Search results for: fuzzy network project

Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

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The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

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Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

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The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

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Authors: Jana Tchekalarova, Stela Georgieva, Petia Peneva, Petar Todorov

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In the present study, a series of bioconjugates of N-modified hemorphine analogs containing second pharmacophore cinnamic acids (CA) or caffeic (KA) were synthesized by a traditional solid-phase Fmoc chemistry method for peptide synthesis. Electrochemical and fluorimetrical analysis and in vivo anticonvulsant activity in mice were conducted on the compounds. The three CA acids (H4-CA, H5-CA, and H7-CA) and three KA acids (H4-KA, H5-KA, and H7-KA)-conjugated hemorphine derivatives showed dose-dependent anticonvulsant activity in the maximal electroshock test (MES) in mice. The KA-conjugated H5-KA derivate was the only compound that suppressed clonic seizures at the lowest dose of 0.5 µg/mouse in the scPTZ test. The activity against the psychomotor seizures in the 6-Hz test was detected only for the H4-CA (0.5 µg) and H4-KA (0.5 µg and 1 µg), respectively. The peptide derivates did not exhibit neurotoxicity in the rotarod test. Our findings suggest that conjugated CA and KA hemorphine peptides can be used as a background for developing hemorphin-related analogs with anticonvulsant activity. Acknowledgements: This study is funded by the European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project № BG-RRP-2.004-0002, "BiOrgaMCT".

Keywords: hemorphins, caffeic/cinnamic acid, anticonvulsant activity, electrochemistry, fluorimetry

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Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

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Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Bangaly Kaba

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In the global information society, the importance of the Internet cannot be overemphasized. Africa needs access to the powerful information and communication tools of the Internet in order to obtain the resources and efficiency essential for sustainable development. Unfortunately, in 2013, the data from Internetworldstats showed only 15% of African populations have access to Internet. This relative low Internet penetration rate signals a problem that may threaten the economic development, governmental efficiency, and ultimately the global competitiveness of African countries. Many initiatives were undertaken to bring the benefits of the global information revolution to the people of Africa, through connection to the Internet and other Global Information Infrastructure technologies. The purpose is to understand differences between socio-economically advantaged and disadvantaged internet users. From that, we will determine what prevents disadvantaged groups from benefiting from Internet usage. Data were collected through a survey from Internet users in Ivory Coast. The results reveal that Personal network exposure, Self-efficacy and Availability are the key drivers of continued use intention for the socio-economically disadvantaged group. The theoretical and practical implications are also described.

Keywords: digital inequality, internet, integrative model, socio-economically advantaged and disadvantaged, use continuance, Africa

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Ahmad Abubakar Sadiq, Nwohu Ndubuka Mark, Jacob Tsado, Ahmad Adam Asharaf, Agbachi E. Okenna, Enesi E. Yahaya, Ambafi James Garba

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Transmission system performance analysis is vital to proper planning and operations of power systems in the presence of deregulation. Key performance indicators (KPIs) are often used as measure of degree of performance. This paper gives a novel method to determine the transmission efficiency by evaluating the ratio of real power losses incurred from a specified transfer direction. Available Transmission Transfer Efficiency (ATTE) expresses the percentage of real power received resulting from inter-area available power transfer. The Tie line (Rated system path) performance is seen to differ from system wide (Network response) performance and ATTE values obtained are transfer direction specific. The required sending end quantities with specified receiving end ATC and the receiving end power circle diagram are obtained for the tie line analysis. The amount of real power loss load relative to the available transfer capability gives a measure of the transmission grid efficiency.

Keywords: performance, transmission system, real power efficiency, available transfer capability

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Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

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Authors: Yosr Ghozzi

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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

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Authors: Z. Herceg, V. Stulic, T. Vukusic, A. Rezek Jambrak

