Search results for: information centric network

Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

Procedia PDF Downloads 76

Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

Procedia PDF Downloads 175

Authors: Chung-Hung Tsai, Ya-Ping Li

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Tourism industry is highly depended on the natural environment and climate. Compared to other industries, it is more susceptible to environment and climate. Taiwan belongs to a sea island country and located in the subtropical monsoon zone. The events of climate variability, frequency of typhoons and rainfalls raged are caused regularly serious disaster. In traditional disaster assessment, it usually focuses on the disaster damage and risk assessment, which is short of the features from different industries to understand the impact of the restoring force in post-disaster resilience and the main factors that constitute resilience. The object of this study is based on disaster recovery experience of tourism area and to understand the main factors affecting the tourist area of disaster resilience. The combinations of literature review and interviews with experts are prepared an early indicator system of the disaster resilience. Then, it is screened through a Fuzzy Delphi Method and Analytic Network Process for weight analysis. Finally, this study will establish the tourism disaster resilience evaluation index system considering the Taiwan's tourism industry characteristics. We hope that be able to enhance disaster resilience after tourist areas and increases the sustainability of industrial development. It is expected to provide government departments the tourism industry as the future owner of the assets in extreme climates responses.

Keywords: resilience, Fuzzy Delphi Method, Analytic Network Process, industrial development

Procedia PDF Downloads 404

Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

Procedia PDF Downloads 95

Authors: Alireza Monzavi Chaleshtari, Mahnaz Aliakbari Dehkordi, Amin Asadi Hieh, Majid Kazemnezhad

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This research was conducted with the aim of determining the effectiveness of sexual cognitive behavioral therapy on psychological performance and openness to experience in women. The type of research was experimental in the form of pre-test-post-test. The statistical population of this research was made up of all working and married women with membership in the researcher's Instagram social network who had problems in marital-sexual relationships (N=900). From the statistical community, which includes working and married women who are members of the researcher's Instagram social network who have problems in marital-sexual relationships, there are 30 people including two groups (15 people in the experimental group and 15 people in the control group) as available sampling and selected randomly. They were placed in two experimental and control groups. The anxiety, stress, and depression scale (DASS) and the Costa and McCree personality questionnaire were used to collect data, and the cognitive behavioral therapy protocol of Dr. Mehrnaz Ali Akbari was used for the treatment sessions. To analyze the data, the covariance test was used in the SPSS22 software environment. The results showed that sexual cognitive behavioral therapy has a positive and significant effect on psychological performance and openness to experience in women. Conclusion: It can be concluded that interventions such as cognitive-behavioral sex can be used to treat marital problems.

Keywords: sexual cognitive behavioral therapy, psychological function, openness to experience, women

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Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

Procedia PDF Downloads 336

Authors: Chariton Christou, David Cornwell

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Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

Procedia PDF Downloads 376

Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Xinrong Li, Jiawei Dai

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Food production, food safety, and the food supply chain are causing a great challenge to human health and the environment. Different kinds of food have different environmental costs. Therefore, a healthy diet can alleviate this problem to a certain extent. In this project, an online questionnaire was conducted to understand the purchase behaviour of consumers and their attitudes towards basic food information. However, the data shows that the public's current consumption habits and ideology do not meet the long-term development of sustainable social needs. In order to solve the environmental problems caused by the unbalanced diet of the public and the social problems of unequal food distribution, the purpose of this paper is to explore how to use the emerging media of VR to visualize food supply chain information so as to attract users' attention to the environmental cost of food. In this project, the food supply chain of imported and local cheese was compared side-by-side in the virtual reality environment, including the origin, transportation, sales, and other processes, which can effectively help users understand the difference between the two processes and environmental costs. Besides, the experimental data demonstrated that the participant would like to choose low environmental cost food after experiencing the whole process.

Keywords: virtual reality, information design, food supply chain, environmental cost

Procedia PDF Downloads 97

Authors: Sabo Elizabeth

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Electronic learning is increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. This approach is important in human capital development. An investigation of open distance and e-learning facilities and information need by open and distance learning students was carried out in Jalingo, Nigeria. Structured questionnaires were administered to 70 registered ODL students of the NOUN. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Assessment of the effectiveness of ODL facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women. A large proportion of the respondents are married and there are more matured students in ODL compared to the youth. A high proportion of the ODL students obtained qualifications higher than the secondary school certificate. The proportion of computer literate ODL students was high, and large number of the students does not own a laptop computer. Inadequate e -books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities in the study areas. Inadequate computer facilities and power back up caused inconveniences and delay in administering and use of e learning facilities. To a high extent, open and distance learning students needed information on university time table and schedule of activities, availability and access to books (hard and e-books) and reference materials. The respondents emphasized that contact with course coordinators via internet will provide a better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

