Search results for: applications of big data

Authors: Mochamad Nuruz Zaman, Mangatur Rudolf Nababan, M. A. Djatmika

Abstract:

Both society and education areas teach to have good communication for building the interpersonal skills up. Everyone has the capacity to understand something new, either well comprehension or worst understanding. Worst understanding makes the language errors when the interactions are done by someone in the first meeting, and they do not know before it because of distance area. “The Space between Us” movie delivers the love-adventure story between Mars Boy and Earth Girl. They are so many missing conversations because of the different climate and environment. As the moviegoer also must be focused on the subtitle in order to enjoy well the movie. Furthermore, Indonesia subtitle and English conversation on the movie still have overlapping understanding in the translation. Translation hereby consists of source language -SL- (English conversation) and target language -TL- (Indonesia subtitle). These research gap above is formulated in research question by how the language errors happened in that movie and their effects on translation quality which is deepest analyzed by translation study toward discourse analysis approach. The research goal is to expand the language errors and their translation qualities in order to create a good atmosphere in movie media. The research is studied by embedded research in qualitative design. The research locations consist of setting, participant, and event as focused determined boundary. Sources of datum are “The Space between Us” movie and informant (translation quality rater). The sampling is criterion-based sampling (purposive sampling). Data collection techniques use content analysis and questioner. Data validation applies data source and method triangulation. Data analysis delivers domain, taxonomy, componential, and cultural theme analysis. Data findings on the language errors happened in the movie are referential, register, society, textual, receptive, expressive, individual, group, analogical, transfer, local, and global errors. Data discussions on their effects to translation quality are concentrated by translation techniques on their data findings; they are amplification, borrowing, description, discursive creation, established equivalent, generalization, literal, modulation, particularization, reduction, substitution, and transposition.

Keywords: discourse analysis, language errors, The Space between Us movie, translation techniques, translation quality instruments

Procedia PDF Downloads 212

Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

Abstract:

Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

Procedia PDF Downloads 205

Authors: Markus Feufel, Friederike Kendel, Caren Hilger, Selamawit Woldai

Abstract:

Since the corona pandemic, the use of video consultation has increased remarkably. For vulnerable groups such as oncological patients, the advantages seem obvious. But how does video consultation potentially change the doctor-patient relationship compared to face-to-face consultation? Which barriers may hinder the effective use of this consultation format in practice? We are presenting first results from a mixed-methods field study, funded by Federal Ministry of Health, which will provide the basis for a hands-on guide for both physicians and patients on how to improve the quality of video consultations. We use a quasi-experimental design to analyze qualitative and quantitative differences between face-to-face and video consultations based on video recordings of N = 64 actual counseling sessions (n = 32 for each consultation format). Data will be recorded from n = 32 gynecological and n = 32 urological cancer patients at two clinics. After the consultation, all patients will be asked to fill out a questionnaire about their consultation experience. For quantitative analyses, the counseling sessions will be systematically compared in terms of verbal and nonverbal communication patterns. Relative frequencies of eye contact and the information exchanged will be compared using 𝝌2 -tests. The validated questionnaire MAPPIN'Obsdyad will be used to assess the expression of shared decision-making parameters. In addition, semi-structured interviews will be conducted with n = 10 physicians and n = 10 patients experienced with video consultation, for which a qualitative content analysis will be conducted. We will elaborate the comprehensive methodological approach we used to compare video vs. face-to-face consultations and present first evidence on how video consultations change the doctor-patient interaction. We will also outline possible barriers of video consultations and best practices on how they may be overcome. Based on the results, we will present and discuss recommendations outlining best practices for how to prepare and conduct high-quality video consultations from the perspective of both physicians and patients.

Keywords: video consultation, patient-doctor-relationship, digital applications, technical barriers

Procedia PDF Downloads 137

Authors: Subhajit Das, Nirjhar Dhang

Abstract:

Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

Procedia PDF Downloads 210

Authors: Marriette Sakah, Samuel Gyamfi, Morkporkpor Delight Sedzro, Christoph Kuhn

Abstract:

