Search results for: supervisory control and data acquisition (scada)

Authors: Tie-Qing Zhang, Seunghun Jung, Young-Bae Kim

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This research is devoted to developing a membrane reactor to flexibly meet the hydrogen demand of onboard fuel cells, which is an important part of green energy development. Among many renewable chemical products, dimethyl ether (DME) has the advantages of low reaction temperature (400 °C in this study), high hydrogen atom content, low toxicity, and easy preparation. Autothermal reforming, on the other hand, has a high hydrogen recovery rate and exhibits thermal neutrality during the reaction process, so the additional heat source in the hydrogen production process can be omitted. Therefore, the DME auto thermal reforming process was adopted in this study. To control the temperature of the reaction catalyst bed and hydrogen production rate, a Model Predictive Control (MPC) scheme was designed. Taking the above two variables as the control objectives, stable operation of the reformer can be achieved by controlling the flow rates of DME, steam, and high-purity air in real-time. To prevent catalyst poisoning in the fuel cell, the hydrogen needs to be purified to reduce the carbon monoxide content to below 50 ppm. Therefore, a Pd-Ag hydrogen semi-permeable membrane with a thickness of 3-5 μm was inserted into the auto thermal reactor, and the permeation efficiency of hydrogen was improved by steam purging on the permeation side. Finally, hydrogen with a purity of 99.99 was obtained.

Keywords: hydrogen production, auto thermal reforming, membrane, fuel cell

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Authors: Halimi Mohamed Taher, Kordoghli Bassem, Ben Hassen Mohamed, Sakli Faouzi

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Textile industry has been an important part of many developing countries economies such as Tunisia. This industry is confronted with a challenging and increasing competitive environment. Good quality management in production process is the key factor for retaining existence especially in raw material exploitation. The present work aims to develop an intelligent system for fabric inspection. In the first step, we have studied the method used for fabric control which takes into account the default length and localization in woven. In the second step, we have used a method based on the fuzzy logic to minimize the Demerit point indicator with appropriate total rollers length, so that the quality problem becomes multi-objective. In order to optimize the total fabric quality, we have applied the genetic algorithm (GA).

Keywords: fabric control, Fuzzy logic, genetic algorithm, quality management

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Authors: Yasaman Sanayei, Alireza Bahiraie

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This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR). The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. Employing reactive dye by Sphingomonas paucimobilis bacteria at sequence batch reactor is a novel approach of dye removal. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was a= 0.44. In orderto adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with R2> 0.99 and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics. Note that SBR are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANN. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed.

Keywords: artificial neural network, COD removal, SBR, Sphingomonas paucimobilis

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

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Authors: Mimoza Canga, Vito Malagnino, Giulia Malagnino, Irene Malagnino

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Objective: The objective of this study was to compare the effectiveness of Mtwo and RaCe rotary instruments, in cleaning and shaping root canals curvature. Material and Method: The present study was conducted on 160 simulated canals in resin blocks, with an angle curvature 15°-30°. These 160 simulated canals were divided into two groups, where each group consisted of 80 blocks. Each group was divided into two subgroups (n=40 canals each). The simulated canals subgroups were prepared with Mtwo and RaCe rotary nickel-titanium instruments. The root canals were measured at four different points of reference, starting at 13 mm from the orifice. In the first group, the canals were prepared using Mtwo rotary system (VDW, Munich, Germany). The Mtwo files used were: 10/0.04, 15/0.05, 20/0.06, and 25/0.06. These instruments entered in the full length of the canal. Each file was rotated in the canal until it reached the apical point. In the second group, the canals were prepared using RaCe instruments (La Chaux-De-Fonds, Switzerland), performing the crown down technique, using the torque electric control motor (VDWCO, Munich, Germany), with 600 RPM and 2n/cm as follow: ≠40/0.10, ≠35/0.08, ≠30/0.06, ≠25/0.04, ≠25/0.02. The data were recorded using SPSS version 23 software (Microsoft, IL, USA). Data analysis was done using ANOVA test. Results: The results obtained by using the Mtwo rotary instruments, showed that these instruments were able to clean and shape in the right-to-left motion curved canals, at different levels, without any deviation, and in perfect symmetry, with a P-value=0.000. The data showed that the greater the depth of the root canal, the greater the deviations of the RaCe rotary instruments. These deviations occurred in three levels, which are: S2(P=0.004), S3( P=0.007), S4(P=0.009). The Mtwo files can go deeper and create a greater angle in S4 level (21°-28°), compared to RaCe instruments with an angle equal to 19°-24°. Conclusion: The present study noted a clinically significant difference between Mtwo rotary instruments and RaCe rotary files used for the canal preparation and indicated that Mtwo instruments are a better choice for the curved canals.

