Search results for: open data
25272 Methodology of the Turkey’s National Geographic Information System Integration Project
Authors: Buse A. Ataç, Doğan K. Cenan, Arda Çetinkaya, Naz D. Şahin, Köksal Sanlı, Zeynep Koç, Akın Kısa
Abstract:
With its spatial data reliability, interpretation and questioning capabilities, Geographical Information Systems make significant contributions to scientists, planners and practitioners. Geographic information systems have received great attention in today's digital world, growing rapidly, and increasing the efficiency of use. Access to and use of current and accurate geographical data, which are the most important components of the Geographical Information System, has become a necessity rather than a need for sustainable and economic development. This project aims to enable sharing of data collected by public institutions and organizations on a web-based platform. Within the scope of the project, INSPIRE (Infrastructure for Spatial Information in the European Community) data specifications are considered as a road-map. In this context, Turkey's National Geographic Information System (TUCBS) Integration Project supports sharing spatial data within 61 pilot public institutions as complied with defined national standards. In this paper, which is prepared by the project team members in the TUCBS Integration Project, the technical process with a detailed methodology is explained. In this context, the main technical processes of the Project consist of Geographic Data Analysis, Geographic Data Harmonization (Standardization), Web Service Creation (WMS, WFS) and Metadata Creation-Publication. In this paper, the integration process carried out to provide the data produced by 61 institutions to be shared from the National Geographic Data Portal (GEOPORTAL), have been trying to be conveyed with a detailed methodology.Keywords: data specification, geoportal, GIS, INSPIRE, Turkish National Geographic Information System, TUCBS, Turkey's national geographic information system
Procedia PDF Downloads 14425271 Secure Content Centric Network
Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris
Abstract:
Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer
Procedia PDF Downloads 64425270 Fuel Inventory/ Depletion Analysis for a Thorium-Uranium Dioxide (Th-U) O2 Pin Cell Benchmark Using Monte Carlo and Deterministic Codes with New Version VIII.0 of the Evaluated Nuclear Data File (ENDF/B) Nuclear Data Library
Authors: Jamal Al-Zain, O. El Hajjaji, T. El Bardouni
Abstract:
A (Th-U) O2 fuel pin benchmark made up of 25 w/o U and 75 w/o Th was used. In order to analyze the depletion and inventory of the fuel for the pressurized water reactor pin-cell model. The new version VIII.0 of the ENDF/B nuclear data library was used to create a data set in ACE format at various temperatures and process the data using the MAKXSF6.2 and NJOY2016 programs to process the data at the various temperatures in order to conduct this study and analyze cross-section data. The infinite multiplication factor, the concentrations and activities of the main fission products, the actinide radionuclides accumulated in the pin cell, and the total radioactivity were all estimated and compared in this study using the Monte Carlo N-Particle 6 (MCNP6.2) and DRAGON5 programs. Additionally, the behavior of the Pressurized Water Reactor (PWR) thorium pin cell that is dependent on burn-up (BU) was validated and compared with the reference data obtained using the Massachusetts Institute of Technology (MIT-MOCUP), Idaho National Engineering and Environmental Laboratory (INEEL-MOCUP), and CASMO-4 codes. The results of this study indicate that all of the codes examined have good agreements.Keywords: PWR thorium pin cell, ENDF/B-VIII.0, MAKXSF6.2, NJOY2016, MCNP6.2, DRAGON5, fuel burn-up.