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Gas phase plasma treatment is a new nonthermal technology used for food and water decontamination. In this study, we have investigated influence of the gas phase plasma treatment on yeast cells of S. cerevisiae. Sample was composed of 10 mL of yeast suspension and 190 mL of 0.01 M NaNO₃ with a medium conductivity of 100 µS/cm. Samples were treated in a glass reactor with a point- to-plate electrode configuration (high voltage electrode-titanium wire in the gas phase and grounded electrode in the liquid phase). Air or argon were injected into the headspace of the reactor at the gas flow of 5 L/min. Frequency of 60, 90 and 120 Hz, time of 5 and 10 min and positive polarity were defined parameters. Inactivation was higher with the applied higher frequency, longer treatment time and injected argon. Inactivation was not complete which resulted in complete recovery. Cellular leakage (260 nm and 280 nm) was higher with a longer treatment time and higher frequency. Leakage at 280 nm which defines a leakage of proteins was higher than leakage at 260 nm which defines a leakage of nucleic acids. The authors would like to acknowledge the support by Croatian Science Foundation and research project 'Application of electrical discharge plasma for preservation of liquid foods'.

Keywords: Saccharomyces cerevisiae, inactivation, gas-phase plasma treatment, cellular leakage

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Authors: M. Danial Ismail, Turkan Sultan Yasar Ismail, Mehmet Cetin

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Eco-design issues are seldom addressed as a major importance in most projects in Turkey. Cities undergo a rapid urban expansion with less awareness and focus on green spaces. The aim of this paper is firstly to analyse the graduating landscape architecture students of Kastamonu University’s perception on the new course content that discusses the relationship of art, space and nature in the context of landscape architectural design using the perception analysis methodology. Secondly, this paper also addresses how these elements synthesize together in an artistic perception in concept and form. In this study, a new coursework subject was introduced as a part of the curriculum for the 4th year students of the undergraduate program and project proposals dealing with the concept of art, space and nature were discussed and graded. Simulations of contemporary art installations in gallery spaces are built upon the concept of critical awareness to ecological problems. These concepts and simulations are important as they will influence future developments and projects. This paper will give an insight to scholars and professionals regarding new concepts of multidisciplinary education strategies and its positive effects on critical and creative design thinking within the scope of ecological design.

Keywords: art, ecological design, landscape architecture curriculum, space and nature

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.

Keywords: sustainability, curricula improvement, robotics, STEP program

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Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: robotic, automated, production, offline programming, CAD

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Authors: Tam Nguyen

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Self-leadership is strongly tied to the ability to be resilient in the face of adversity. This study aims to demonstrate how a strategy based on a culturally relevant "bamboo metaphor" enables Asian students to cross cultural boundaries and to engage in online discussions to unlock their self-leadership potential. Asian students are influenced to varying degrees by the Confucian heritage culture, which educates students to respect authority, maintain harmony, and avoid public confrontations. This has a significant impact on the cultural readiness of Asian students to express their development as self-leaders. In this research project, researchers as mentors individually assist students, cultivate cognitive progress, encourage and personally ask students to join a process of mentorship program. This study analyzes and interprets the data from a large online seminar in Ho Chi Minh City, Vietnam, where students were trained in self-leadership skills. Focus-group interviews were implemented among 90 students in the program. Findings reveal the emotional needs of Asian students and suggest a cognitive model for developing students' self-awareness, self-confidence, and self-efficacy. The research results are anticipated to be applicable to a broader Asian population with a comparable cultural environment to Vietnam.

Keywords: self-leadership, bamboo resilience, cognitive modeling, Asian culture

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Authors: Xing Zhang

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Since the State Council of China issued the Regulations on the Conservation of Historical Cultural Towns and Villages in 2008, formulation of conservation planning has been carried out in national, provincial and municipal historical and cultural villages for protection needs, which provides a legal basis for inheritance of historical culture and protection of historical resources. Although the quantity and content of the conservation planning are continually increasing, the implementation and application are still ambiguous. To solve the aforementioned problems, this paper explores methods to enhance the implementation of conservation planning from the perspective of planning formulation. Specifically, the technical framework of "overall objectives planning - sub-objectives planning - zoning guidelines - implementation by stages" is proposed to implement the planning objectives in different classifications and stages. Then combined with details of the Qiqiao historical and cultural village conservation planning project in Ningbo, five sub-objectives are set, which are implemented through the village zoning guidelines. At the same time, the key points and specific projects in the near-term, medium-term and long-term work are clarified, and the spatial planning is transformed into the action plan with time scale. The proposed framework and method provide a reference for the implementation and management of the conservation planning of historical and cultural villages in the future.