Procedia PDF Downloads 325

Authors: Fazli Rahim Shinwari, Ulrich Dittmer

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Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

Procedia PDF Downloads 153

Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

Procedia PDF Downloads 137

Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Daniel Suarez Alonso

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This study has tried to focus on the alternatives offered to police institutions by the implementation of Geographic Information systems. Providing operational police commanders with effective and efficient tools, providing analytical capacity to reduce criminal opportunities, must be a priority. Given the intimate connection of crimes and infractions to the environment, law enforcement institutions must respond proactively to changing circumstances of anti-norm behaviors. To this end, it has been intended to analyze the antisocial spatial distribution of the city of Móstoles, trying to identify those spatiotemporal patterns that occur to anticipate their commission through the planning of dynamic preventive strategies. The application of GIS offers alternative analytical approaches to the different problems that underlie the development of life in society, focusing resources on those places with the highest concentration of incidents.

Keywords: data analysis, police organizations, police prevention, geographic information systems

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Authors: Emin Gundogar, Aysegul Yilmaz

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Strategic performance control is a significant procedure in management. There are various methods to improve this procedure. This study introduces an information system that is developed to score performance for municipal management. The application of the system is clarified by exemplifying municipal processes.

Keywords: management information system, municipal management, performance control

Procedia PDF Downloads 477

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

Procedia PDF Downloads 120

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 103

Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

Procedia PDF Downloads 75

Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

Procedia PDF Downloads 275

Authors: Hanady Al-Zagheer

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The purpose of this paper research is to introduce the role of the social media (face book) in growing small and medium enterprises in Jordan, Today’s developments of information technologies are dazzling. Using information technologies results in having advantages in competition, decreasing costs, gaining time, and getting and sharing information. Now it is possible to state that there are different types of usage within the information technologies. Small and medium enterprises have been grown rapidly in recent years and continue to grow. Jordanian females have played a large role in the growth of entrepreneurship and have made an impact on household economics. Virtual storefronts have allowed these women to balance roles assigned by tradition and culture while becoming successful providers. If you have a small business with a limited public relations and advertising budget, Facebook can be a cost effective way to promote your services because opening an account is free. However, this can work against you if you do not maintain the page. A Face book page without frequent updates can destroy your brand value and image. According to a 2009 Computerworld article by Lisa Hoover, having a Facebook page that looks abandoned is worse than having no page at all. You might need to hire someone or pay an employee to update your business’s Facebook page.

Keywords: social media, social media small, medium enterprises, Jordan

Procedia PDF Downloads 329

Authors: Victor V. Ribeiro, Thais C. Lopes, Rafael A. A. Monteiro

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The Albatroz, Baleia Jubarte, Coral Vivo, Golfinho Rotador and Tamar projects make up the Young Sea Network (YSN), part of the BIOMAR Network, which aims to integrate the environmental youths of the Brazilian coast. For this, three editions of the Young Sea Meeting (YSM) were performed. Seeking to stimulate belonging, self-knowledge, participation, autonomy and youth protagonism, the Albatroz Project hosted the III YSM, in Bertioga (SP), in April 2019 and aimed to collectively plan the meeting. Five pillars of Environmental Education were used: identity, community, dialogue, power to act and happiness, the OCA Method and the Young Educates Young; Young Chooses Young; and One Generation Learns from the Other principals. In December 2018, still in the II YSM, the participatory planning of the III YSM began. Two "representatives" of each group were voluntarily elected to facilitate joint decisions, propose, receive and communicate demands from their groups and coordinators. The Young Albatroz Collective (YAC) facilitated the organization process as a whole. The purpose of the meeting was collectively constructed, answering the following question: "What is the YSM for?". Only two of the five pairs of representatives responded. There was difficulty gathering the young people in each group, because it was the end of the year, with people traveling. Thus, due to the short planning time, the YAC built a pre-programming to be validated by the other groups, defining as the objective of the meeting the strengthening of youth protagonism within the YSN. In the planning process, the YAC held 20 meetings, with 60 hours of face-to-face work, in three months, and two technical visits to the headquarters of the III YSM. The participatory dynamics of consultation, when it occurred, required up to two weeks, evidencing the limits of participation. The project coordinations stated that they were not being included in the process by their young people. There is a need to work more to be able to aloud the participation, developing skills and understanding about its principles. This training must take place in an articulated way between the network, implying the important role of the five projects in jointly developing and implementing educator processes with this objective in a national dimension, but without forgetting the specificities of each young group. Finally, it is worth highlighting the great potential of the III YSM by stimulating the exercise of leading environmental youth in more than 50 young people from Brazilian coast, linked to the YSN, stimulating the learning and mobilization of young people in favor of coastal and marine conservation.