Procedia PDF Downloads 10325269 Natural Language News Generation from Big Data
Authors: Bastian Haarmann, Likas Sikorski
Abstract:
In this paper, we introduce an NLG application for the automatic creation of ready-to-publish texts from big data. The fully automatic generated stories have a high resemblance to the style in which the human writer would draw up a news story. Topics may include soccer games, stock exchange market reports, weather forecasts and many more. The generation of the texts runs according to the human language production. Each generated text is unique. Ready-to-publish stories written by a computer application can help humans to quickly grasp the outcomes of big data analyses, save time-consuming pre-formulations for journalists and cater to rather small audiences by offering stories that would otherwise not exist.Keywords: big data, natural language generation, publishing, robotic journalism
Procedia PDF Downloads 43125268 Performance Evaluation of the Classic seq2seq Model versus a Proposed Semi-supervised Long Short-Term Memory Autoencoder for Time Series Data Forecasting
Authors: Aswathi Thrivikraman, S. Advaith
Abstract:
The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.Keywords: LSTM, autoencoder, forecasting, seq2seq model
Procedia PDF Downloads 15625267 A Survey on Various Technique of Modified TORA over MANET
Authors: Shreyansh Adesara, Sneha Pandiya
Abstract:
The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.Keywords: IMEP, mobile ad-hoc network, protocol, TORA
Procedia PDF Downloads 44225266 Assessment of the Effect of Farmer-Herder Conflict on the Livelihood of Rural Households in Bogoro Local Government Area of Bauchi State, Nigeria
Authors: Luka Jumma Gizaki
Abstract:
The study assessed the effect of farmer-herder conflict on the livelihood of rural households in Bogoro L.G.A., Bauchi State, Nigeria. Multistage sampling procedures were used to randomly select 66 crop farmers in the study area. Data were collected by means of a structured questionnaire. The result was analyzed using descriptive and inferential statistics. Results showed that the majority of the respondents were males with a mean age of 39 years and a farming experience of 16 years. About 95% of the respondents had formal education, with a mean household size of 8 persons per household. Farmer-herder conflicts were found to be caused by grazing on growing crops, wrong approach by farmers in raising complaints and harassment of herdsmen, absence of grazing route and poisoning of uncultivated lands. Constraints to resolving conflict were found to include personal interest, lack of government will, ethnicity and religious difference and open grazing ranking first, second and third, among others. Six factors connected to farmer-herder conflict were found to significantly affect the livelihood of rural households. These were the value of crops destroyed, the number of livestock lost, and the cost of treatment of wounds sustained from the conflict. The value of crops and the size of farmland abandoned in fear were significant, and the cost of seeking redress was significant at P≤0.01. It was concluded that farmer-herder conflict impacts negatively not only crops and animals but also affects the lives of farmers and herders as well as their economy. It is recommended that proper methods be adopted to avoid its occurrence, and when it occurs, the erring party should be appropriately punished.Keywords: farmer, herder, conflict, effect, coping
Procedia PDF Downloads 4625265 The Analysis of Emergency Shutdown Valves Torque Data in Terms of Its Use as a Health Indicator for System Prognostics
Authors: Ewa M. Laskowska, Jorn Vatn
Abstract:
Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL
Procedia PDF Downloads 9125264 An Open Trial of Mobile-Assisted Cognitive Behavioral Therapy for Negative Symptoms in Schizophrenia: Pupillometry Predictors of Outcome
Authors: Eric Granholm, Christophe Delay, Jason Holden, Peter Link
Abstract:
Negative symptoms are an important unmet treatment needed for schizophrenia. We conducted an open trial of a novel blended intervention called mobile-assisted cognitive behavior therapy for negative symptoms (mCBTn). mCBTn is a weekly group therapy intervention combining in-person and smartphone-based CBT (CBT2go app) to improve experiential negative symptoms in people with schizophrenia. Both the therapy group and CBT2go app included recovery goal setting, thought challenging, scheduling of pleasurable activities and social interactions, and pleasure savoring interventions to modify defeatist attitudes, a target mechanism associated with negative symptoms, and improve experiential negative symptoms. We tested whether participants with schizophrenia or schizoaffective disorder (N=31) who met prospective criteria for persistent negative symptoms showed improvement in experiential negative symptoms. Retention was excellent (87% at 18 weeks) and severity of defeatist attitudes and motivation and pleasure negative symptoms declined significantly in mCBTn with large effect sizes. We also tested whether pupillary responses, a measure of cognitive effort, predicted improvement in negative symptoms mCBTn. Pupillary responses were recorded at baseline using a Tobii pupillometer during the digit span task with 3-, 6- and 9-digit spans. Mixed models showed that greater dilation during the task at baseline significantly predicted a greater reduction in experiential negative symptoms. Pupillary responses may provide a much-needed prognostic biomarker of which patients are most likely to benefit from CBT. Greater pupil dilation during a cognitive task predicted greater improvement in experiential negative symptoms. Pupil dilation has been linked to motivation and engagement of executive control, so these factors may contribute to benefits in interventions that train cognitive skills to manage negative thoughts and emotions. The findings suggest mCBTn is a feasible and effective treatment for experiential negative symptoms and justify a larger randomized controlled clinical trial. The findings also provide support for the defeatist attitude model of experiential negative symptoms and suggest that mobile-assisted interventions like mCBTn can strengthen and shorten intensive psychosocial interventions for schizophrenia.Keywords: cognitive-behavioral therapy, mobile interventions, negative symptoms, pupillometry schizophrenia