Keywords: conservation planning, planning by stages, planning implementation, zoning guidelines

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Authors: Irfan U. Din

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The growing presence and operational capacity of Islamic State aka Daesh, which emerged in Pak-Afghan region in 2015, poses a serious threat to the already fragile state of the security situation in the region. This paper will shed light on the current state of IS-K network in the Pak-Afghan region and will explain how its presence and operational capacity in the northern and central Afghanistan has increased despite intensive military operations against the group in Nangarhar province – the stronghold of IS-K. It will also explore the role of Pakistani Taliban in the emergence and expansion of IS-K in the region and will unveil the security implication of growing nexus of IS-K and transnational organized groups for the region in Post NATO withdrawal scenario. The study will be qualitative and will rely on secondary and primary data to explore the topic. For secondary data existing literature on the topic will be extensively reviewed while for primary data in-depth interviews will be conducted with subject experts, Taliban commanders, and field researchers.

Keywords: Islamic State of Khorasan (IS-K), North Atlantic Treaty Organization (NATO), Pak-Afghan Region, Transnational Organized Crime (TNOC)

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Haozhe Xiang

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With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

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Authors: Jarumon Nookhong, Thanakorn Uiphanit

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This study is a research and development project which aims to develop XML Resume System to be the standard system in Thailand as well as to measure the efficiency of the XML Resume System in Thailand. This research separates into 2 stages: 1) to develop XML Document System to be the standard in Thailand, and 2) to experiment the system performance. The sample in this research is committed by 50 specialists in the field of human resources by selecting specifically. The tool that uses in this research is XML Resume System in Thailand and the performance evaluation format of system while the analysis of the data is calculated by using average and standard deviation. The result of the research found that the development of the XML Resume System that aims to be the standard system in Thailand had the result 2.67 of the average which is in a good level. The evaluation in testing the performance of the system had been done by the specialists of human resources who use the XML Resume system. When analyzing each part, it found out that the abilities according to the user’s requirement from specialists in the field of human resources, the convenience and easiness in usages, and the functional competency are respectively in a good level. The average of the ability according to the user’s need from specialists of human resources is 2.92. The average of the convenience and easiness in usages is 2.56. The average of functional competency is 2.53. These can be used as the standard effectively.

Keywords: resume, XML, XML schema, computer science

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Authors: Mallikarjuna Rao Yamarthy, Subramanyam Makam Venkata, Satya Prasad Kodati

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The main objective of the proposed work is to reduce the overall network traffic incurred by mobility management, packet delivery cost and to increase the resource utilization. The proposed algorithm, An Efficient Resource Management Algorithm (ERMA) for mobility management in wireless mesh networks, relies on pointer based mobility management scheme. Whenever a mesh client moves from one mesh router to another, the pointer is set up dynamically between the previous mesh router and current mesh router based on the distance constraints. The algorithm evaluated for signaling cost, data delivery cost and total communication cost performance metrics. The proposed algorithm is demonstrated for both internet sessions and intranet sessions. The proposed algorithm yields significantly better performance in terms of signaling cost, data delivery cost, and total communication cost.

Keywords: data delivery cost, mobility management, pointer forwarding, resource management, wireless mesh networks

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Authors: Luisa Barreira, Viana Castaneda, Maria J. Rodrigues, Florinda Gama, Tamara Santos, Marta Oliveira, Catarina Pereira, Maribela Pestana, Pedro Correia, Miguel Salazar, Carla Nunes, Luisa Custodio, Joao Varela