Keywords: canal curvature, canal preparation, Mtwo, RaCe, resin blocks

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Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Kemi Olalekan Oduntan

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This paper is of the view that entrepreneurship education (if well utilized) can solve the problems of unemployment and the clamor for paid employment in Nigeria. Nigeria educational system is bookish too more academically oriented thereby neglecting the entrepreneurial and vocational values to a greater extent. This paper examines the utilization of entrepreneurship education as a way out of the myriad of unemployment in Nigeria, with the need to refocus Nigeria educational system towards skills acquisition that prepares Nigerians for self-reliance, hence being an employer of labor, while sustainable development and economic diversification are also stressed. The paper further argues that entrepreneurship education will equip the students and Nigeria working class youth with the skills to be jobs creators and become an employer of labor which it will solve Nigeria’s problems such as poverty, overdependence on foreign goods, low economic growth and poor infrastructural development among others. We concludes and recommends that a new pedagogy that prepares students and working class youth with knowledge and practical skills to be entrepreneurial be instituted, promoted and made compulsory in all our tertiary institutions as a way of reducing the menace unemployment in Nigeria.

Keywords: entrepreneurship education, unemployment, national development, self-employment

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Daodu Joshua Rotimi

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This study investigated the Efficacy of Self-Assessment Metacognitive Strategy on Academic performance in Energy Concepts among Upper Basic Science Students in Ankpa, Kogi State, Nigeria. The research design adopted for the study was a Quasi-experimental control group design which employed a pretest, posttest of the experimental and control groups. The population of the study consisted of one hundred and twenty-four (124) JSSII Students; sixty-five (65) for the experimental group and (59) for the control group. The instrument used for the study was the Energy Concept Performance Test (ECPT), with a reliability coefficient of 0.80. Two research questions were answered using descriptive statistics of mean and standard deviation, while two hypotheses were tested using a t-test at P≤0.05 level of significance. The findings of the study revealed that the use of the Self-Assessment Metacognitive Strategy has a positive effect on students’ performance in energy concepts among upper Basic Science Students leading to high academic performance; also, there is no significant difference in the mean Academic Performance scores between Male and Female students taught Energy Concept using Self-Assessment Metacognitive Strategy. Based on the research findings, recommendations were made, which include that Secondary school teachers should be encouraged the use Self-Assessment Metacognitive strategy so as to make the learning process attractive, interactive and enriching to the learners.

Keywords: metacognition, self-assessment, performance, efficacy

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Authors: Yasmin Umar Assegaf, Falikhatun, Salamah Wahyuni

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This study aims to provide empirical evidence about the influence of Islamic Corporate Social Responsibility Disclosures of the financial performance of Islamic banking with the characteristics of the company, as a control variable in Islamic banking in Indonesia. ICSR disclosures are an independent variable, while the Financial Performance is the dependent variable (proxied by Return on Assets (ROA), Return on Equity (ROE), Income Expense Ratio (IER), and Non-net Interest Margin (NIM). The control variables used are firm size, firm age and the type of audit. The population of the study was all Islamic Banks (BUS) operate in Indonesia. The research sample is Islamic Commercial Bank which has existed in Indonesia since 2002 and publishes financial statements between the years of 2007-2011. The sample of the study were include 31 Annual Report published. The results of this study concluded that there are significant influences between the ICSR Disclosures and financial performance. The disclosure is partially effect on ROA, IER and NIM, whereas there is no influence on ROE. Further result shows that all control variables (Firm Size, Age, and Type of Audit Companies) does not have any influence on ICSR Disclosures in Indonesia. This research gives a suggestion for further research to compare these ICSR disclosures in Indonesia with ICSR disclosures in other countries that have Islamic banking, by using other measure variables of financial performance, to get more comprehensive model and real picture.