Procedia PDF Downloads 18025263 Person-Centered Thinking as a Fundamental Approach to Improve Quality of Life
Authors: Christiane H. Kellner, Sarah Reker
Abstract:
The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centred design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like centre in Schönbrunn - a large residential complex and service provider for persons with disabilities in the outskirts of Munich - will be remodelled to open up the community to all people as well as transform social space. This strategy should lead to more equal opportunities and open the way for a much more diverse community. The research project “Index for participation development and quality of life for persons with disabilities” (TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at the Franziskuswerk Schönbrunn supports this transformation process called “Vision 2030”. In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees using person-centred planning). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one sub-project more in-depth, namely “The Person-Centred Think Tank” [Arbeitskreis Personenzentriertes Denken; PZD]. In the context of person-centred thinking (PCT), persons with disabilities are encouraged to (re)gain or retain control of their lives through the development of new choice options and the validation of individual lifestyles. PCT should thus foster and support both participation and quality of life. The project aims to establish PCT as a fundamental approach for both employees and persons with disabilities in the institution through in-house training for the staff and, subsequently, training for users. Hence, for the academic support and supervision team, the questions arising from this venture can be summed up as follows: (1) has PCT already gained a foothold at the Franziskuswerk Schönbrunn? And (2) how does it affect the interaction with persons with disabilities and how does it influence the latter’s everyday life? According to the holistic approach described above, the target groups for this study are both the staff and the users of the institution. Initially, we planned to implement the group discussion method for both target-groups. However, in the course of a pretest with persons with intellectual disabilities, it became clear that this type of interview, with hardly any external structuring, provided only limited feedback. In contrast, when the discussions were moderated, there was more interaction and dialogue between the interlocutors. Therefore, for this target-group, we introduced structured group interviews. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. We analysed and evaluated the group interviews and discussions with the help of qualitative content analysis according to Mayring in order to obtain information about users’ quality of life. We sorted out the statements relating to quality of life obtained during the group interviews into three dimensions: subjective wellbeing, self-determination and participation. Nevertheless, the majority of statements were related to subjective wellbeing and self-determination. Thus, especially the limited feedback on participation clearly demonstrates that the lives of most users do not take place beyond the confines of the institution. A number of statements highlighted the fact that PCT is anchored in the everyday interactions within the groups. However, the implementation and fostering of PCT on a broader level could not be detected and thus remain further aims of the project. The additional interviews we have planned should validate the results obtained until now and open up new perspectives.Keywords: person-centered thinking, research with persons with disabilities, residential complex and service provider, participation, self-determination.
Procedia PDF Downloads 32325262 Case study of Environmental Impact Assessment of Quarrying Activities
Authors: Hocine Benabid, M. F. Ghorab
Abstract:
The exploration of open pit mines and quarries has always been important resources that provide many valuable needed minerals but very often accompanied by large amounts of dust rejected into the air and also many other negative environmental impacts. The dust remains suspended in the atmosphere before being deposited on soils, on forest trees, on plants and also on water, causing at long term allergic and respiratory diseases for residents living in the vicinity or even far away from the mines and quarries. As a consequence of this activity, dust can also disturb the photosynthetic activity of plants and affect water quality. It is for these reasons and because of the intensification of these activities that our motivations have become larger to deal with this kind of topic, which is becoming nowadays an environmental and health concern for almost every country in the world.Keywords: mines, dust, environmental impacts, environmental concern
