented and the potential strategies to address them, with a total of 183 references.

Keywords: chemistry, nanotechnology, quantum, molecule, spin

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Authors: Diego de Almeida Pereira

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The roughness index of a road is considered the most important parameter about the quality of the pavement, as it has a close relation with the comfort and safety of the road users. Such condition can be established by means of functional evaluation of pavement surface deviations, measured by the International Roughness Index (IRI), an index that came out of the international evaluation of pavements, coordinated by the World Bank, and currently owns, as an index of limit measure, for purposes of receiving roads in Brazil, the value of 2.7 m/km. This work make use of the e.IRI parameter, obtained by the Roadroid app. for smartphones which use Android operating system. The choice of such application is due to the practicality for the user interaction, as it possesses a data storage on a cloud of its own, and the support given to universities all around the world. Data has been collected for six months, once in each month. The studies begun in March 2018, season of precipitations that worsen the conditions of the roads, besides the opportunity to accompany the damage and the quality of the interventions performed. About 350 kilometers of sections of four federal highways were analyzed, BR-020, BR-040, BR-060 and BR-070 that connect the Federal District (area where Brasilia is located) and surroundings, chosen for their economic and tourist importance, been two of them of federal and two others of private exploitation. As well as much of the road network, the analyzed stretches are coated of Hot Mix Asphalt (HMA). Thus, this present research performs a contrastive discussion between comfort conditions and safety of the roads under private exploitation in which users pay a fee to the concessionaires so they could travel on a road that meet the minimum requirements for usage, and regarding the quality of offered service on the roads under Federal Government jurisdiction. And finally, the contrast of data collected by National Department of Transport Infrastructure – DNIT, by means of a laser perfilometer, with data achieved by Roadroid, checking the applicability, the practicality and cost-effective, considering the app limitations.

Keywords: roadroid, international roughness index, Brazilian roads, pavement

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Authors: Mohamed Zakaulla, A. R. Anwar Khan

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Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results.

Keywords: analysis of variance, dry sliding wear, hybrid composite, orthogonal array, Taguchi technique

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Authors: Jasim Saleh Said AlDairi

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The potential of applying Lean Management in Higher Education Institutions has increased significantly in last few years, leading to tremendous savings. Reviewing and updating competencies’ curriculum matrix is one of the critical and complicated processes that consume time and effort, and this has triggered searching for a scientific and sustainable approach to manage the such review. This paper presents a novel approach of implementing Lean (5S) methodology in reviewing technical competencies required for the graduates of the Military Technological College (MTC) in the Sultanate of Oman. The 5S framework has been imbedded into an action plan using the PDCA cycle. As a result, the method applied has helped in sorting out the actual required competencies, the team has identified the required (new, amended, and deleted) competencies in all of the targeted Engineering Departments, in addition, the major wastes within the overall process were identified, and the future review process was standardized and documented.

Keywords: PDCA, 5S, lean, MTC, competencies, curriculum matrix, higher education

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

Procedia PDF Downloads 323

Authors: Hussein Alahmer, Amr Ahmed

Abstract:

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

Procedia PDF Downloads 326

Authors: Maulita Sari Hani, Abraham B. Sianipar, Jamaluddin Jompa, Natsir Nessa, Alan T. White

Abstract:

Manta ray is an icon for tourism in Raja Ampat. The tourist volume has been increased for the past ten years which up to approximately 23,000 tourists in 2017. Since 2013, Conservation International Indonesia deployed satellite and acoustic tags on manta ray in Dampier strait to track the species and identify the aggregation areas. These findings encourage the government and the local community to boost conservation through the management of marine protected areas for tourism purposes. Community in Dampier strait including the village of Arborek, Kurkapa, Kapisawar, and Sawingray involved in variety of small scale tourism business including homestay, dive shop, tour operator, and crafts. Working groups of related local businesses were established to support the local community and to ensure the sustainability of the economic viability and environmental sustainability. In order to analyze the economic benefits of manta ray tourism, this study was conducted to identify the number of local business in Dampier Strait and the economic impacts in terms of local finance security, social, humanity, individual, and physical assets. The results of this study identify 30 homestays, 2 dive shops, 10 tour operators, 30 women involved in crafts, and about 50 villagers worked for dive resorts. In addition to community assets, we confirmed the welfare of community has been improved in terms of food security, households, education for children, savings, and health insurance.

Keywords: marine wildlife tourism, elasmobranch, conservation, ecotourism, co-management, economic viability, environmental sustainability

Procedia PDF Downloads 217