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In the last century, the world witnessed an exponential demographic increase that has put an enormous pressure on agriculture and food production. Associated also with climate changes, there has been a decrease in the amount of available freshwater and an increased salinization of soils which can affect the production of most food crops. Halophytes, however, are plants able to withstand high salinities while maintaining a good growth productivity. To cope with the excess salt, they produce secondary metabolites (e.g. vitamins and phenolic compounds) which, along with the natural presence of some minerals, makes them not only nutritionally rich but also functional foods. Some halophytes, as quinoa or salicornia, are already used in some countries, mostly as gourmet food. Hydroponic cultivation of halophytes using seawater or diluted seawater for watering can decrease the pressure on freshwater resources while producing a nutritional and functional food. The XtremeGourmet project funded by the EU aims to develop and optimize the production of different halophytes by hydroponics. One of the more specific objectives of this project is the study of halophytes’ productivity and chemical composition under different abiotic conditions, e.g. salt and nutrient concentration and light intensity. Three species of halophytes commonly occurring in saltmarshes of the South of Portugal (Inula chrithmoides, Salicornia ramosissima and Mesembryanthemum nodiflorum) were cultivated using hydroponics under different salinities, ranging from 5 to 45 dS/m. For each condition, several parameters were assessed namely: total and commercial productivity, electrical conductivity, total soluble solids, proximal composition, mineral profile, total phenolics, flavonoids and condensed tannins content and antioxidant activity. Results show that productivity was significantly reduced for all plants with increasing salinity up to salinity 29 dS/m and remained low onwards. Oppositely, the electrical conductivity and the total soluble solids content of the produced plants increased with salinity, reaching a plateau at 29 dS/m. It seems that plants reflect the salt concentration of the water up to some point, being able to regulate their salt content for higher salinities. The same tendency was observed for the ash content of these plants, which is related to the mineral uptake from the cultivating media and the plants’ capacity to both accumulate and regulate ions’ concentration in their tissues. Nonetheless, this comes with a metabolic cost which is observed by a decrease in productivity. The mineral profile of these plants shows high concentrations of sodium but also high amounts of potassium. In what concerns the microelements, these plants appear to be a good source of manganese and iron and the low amounts of toxic metals account for their safe consumption in moderate amounts. Concerning the phenolics composition, plants presented moderate concentrations of phenolics but high amounts of condensed tannins, particularly I. crithmoides which accounts for its characteristic sour and spicy taste. Contrary to some studies in which higher amounts of phenolics were found in plants cultivated under higher salinities, in this study, the highest amount of phenolic compounds were found in plants grown at the lowest or intermediate salinities. Nonetheless, there was a positive correlation between the concentration of these compounds and the antioxidant capacity of the plants’ extracts.

Keywords: functional properties, halophytes, hydroponics, nutritional composition, salinity effect

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Authors: Yu Hung Chiang, Hei Chia Wang

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In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: V. V. Singh

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In this paper we have focused on the study of a Linux operating system connected in a LAN (local area network). We have considered two different topologies STAR topology (subsystem-1) and BUS topology (subsystem-2) which are placed at two different places and connected to a server through a hub. In both topologies BUS topology and STAR topology, we have assumed 'n' clients. The system has two types of failure partial failure and complete failure. Further the partial failure has been categorized as minor partial failure and major partial failure. It is assumed that minor partial failure degrades the subsystem and the major partial failure brings the subsystem to break down mode. The system can completely failed due to failure of server hacking and blocking etc. The system is studied by supplementary variable technique and Laplace transform by taking different types of failure and two types of repairs. The various measures of reliability like availability of system, MTTF, profit function for different parametric values has been discussed.

Keywords: star topology, bus topology, hacking, blocking, linux operating system, Gumbel-Hougaard family copula, supplementary variable

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

Abstract:

Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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Authors: Aileen F. Wang

Abstract:

Mammography has been one of the most reliable methods for early detection and diagnosis of breast cancer. However, mammography misses about 17% and up to 30% of breast cancers due to the subtle and unstable appearances of breast cancer in their early stages. Recent computer-aided diagnosis (CADx) technology using Zernike moments has improved detection accuracy. However, it has several drawbacks: it uses manual segmentation, Zernike moments are not robust, and it still has a relatively high false negative rate (FNR)–17.6%. This project will focus on the development of a novel breast cancer detection algorithm to automatically segment the breast mass and further reduce FNR. The algorithm consists of automatic segmentation of a single breast mass using Point Region Growing Segmentation, reconstruction of the segmented breast mass using Pseudo-Zernike moments, and classification of the breast mass using the root mean square (RMS). A comparative study among the various algorithms on the segmentation and reconstruction of breast masses was performed on randomly selected mammographic images. The results demonstrated that the newly developed algorithm is the best in terms of accuracy and cost effectiveness. More importantly, the new classifier RMS has the lowest FNR–6%.

Keywords: computer aided diagnosis, mammography, point region growing segmentation, pseudo-zernike moments, root mean square

Procedia PDF Downloads 444

Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

Abstract:

Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

Procedia PDF Downloads 357