Keywords: Marine Conservation, Environmental Education, Youth, Participation, Planning

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Authors: Max Plotnikov, Arkadius Schier

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To counteract climate change, the European Commission adopted the European Green Deal (EDG) in 2019. Some of the main objectives of the EDG are climate neutrality by 2050, decarbonization, sustainable mobility, and the shift from a linear economy to a circular economy in the European Union. The mobility turnaround envisages, among other things, the switch from classic internal combustion vehicles to electromobility. The aforementioned goals are therefore accompanied by increased demand for lithium-ion batteries (LIBs) and the associated logistics. However, this inevitably gives rise to challenges that need to be addressed. Depending on whether the LIB is transported by road, rail, air, or sea, there are different regulatory frameworks in the European Union that relevant players in the value chain must adhere to. LIBs are classified as Dangerous Goods Class 9, and against this backdrop, there are various restrictions that need to be adhered to when transporting them for various actors. Currently, the exchange of information in the value chain between the various actors is almost entirely paper-based. Especially in the transport of dangerous goods, this often leads to a delay in the transport or to incorrect data. The exchange of information with the authorities is particularly essential in this context. A solution for the digital exchange of information is currently being developed. Electronic freight transport information (eFTI) enables fast and secure exchange of information between the players in the freight transport process. This concept is to be used within the supply chain from 2025. Another initiative that is expected to improve the monitoring of LIB in this context, among other things, is the battery pass. In July 2023, the latest battery regulation was adopted in the Official Journal of the European Union. This battery pass gives different actors static as well as dynamic information about the batteries depending on their access rights. This includes master data such as battery weight or battery category or information on the state of health or the number of negative events that the battery has experienced. The integration of the battery pass with the eFTI platform will be investigated for synergy effects in favor of the actors for battery transport.

Keywords: battery logistics, battery passport, data sharing, eFTI, sustainability

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Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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Authors: Azizah Ismail, Zainab Khalifah, Abbas Mardani

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Sustainable community-based tourism through homestay programme is a growing niche market that has impacted destinations in many countries including Malaysia. With demand predicted to continue increasing, the importance of the homestay product will grow in the tourism industry. This research examines the sustainability criteria for homestay programme in Malaysia covering economic, socio-cultural and environmental dimensions. This research applied a two-stage methodology for data analysis. Specifically, the researcher implements a hybrid method which combines two multi-criteria decision making approaches. In the first stage of the methodology, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique is applied. Then, Analytical Network Process (ANP) is employed for the achievement of the objective of the current research. After factors identification and problem formulation, DEMATEL is used to detect complex relationships and to build a Network Relation Map (NRM). Then ANP is used to prioritize and find the weights of the criteria and sub-criteria of the decision model. The research verifies the framework of multi-criteria for sustainable community-based tourism from the perspective of stakeholders. The result also provides a different perspective on the importance of sustainable criteria from the view of multi-stakeholders. Practically, this research gives the framework model and helps stakeholders to improve and innovate the homestay programme and also promote community-based tourism.

Keywords: community-based tourism, homestay programme, sustainable tourism criteria, sustainable tourism development

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Authors: Mohammad Nehal Hasnine, Md Kamrul Hasan Chayon, Md Mobasswer Rahman

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Organizational tendencies towards computer-based information processing have been observed noticeably in the third-world countries. Many enterprises are taking major initiatives towards computerized working environment because of massive benefits of computer-based information processing. However, designing and developing information resource management software for small and mid-size enterprises under budget costs and strict deadline is always challenging for software engineers. Therefore, we introduced an approach to design mid-size enterprise software by using the Waterfall model, which is one of the SDLC (Software Development Life Cycles), in a cost effective way. To fulfill research objectives, in this study, we developed mid-sized enterprise software named “BSK Management System” that assists enterprise software clients with information resource management and perform complex organizational tasks. Waterfall model phases have been applied to ensure that all functions, user requirements, strategic goals, and objectives are met. In addition, Rich Picture, Structured English, and Data Dictionary have been implemented and investigated properly in engineering manner. Furthermore, an assessment survey with 20 participants has been conducted to investigate the usability and performance of the proposed software. The survey results indicated that our system featured simple interfaces, easy operation and maintenance, quick processing, and reliable and accurate transactions.