Ghana is experiencing rapid economic development and its cities command an increasingly dominant role as centers of both production and consumption. Cities run on energy and are extremely vulnerable to energy scarcity, energy price escalations and health impacts of very poor air quality. The overriding concern in Ghana and other West African states is bridging the gap between energy demand and supply. Energy efficiency presents a cost-effective solution for supply challenges by enabling more coverage with current power supply levels and reducing the need for investment in additional generation capacity and grid infrastructure. In Ghana, major issues for energy policy formulation in residential applications include lack of disaggregated electrical energy consumption data and lack of thorough understanding with regards to socio-economic influences on energy efficiency investment. This study uses a bottom up approach to estimate baseline electricity end-use as well as the energy consumption of best available technologies to enable estimation of energy-efficiency resource in terms of relative reduction in total energy use for Tema city, Ghana. A ground survey was conducted to assess the probable consumer behavior in response to energy efficiency initiatives to enable estimation of the amount of savings that would occur in response to specific policy interventions with regards to funding and incentives provision targeted at households. Results show that 16% - 54% reduction in annual electricity consumption is reasonably achievable depending on the level of incentives provision. The saved energy could supply 10000 - 34000 additional households if the added households use only best available technology. Political support and consumer awareness are necessary to translate energy efficiency resources into real energy savings.

Keywords: achievable energy savings, energy efficiency, Ghana, household appliances

Procedia PDF Downloads 208

Authors: Shreya Asthana

Abstract:

Testers know that the feature they tested on stage is working perfectly in production only after release went live. Sometimes something breaks in production and testers get to know through the end user’s bug raised. The panic mode starts when your staging test results do not reflect current production behavior. And you started doubting your testing skills when finally the user reported a bug to you. Testers can deploy their confidence on release day by testing on production. Once you start doing testing in production, you will see test result accuracy because it will be running on real time data and execution will be a little faster as compared to staging one due to elimination of bad data. Feature flagging, canary releases, and data cleanup can help to achieve this technique of testing. By this paper it will be easier to understand the steps to achieve production testing before making your feature live, and to modify IT company’s testing procedure, so testers can provide the bug free experience to the end users. This study is beneficial because too many people think that testing should be done in staging but not in production and now this is high time to pull out people from their old mindset of testing into a new testing world. At the end of the day, it all just matters if the features are working in production or not.

Keywords: bug free production, new testing mindset, testing strategy, testing approach

Procedia PDF Downloads 67

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 558

Authors: Vibha Devi, Shabina Khanam

Abstract:

Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

Procedia PDF Downloads 136

Authors: Oluseun A. Sanuade, Sanlinn I. Kaka, Adesoji O. Akanji, Olukole A. Akinbiyi

Abstract:

Prospect evaluation of ‘the ‘ADE’ field was done using 3D seismic data and well log data. The field is located in the offshore Niger Delta where water depth ranges from 450 to 800 m. The objectives of this study are to explore deeper prospects and to ascertain the kind of traps that are favorable for the accumulation of hydrocarbon in the field. Six horizons with major and minor faults were identified and mapped in the field. Time structure maps of these horizons were generated and using the available check-shot data the maps were converted to top structure maps which were used to calculate the hydrocarbon volume. The results show that regional structural highs that are trending in northeast-southwest (NE-SW) characterized a large portion of the field. These highs were observed across all horizons revealing a regional post-depositional deformation. Three prospects were identified and evaluated to understand the different opportunities in the field. These include stratigraphic pinch out and bi-directional downlap. The results of this study show that the field has potentials for new opportunities that could be explored for further studies.

Keywords: hydrocarbon, play, prospect, stratigraphy

Procedia PDF Downloads 256

Authors: Sandesh Achar

Abstract:

Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

Procedia PDF Downloads 38

Authors: Diana Rymuszka, Konrad Terpiłowski, Lucyna Hołysz, Elena Goncharuk, Iryna Sulym

Abstract:

Superhydrophobic surfaces exhibit extremely high water repellency. The commonly accepted basic criterion for such surfaces is a water contact angle larger than 150°, low contact angle hysteresis and low sliding angle. These surfaces are of special interest, because properties such as anti-sticking, anti-contamination and self-cleaning are expected. These properties are attractive for many applications such as anti-sticking of snow for antennas and windows, anti-biofouling paints for boats, waterproof clothing, self-cleaning windshields for automobiles, dust-free coatings or metal refining. The various methods for the preparation of superhydrophobic surfaces since last two decades have been reported, such as phase separation, electrochemical deposition, template method, plasma method, chemical vapor deposition, wet chemical reaction, sol-gel processing, lithography and so on. The aim of the study was to investigate the influence of modified colloidal silica, used as a filler, on the hydrophobicity of the polymer film deposited on the glass support activated with plasma. On prepared surfaces water advancing (ӨA) and receding (ӨR) contact angles were measured and then their total apparent surface free energy was determined using the contact angle hysteresis approach (CAH). The structures of deposited films were observed with the help of an optical microscope. Topographies of selected films were also determined using an optical profilometer. It was found that plasma treatment influence glass surface wetting and energetic properties that is observed in higher adhesion between polymer/filler film and glass support. Using the colloidal silica particles as a filler for the polymer thin film deposited on the glass support, it is possible to produce strongly adhering layers of superhydrophobic properties. The best superhydrophobic properties were obtained for surfaces of the film glass/polimer + modified silica covered in 89 and 100%. The advancing contact angle measured on these surfaces amounts above 150° that leads to under 2 mJ/m2 value of the apparent surface free energy. Such films may have many practical applications, among others, as dust-free coatings or anticorrosion protection.