Procedia PDF Downloads 38325261 National Image in the Age of Mass Self-Communication: An Analysis of Internet Users' Perception of Portugal
Authors: L. Godinho, N. Teixeira
Abstract:
Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.Keywords: national image, internet, self-communication, perception
Procedia PDF Downloads 25625260 Block Mining: Block Chain Enabled Process Mining Database
Authors: James Newman
Abstract:
Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.Keywords: blockchain, process mining, memory optimization, protocol
Procedia PDF Downloads 10325259 Efficiently Silicon Metasurfaces at Visible Light
Authors: Juntao Li
Abstract:
The metasurfaces for beam deflecting with gradient silicon posts in the square lattices were fabricated on the thin film crystal silicon with quartz substrate. By using the crystals silicon with high refractive index and high transmission to control the phase over 2π coverage, we demonstrated the polarization independent beam deflecting at wavelength of 532nm with 45% transmission in experiment and 70% in simulation into the desired angle. This simulation efficiency is almost close to the TiO2 metasurfaces but has higher refractive index and lower aspect ratio to reduce fabrication complexity. The result can extend the application of silicon metalsurfaces from 700 nm to 500 nm hence open a new way to use metasurfaces efficiently in visible light regime.Keywords: metasurfaces, crystal silicon, light deflection, visible light
Procedia PDF Downloads 28325258 Vulnerability of Groundwater to Pollution in Akwa Ibom State, Southern Nigeria, using the DRASTIC Model and Geographic Information System (GIS)
Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze
Abstract:
Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.Keywords: groundwater, vulnerability, DRASTIC model, pollution
Procedia PDF Downloads 20725257 Retrospective Study on the Impacts of Age, Gender, Economic Status, Education Level and Drug Availability in Public Hospital on Seeking Care of Dermatological Condition in Rwanda
Authors: Uwizera Egide
Abstract:
Introduction: Dermatological conditions are one of the most burdensome diseases in our health system. Global studies suggest that around 1 in 3 people gets a skin disease at a certain point in their life, though this does not necessarily guarantee the urge to consult. For a high-ranking disease, it is surprising how there is not enough data to support its effect on the economy and the general health system impact. It is for that reason that this study’s aim is to identify the burden of dermatological conditions in Rwanda so as to have a general picture of what our population is going through in regards to dermatological conditions. Methods: We used a cross sectional retrospective study. Data were obtained from patient’s information recorded in an open clinic at CHUB in a period of six months from July to December of the year 2021. Results: The study had a total of 4600 patients who attended dermatology service in a period of six months from July to December of the year 2021. We found a list of 102 dermatological diseases that presented at variable rates. The most prevalent disease was atopic dermatitis, at a rate of 23%. About 90% of presented conditions had only one choice of treatment from the hospital pharmacy. Most patients who presented were between 18-35 years old and with a predominance of the female gender; the level of education was either secondary or University Degree in our study, 65.4% of patients who presented were female; the majority, around 45% were between 18-35 years old, mostly being single 56%. The majority came from Southern province as it is the location of the hospital. The insurance mostly used was community-based health insurance with 63.8%, followed by RSSB with 18.5%, MS/UR, and other private insurances. The frequency of group drugs prescribed among all dermatological medications, steroids were the most commonly given medications at a rate of 39%, followed by emollients, antibiotics, and antifungal. The drugs prescribed were mostly available in the pharmacy of CHUB, with 60% and 40% being found in pharmacies outside the hospital. Conclusion: Dermatological conditions are prevalent in all age groups and distributed through all socioeconomic classes. About 9.2% of patient who consulted CHUB in 2021 presented one Dermatological condition of which 40 % of prescribed medications is never found in Hospital urging a need to buy medication in private pharmacies with more expenses and a risk of not complying on prescribed medication if in case they can’t afford paying them outside the CHUB. This finding urges a need to avail all essential dermatological drugs in hospital pharmacies to allow our patients to get them for the proper compliance of prescribed drugs in the management of skin diseases.Keywords: atopic dermatitis, CHUB (centre hopitalier univerisitaire de butare), dermatological condition, fungal infections
Procedia PDF Downloads 11725256 A Survey of Crowdsourcing Technology
Authors: Qianjia Cheng, Hongquan Jiang
Abstract:
Crowdsourcing solves the problems that computers can't handle by integrating computers and the Internet. Its extensive knowledge sources, high efficiency and high quality, make crowdsourcing attract wide attention in industry and academia in recent years. The development of online crowdsourcing platforms such as Clickworker and Amazon Mechanical Turk(Mturk) tend to mature gradually. This paper sorts out the concept of crowdsourcing, sorts out the workflow of competitive crowdsourcing, summarizes the related technologies of crowdsourcing based on the workflow, quality control, cost control and delay control, introduces the typical crowdsourcing platform. Finally, we highlight some open problems of the current crowdsourcing and present some future research direction in this area.Keywords: application, crowdsourcing, crowdsourcing platform, system architecture
Procedia PDF Downloads 7025255 Design of Cloud Service Brokerage System Intermediating Integrated Services in Multiple Cloud Environment
Authors: Dongjae Kang, Sokho Son, Jinmee Kim
Abstract:
Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service
Procedia PDF Downloads 48825254 Commercial Automobile Insurance: A Practical Approach of the Generalized Additive Model
Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou
Abstract:
The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.Keywords: insurance, data science, modeling, monitoring, regulation, processes
Procedia PDF Downloads 7625253 Comparative Study of Scheduling Algorithms for LTE Networks
Authors: Samia Dardouri, Ridha Bouallegue
Abstract:
Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing
Procedia PDF Downloads 38325252 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)
Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean
Abstract:
The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.Keywords: pan evaporation, intelligent methods, shahroud, mayamey
Procedia PDF Downloads 7425251 Navigating a Changing Landscape: Opportunities for Research Managers
Authors: Samba Lamine Cisse, Cheick Oumar Tangara, Seynabou Sissoko, Mahamadou Diakite, Seydou Doumbia
Abstract:
Introduction: Over the past two decades, the world has been constantly changing, with new trends in project management. These trends are transforming the methods and priorities of research project management. They include the rise of digital technologies, multidisciplinary, open science, and the pressure for high-impact results. Managers, therefore, find themselves at a crossroads between the challenges and opportunities offered by these new trends. This paper aims to identify the challenges and opportunities they face while proposing strategies for effectively navigating this dynamic context. Methodology: This is a qualitative study based on an analysis of the challenges and opportunities facing the University Clinical Research Center in terms of new technologies and project management methods. This blended approach provides an overview of emerging trends and practices. Results: This article shows how research managers can turn new research trends in their favor and how they can adapt to the changes they face to optimize the productivity of research teams while ensuring the quality and ethics of the work. It also explores the importance of developing skills in data management, international collaboration, and innovation management. Finally, it proposes strategies for responding effectively to the challenges posed by these new trends while strengthening the position of research managers as essential facilitators of scientific progress. Conclusion: Navigating this changing landscape requires research managers to be highly flexible and able to anticipate the realities of their institution. By adopting modern project management methodologies and cultivating a culture of innovation, they can turn challenges into opportunities and propel research toward new horizons. This paper provides a strategic framework for overcoming current obstacles and capitalizing on future developments in research.Keywords: new trends, research management, opportunities, challenges
Procedia PDF Downloads 1325250 Generating Insights from Data Using a Hybrid Approach
Authors: Allmin Susaiyah, Aki Härmä, Milan Petković
Abstract:
Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.Keywords: data mining, insight mining, natural language generation, pre-trained language models
Procedia PDF Downloads 12025249 Usability Evaluation of Rice Doctor as a Diagnostic Tool for Agricultural Extension Workers in Selected Areas in the Philippines
Authors: Jerome Cayton Barradas, Rowely Parico, Lauro Atienza, Poornima Shankar
Abstract:
The effective agricultural extension is essential in facilitating improvements in various agricultural areas. One way of doing this is through Information and communication technologies (ICTs) like Rice Doctor (RD), an app-based diagnostic tool that provides accurate and timely diagnosis and management recommendations for more than 80 crop problems. This study aims to evaluate the RD usability by determining the effectiveness, efficiency, and user satisfaction of RD in making an accurate and timely diagnosis. It also aims to identify other factors that affect RD usability. This will be done by comparing RD with two other diagnostic methods: visual identification-based diagnosis and reference-guided diagnosis. The study was implemented in three rice-producing areas and has involved 96 extension workers. Respondents accomplished a self-administered survey and participated in group discussions. Data collected was then subjected to qualitative and quantitative analysis. Most of the respondents were satisfied with RD and believed that references are needed in assuring the accuracy of diagnosis. The majority found it efficient and easy to use. Some found it confusing and complicated, but this is because of their unfamiliarity with RD. Most users were also able to achieve accurate diagnosis proving effectiveness. Lastly, although users have reservations, they are satisfied and open to using RD. The study also found out the importance of visual identification skills in using RD and the need for capacity development and improvement of access to RD devices. From these results, the following are recommended to improve RD usability: review and upgrade diagnostic keys, expand further RD content, initiate capacity development for AEWs, and prepare and implement an RD communication plan.Keywords: agricultural extension, crop protection, information and communication technologies, rice doctor