Keywords: end-user application development, enterprise software design, information resource management, usability

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Authors: Nungki Rositaningsih, Emil Budianto

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Starch has been widely used as an encapsulation material for drug delivery system. However, starch hydrogel is very easily degraded during metabolism in human stomach. Modification of this material is needed to improve the encapsulation process in drug delivery system, especially for gastrointestinal drug. In this research, three modified starch-based hydrogels are synthesized i.e. Crosslinked starch hydrogel, Semi- and Full- Interpenetrating Polymer Network (IPN) starch hydrogel using Poly(N-Vinyl-Pyrrolidone). Non-modified starch hydrogel was also synthesized as a control. All of those samples were compared as biomaterials, floating drug delivery, and their ability in loading drug test. Biomaterial characterizations were swelling test, stereomicroscopy observation, Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FTIR). Buoyancy test and stereomicroscopy scanning were done for floating drug delivery characterizations. Lastly, amoxicillin was used as test drug, and characterized with UV-Vis spectroscopy for loading drug observation. Preliminary observation showed that Full-IPN has the most dense and elastic texture, followed by Semi-IPN, Crosslinked, and Non-modified in the last position. Semi-IPN and Crosslinked starch hydrogel have the most ideal properties and will not be degraded easily during metabolism. Therefore, both hydrogels could be considered as promising candidates for encapsulation material. Further analysis and issues will be discussed in the paper.

Keywords: biomaterial, drug delivery system, interpenetrating polymer network, poly(N-vinyl-pyrrolidone), starch hydrogel

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Authors: Scarlet Alejandra Romano, Joni Kareco

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The three pillars of sustainability (social, economic and environmental) are relevant concepts to the Architecture, Engineering, and Construction (AEC) industry because of the increase of international agreements and guidelines related to this topic during the last years. Considering these three pillars, the AEC industry faces important challenges, for instance, to decrease the carbon emissions (environmental challenge), design sustainable spaces for people (social challenge), and improve the technology of this field to reduce costs and environmental problems (economic and environmental challenge). One alternative to overcome these challenges is Building Information Modelling program (BIM) because according to several authors, this technology improves the performance of the sustainable buildings in all their lifecycle phases. The main objective of this paper is to explore and analyse the current advantages and disadvantages of the BIM implementation in the life-cycle of sustainable buildings considering the three pillars of sustainability as analysis parameters. The methodology established to achieve this objective is exploratory-descriptive with the literature review technique. The partial results illustrate that despite the BIM disadvantages and the lack of information about its social sustainability advantages, this software represents a significant opportunity to improve the three sustainable pillars of the sustainable buildings.

Keywords: building information modelling, building lifecycle analysis, sustainability, sustainable buildings

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Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

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In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

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Authors: Jung Lee

Abstract:

The last decade has witnessed more people than ever before using social media and broadening their social circles. Social media users connect not only with their friends but also with professional acquaintances, primarily coworkers, and clients; personal and professional social circles are mixed within the same social media platform. Considering the positive aspect of social media in facilitating communication and mutual understanding between individuals, we infer that social media interactions with co-workers could indeed benefit one’s professional life. However, given privacy issues, sharing all personal details with one’s co-workers is not necessarily the best practice. Should one connect with coworkers via social media? Will social media connections with coworkers eventually benefit one’s long-term career? Will the benefit differ across cultures? To answer, this study examines how social media can contribute to organizational communication by tracing the foundation of user motivation based on social capital theory, leader-member exchange (LMX) theory and expectancy theory of motivation. Although social media was originally designed for personal communication, users have shown intentions to extend social media use for professional communication, especially when the proper incentive is expected. To articulate the user motivation and the mechanism of the incentive expectation scheme, this study applies those three theories and identify six antecedents and three moderators of social media use motivation including social network flaunt, shared interest, perceived social inclusion. It also hypothesizes that the moderating effects of those constructs would significantly differ based on the relationship hierarchy among the workers. To validate, this study conducted a survey of 329 active social media users with acceptable levels of job experiences. The analysis result confirms the specific roles of the three moderators in social media adoption for organizational communication. The present study contributes to the literature by developing a theoretical modeling of ambivalent employee perceptions about establishing social media connections with co-workers. This framework shows not only how both positive and negative expectations of social media connections with co-workers are formed based on expectancy theory of motivation, but also how such expectations lead to behavioral intentions using career success model. It also enhances understanding of how various relationships among employees can be influenced through social media use and such usage can potentially affect both performance and careers. Finally, it shows how cultural factors induced by social media use can influence relations among the coworkers.

Keywords: the social network, workplace, social capital, motivation

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