Keywords: contact angle, plasma, superhydrophobic, surface free energy

Procedia PDF Downloads 467

Authors: Dogaru-Ulieru Valentin, Sălișteanu Ioan Corneliu, Ardeleanu Mihăiță Nicolae, Broscăreanu Ștefan, Sălișteanu Bogdan, Mihai Mihail

Abstract:

The SiaMOTO system is a communications and data processing platform for vehicle traffic. The human factor is the most important factor in the generation of this data, as the driver is the one who dictates the trajectory of the vehicle. Like any trajectory, specific parameters refer to position, speed and acceleration. Constant knowledge of these parameters allows complex analyses. Roadways allow many vehicles to travel through their confined space, and the overlapping trajectories of several vehicles increase the likelihood of collision events, known as road accidents. Any such event has causes that lead to its occurrence, so the conditions for its occurrence are known. The human factor is predominant in deciding the trajectory parameters of the vehicle on the road, so monitoring it by knowing the events reported by the DiaMOTO device over time, will generate a guide to target any potentially high-risk driving behavior and reward those who control the driving phenomenon well. In this paper, we have focused on detailing the communication infrastructure of the DiaMOTO device with the traffic data collection server, the infrastructure through which the database that will be used for complex AI/DLM analysis is built. The central element of this description is the data string in CODEC-8 format sent by the DiaMOTO device to the SiaMOTO collection server database. The data presented are specific to a functional infrastructure implemented in an experimental model stage, by installing on a number of 50 vehicles DiaMOTO unique code devices, integrating ADAS and GPS functions, through which vehicle trajectories can be monitored 24 hours a day.

Keywords: DiaMOTO, Codec-8, ADAS, GPS, driver monitoring

Procedia PDF Downloads 72

Authors: Ferdi Sönmez, Başak Buluz

Abstract:

Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: knowledge management, agility requirements, agility, knowledge

Procedia PDF Downloads 256

Authors: Cláudia Moço, Maria Santos, Carlos Arsénio, Débora Mendes, Miguel Oliveira. José Paulo Da Silva

Abstract:

Construction industry generates large amounts of waste all over the world. About 450 million tons of construction and demolition wastes (C&DW) are produced annually in the European Union. C&DW are highly heterogeneous materials in size and composition, which imposes strong difficulties on their management. Directive n.º 2008/98/CE, of the European Parliament and of the Council of 6 November establishes that 70 % of the C&DW have to be recycled by 2020. To evaluate possible applications of these materials, a detailed physical, chemical and environmental characterization is necessary. Multi Triagem, Lda. is a company located in Algarve (Portugal) and was supported by the European Regional Development Fund (grant QREN 30307 Multivalor) to quantify and characterize the received C&DW, in order to evaluate their possible applications. This evaluation, performed in collaboration with the University of Algarve, involves a physical, chemical and environmental detailed characterization of the received C&DW. In this work we report on the amounts, trial procedures and properties of the C&DW received over a period of fifteen month. In this period the company received C&DW coming from 393 different origins. The total amount was 32.458 tons, mostly mixtures containing concrete, masonry/mortar and soil/rock. Most of C&DW came from demodulation constructions and diggings. The organic/inert component, namely metal, glass, wood and plastics, were screened first and account for about 3 % of the received materials. The remaining materials were screened and grouped according to their origin and contents, the latter evaluated by visual inspection. Twenty five samples were prepared and submitted to a detailed physical, chemical and environmental analysis. The C&DW aggregates show lower quality properties than natural aggregates for concrete preparation and unbound layers of road pavements. However, chemical analyzes indicated that most samples are environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds is needed in order to perform a proper screening of the C&DW. C&DW aggregates provide a good alternative to natural aggregates.