Procedia PDF Downloads 25425248 Review of K0-Factors and Related Nuclear Data of the Selected Radionuclides for Use in K0-NAA
Authors: Manh-Dung Ho, Van-Giap Pham, Van-Doanh Ho, Quang-Thien Tran, Tuan-Anh Tran
Abstract:
The k0-factors and related nuclear data, i.e. the Q0-factors and effective resonance energies (Ēr) of the selected radionuclides which are used in the k0-based neutron activation analysis (k0-NAA), were critically reviewed to be integrated in the “k0-DALAT” software. The k0- and Q0-factors of some short-lived radionuclides: 46mSc, 110Ag, 116m2In, 165mDy, and 183mW, were experimentally determined at the Dalat research reactor. The other radionuclides selected are: 20F, 36S, 49Ca, 60mCo, 60Co, 75Se, 77mSe, 86mRb, 115Cd, 115mIn, 131Ba, 134mCs, 134Cs, 153Gd, 153Sm, 159Gd, 170Tm, 177mYb, 192Ir, 197mHg, 239U and 239Np. The reviewed data as compared with the literature data were biased within 5.6-7.3% in which the experimental re-determined factors were within 6.1 and 7.3%. The NIST standard reference materials: Oyster Tissue (1566b), Montana II Soil (2711a) and Coal Fly Ash (1633b) were used to validate the new reviewed data showing that the new data gave an improved k0-NAA using the “k0-DALAT” software with a factor of 4.5-6.8% for the investigated radionuclides.Keywords: neutron activation analysis, k0-based method, k0 factor, Q0 factor, effective resonance energy
Procedia PDF Downloads 12625247 Optimizing Electric Vehicle Charging with Charging Data Analytics
Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat
Abstract:
Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.Keywords: charging data, electric vehicles, machine learning, waiting times
Procedia PDF Downloads 19625246 Finding Data Envelopment Analysis Targets Using Multi-Objective Programming in DEA-R with Stochastic Data
Authors: R. Shamsi, F. Sharifi
Abstract:
In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis
Procedia PDF Downloads 10625245 The Hidden Role of Interest Rate Risks in Carry Trades
Authors: Jingwen Shi, Qi Wu
Abstract:
We study the role played interest rate risk in carry trade return in order to understand the forward premium puzzle. In this study, our goal is to investigate to what extent carry trade return is indeed due to compensation for risk taking and, more important, to reveal the nature of these risks. Using option data not only on exchange rates but also on interest rate swaps (swaptions), our first finding is that, besides the consensus currency risks, interest rate risks also contribute a non-negligible portion to the carry trade return. What strikes us is our second finding. We find that large downside risks of future exchange rate movements are, in fact, priced significantly in option market on interest rates. The role played by interest rate risk differs structurally from the currency risk. There is a unique premium associated with interest rate risk, though seemingly small in size, which compensates the tail risks, the left tail to be precise. On the technical front, our study relies on accurately retrieving implied distributions from currency options and interest rate swaptions simultaneously, especially the tail components of the two. For this purpose, our major modeling work is to build a new international asset pricing model where we use an orthogonal setup for pricing kernels and specify non-Gaussian dynamics in order to capture three sets of option skew accurately and consistently across currency options and interest rate swaptions, domestic and foreign, within one model. Our results open a door for studying forward premium anomaly through implied information from interest rate derivative market.Keywords: carry trade, forward premium anomaly, FX option, interest rate swaption, implied volatility skew, uncovered interest rate parity
Procedia PDF Downloads 44525244 Integrated Model for Enhancing Data Security Processing Time in Cloud Computing
Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali
Abstract:
Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish
Procedia PDF Downloads 35925243 Approximation to the Hardy Operator on Topological Measure Spaces
Authors: Kairat T. Mynbaev, Elena N. Lomakina
Abstract:
We consider a Hardy-type operator generated by a family of open subsets of a Hausdorff topological space. The family is indexed with non-negative real numbers and is totally ordered. For this operator, we obtain two-sided bounds of its norm, a compactness criterion, and bounds for its approximation numbers. Previously, bounds for its approximation numbers have been established only in the one-dimensional case, while we do not impose any restrictions on the dimension of the Hausdorff space. The bounds for the norm and conditions for compactness earlier have been found using different methods by G. Sinnamon and K. Mynbaev. Our approach is different in that we use domain partitions for all problems under consideration.Keywords: approximation numbers, boundedness and compactness, multidimensional Hardy operator, Hausdorff topological space
Procedia PDF Downloads 105