Keywords: construction and demolition wastes, waste classification, waste composition, waste screening

Procedia PDF Downloads 345

Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman

Abstract:

This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), in fit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained shows that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.

Keywords: competency assessment, reliability, validity, item analysis

Procedia PDF Downloads 440

Authors: Yousaf Tariq

Abstract:

There are many reasons which are involved in electronic equipment failure i.e. temperature, humidity, dust, smoke etc. Corrosive gases are also one of the factor which may involve in failure of equipment. Sensitivity of electronic equipment increased when “lead-free” regulation enforced on manufacturers. In data center, equipment like hard disk, servers, printed circuit boards etc. have been exposed to gaseous contamination due to increase in sensitivity. There is a worldwide standard to protect electronic industrial electronic from corrosive gases. It is well known as “ANSI/ISA S71.04 – 1985 - Environmental Conditions for Control Systems: Airborne Contaminants. ASHRAE Technical Committee (TC) 9.9 members also recommended ISA standard in their whitepaper on Gaseous and Particulate Contamination Guideline for data centers. TC 9.9 members represented some of the major IT equipment manufacturers e.g. IBM, HP, Cisco etc. As per standard practices, first step is to monitor air quality in data center. If contamination level shows more than G1, it means that gas-phase air filtration is required other than dust/smoke air filtration. It is important that outside fresh air entering in data center should have pressurization/re-circulated process in order to absorb corrosive gases and to maintain level within specified limit. It is also important that air quality monitoring should be conducted once in a year. Temperature and humidity should also be monitored as per standard practices to maintain level within specified limit.

Keywords: corrosive gases, corrosion, electronic equipment failure, ASHRAE, hard disk

Procedia PDF Downloads 324

Authors: Hyun-Woo Cho

Abstract:

It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

Procedia PDF Downloads 238

Authors: A. Sardi, J. Zbitou, A. Errkik, L. El Abdellaoui, A. Tajmouati, M. Latrach

Abstract:

This paper presents analysis and design of a wideband Wilkinson power divider for wireless applications. The design is accomplished by transforming the lengths and impedances of the quarter wavelength sections of the conventional Wilkinson power divider into U-shaped sections. The designed power divider is simulated by using ADS Agilent technologies and CST microwave studio software. It is shown that the proposed power divider has simple topology and good performances in terms of insertion loss, port matching and isolation at all operating frequencies (1.8 GHz, 2.45 GHz and 3.55 GHz).

Keywords: ADS agilent technologies, CST microwave studio, microstrip, wideband, wilkinson power divider

Procedia PDF Downloads 361

Authors: Vinod Kumar Jaysaval, Prateek Agarwal

Abstract:

Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

Procedia PDF Downloads 464

Authors: M. Gil, R. Montalvo

Abstract:

Business Intelligence (BI) has become a major source of competitive advantages for firms around the world. BI has been defined as the process of data visualization and reporting for understanding what happened and what is happening. Moreover, BI has been studied for its predictive capabilities in the context of trade and financial transactions. The current literature has identified that BI permits managers to identify market trends, understand customer relations, and predict demand for their products and services. This last capability of BI has been of special concern to academics. Specifically, due to its power to build predictive models adaptable to specific time horizons and geographical regions. However, the current literature of BI focuses on predicting specific markets and industries because the impact of such predictive models was relevant to specific industries or organizations. Currently, the existing literature has not developed a predictive model of BI that takes into consideration the whole economy of a geographical area. This paper seeks to create a predictive model of BI that would show the bigger picture of a geographical area. This paper uses a data set from the Secretary of Economic Development of the state of Jalisco, Mexico. Such data set includes data from all the commercial transactions that occurred in the state in the last years. By analyzing such data set, it will be possible to generate a BI model that predicts supply and demand from specific industries around the state of Jalisco. This research has at least three contributions. Firstly, a methodological contribution to the BI literature by generating the predictive supply and demand model. Secondly, a theoretical contribution to BI current understanding. The model presented in this paper incorporates the whole picture of the economic field instead of focusing on a specific industry. Lastly, a practical contribution might be relevant to local governments that seek to improve their economic performance by implementing BI in their policy planning.

Keywords: business intelligence, predictive model, supply and demand, Mexico

Procedia PDF Downloads 120

Authors: Muhammad Rana, Quazi Mamun, Rafiqul Islam

Abstract:

In the Internet of Things (IoT), many devices are connected and accumulate a sheer amount of data. These Internet-driven raw data need to be transferred securely to the end-users via dependable networks. Consequently, the challenges of IoT security in various IoT domains are paramount. Cryptography is being applied to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint properties of IoT devices, the conventional cipher may not be suitable in all IoT networks. This paper designs a robust and effective lightweight cipher to secure the IoT environment and meet the resource-constrained nature of IoT devices. We also propose a symmetric and block-cipher based lightweight cryptographic algorithm. The proposed algorithm increases the complexity of the block cipher, maintaining the lowest computational requirements possible. The proposed algorithm efficiently constructs the key register updating technique, reduces the number of encryption rounds, and adds a new layer between the encryption and decryption processes.

Keywords: internet of things, cryptography block cipher, S-box, key management, security, network

Procedia PDF Downloads 104

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 163

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

Abstract:

Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

Procedia PDF Downloads 113

Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

Abstract:

In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

Procedia PDF Downloads 235

Authors: A. Fakhri Makram, Marwa S. Alwazni, Al-Douri Yarub, Evan T. Salim, Hashim Uda, Chin C. Woei

Abstract:

Lithium niobate (LiNbO₃) nanostructures are prepared on quartz substrate by the sol-gel method. They have been deposited with different molarity concentration and annealed at 500°C. These samples are characterized and analyzed by X-ray diffraction (XRD), Scanning Electron Microscope (SEM) and Atomic Force Microscopy (AFM). The measured results showed an importance increasing in molarity concentrations that indicate the structure starts to become crystal, regular, homogeneous, well crystal distributed, which made it more suitable for optical waveguide application.

Keywords: lithium niobate, morphological properties, thin film, pechini method, XRD

Procedia PDF Downloads 440

Authors: Sheo K. Mishra, Rajneesh K. Srivastava, R. K. Shukla

Abstract:

In the present work, we report on the optical properties including UV-vis absorption and photoluminescence (PL) of ZnO nanostructures synthesized by sol-gel method. Structural and morphological investigations have been performed by X-ray diffraction method (XRD) and scanning electron microscopy (SEM). The XRD result confirms the formation of hexagonal wurtzite phase of ZnO nanostructures. The presence of various diffraction peaks suggests polycrystalline nature. The XRD pattern exhibits no additional peak due to by-products such as Zn(OH)2. The average crystallite size of prepared ZnO sample corresponding to the maximum intensity peaks is to be ~38.22 nm. The SEM micrograph shows different nanostructures of pure ZnO. Photoluminescence (PL) spectrum shows several emission peaks around 353 nm, 382 nm, 419 nm, 441 nm, 483 nm and 522 nm. The obtained results suggest that the prepared phosphors are quite suitable for optoelectronic applications.

Keywords: ZnO, sol-gel, XRD, PL

Procedia PDF Downloads 394

Authors: Sepdiana W. Rahmawati, Santi A. P. Anggraini

Abstract:

The world of education has made progress with the various new technologies with help of computer. No exception physics education, especially virtual physics practical work. By doing practical work, memory of physics concept will be more advantageous for student and they will understand the essence of actual physics, not only spiked formula. With help of computers, created a variety of applications that can be used by students to perform virtual practical work and students will start thinking systematically to be able find its own concepts and understand the application of physics.

Keywords: essence of physics, formation concept, physics concept, virtual practical work

Procedia PDF Downloads 397

Authors: Sara Alshehri, Bayan Alenzi, Atheer Alshehri, Samia Chelloug, Zainab Almry, Hussah Albugmai

Abstract:

This paper concerns body area networks sensor that collect signals around a human body. The black hole attacks are the main security challenging problem because the data traffic can be dropped at any node. The focus of our proposed solution is to efficiently route data packets while detecting black hole nodes.

Keywords: body sensor networks, security, black hole, routing, broadcasting, OMNeT++

Procedia PDF Downloads 636

Authors: Vasant Reddy, Shivani A. Singh, Pravin S. More

Abstract:

In the present investigation, we demonstrated the fabrication of few-layers of graphene sheets with alkali metal i.e. Rb-G using chemical route method. The obtained materials were characterized by means of chemical, structural and electrical techniques, using the ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and 4 points probe, respectively. The XRD studies were carried out to understand the phase of the samples where we found a sharp peak of Rb-G at 26.470. UV-Spectroscopy of Graphene and Rb-modified graphene samples shows the absorption peaks at ~248 nm and ~318 nm respectively. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas.

Keywords: chemical route, graphene, gas sensing, UV-spectroscopy

Procedia PDF Downloads 261

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

Abstract:

In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 213