Keywords: ROA, ROE, IER, NIM, company size, age of the company, audit type, Islamic banking

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Authors: B. Almassri, F. Almahmoud, R. Francois

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Near surface mounted reinforcement (NSM) technique is one of the promising techniques used nowadays to strengthen reinforced concrete (RC) structures. In the NSM technique, the Carbon Fibre Reinforced Polymer (CFRP) rods are placed inside pre-cut grooves and are bonded to the concrete with epoxy adhesive. This paper studies the non-classical mode of failure ‘the separation of concrete cover’ according to experimental and numerical FE modelling results. Experimental results and numerical modelling results of a 3D finite element (FE) model using the commercial software Abaqus and 2D FE model FEMIX were obtained on two beams, one corroded (25 years of corrosion procedure) and one control (A1CL3-R and A1T-R) were each repaired in bending using NSM CFRP rod and were then tested up to failure. The results showed that the NSM technique increased the overall capacity of control and corroded beams despite a non-classical mode of failure with separation of the concrete cover occurring in the corroded beam due to damage induced by corrosion. Another FE model used external steel stirrups around the repaired corroded beam A1CL3-R which failed with the separation of concrete cover, this model showed a change in the mode of failure form a non-classical mode of failure by the separation of concrete cover to the same mode of failure of the repaired control beam by the crushing of compressed concrete.

Keywords: corrosion, repair, Reinforced Concrete, FEM, CFRP, FEMIX

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Authors: Ademuyiwa Agbonyin, Stamatis Zoras, Mohammad Zandi

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This paper investigates the extent to which building energy modelling can be informed based on preliminary information provided by infrared thermography using a thermal imaging camera in a walkthrough audit. The case-study building is the Sheffield Cathedral, built in the early 1400s. Based on an informative qualitative report generated from the thermal images taken at the site, the regions showing significant heat loss are input into a computer model of the cathedral within the integrated environmental solution (IES) virtual environment software which performs an energy simulation to determine quantitative heat losses through the building envelope. Building data such as material thermal properties and building plans are provided by the architects, Thomas Ford and Partners Ltd. The results of the modelling revealed the portions of the building with the highest heat loss and these aligned with those suggested by the thermal camera. Retrofit options for the building are also considered, however, may not see implementation due to a desire to conserve the architectural heritage of the building. Results show that thermal imaging in a walk-through audit serves as a useful guide for the energy modelling process. Hand calculations were also performed to serve as a 'control' to estimate losses, providing a second set of data points of comparison.

Keywords: historic buildings, energy retrofit, thermal comfort, software modelling, energy modelling

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Authors: Sani Ismaila, Shafiu Yau, Abubakar Salisu, Buhari Salisu, Sharifat Balogun, Mustapha Abubakar, Biobaku Khalid, Agaie Bello

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Over the years, Japanese quail egg has been in use in the management of diseases. The objective of this study was to evaluate the analgesic, anti-inflammatory and gastroprotective effects of raw Quail egg (yolk + albumin) in rats. Pain was assessed in rats by recording the latent period and writing reflex, anti-inflammatory effect was determined using both motility and compression test, while the gastro-protective effects were assessed by observing the histology of the stomach after diclofenac-induced gastric ulcers and subsequent treatment with the quail egg, Rats were randomly assigned into 4 groups; Groups I: were the control non-treated (NT), Group II were treated with Tramadol 50 mg/kg/Os (TMD) or Indomethacin (IND) 5mg/kg/Os (positive control for the writhing reflex determination), while group III and IV were treated with 3 and 6g/kg of raw quail egg respectively). Groups treated with quail egg in both doses showed a significant increase in the latent period (p <0 .05) when compared to the control NT, but lower than the group treated with tramadol at 20mins interval (p<0.05). Writing reflexes decrease in groups II, III, and IV compared to the NT group (p < 0.05). While motility increases significantly (p < 0.05) in groups II, compared to I (p<0.05). Control non-treated rats showed a quicker and extensive response to compression using the Vanier calliper on the inflamed paw compared to groups II-IV (p < 0.05). Histological studies of the stomach revealed sloughing of the epithelia, cellular infiltration with micro abscesses in the non-treated, while groups treated concurrently with quail egg showed proliferation of the glandular epithelia and goblet cells, and those treated 30 minutes before diclofenac administration showed proliferation of glands and thickening of the squamous epithelia. This study showed that quail egg has analgesic, anti-inflammatory and gastro-protective potentials and can be used as adjuvant treatment whenever COX-2 enzymes inhibitors are indicated.

Keywords: analgesia, anti-inflammatory, gastroprotective effect, japanese quail egg

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: Wenjuan Du

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The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.

Keywords: phase compensation method, power system small-signal stability, power system stabilizer

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Authors: Naci Büyükkaracığan

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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

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Authors: Nzeaka Emmanuel Ezimako

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With the advent of new media, especially X, the government's previous foundation of media power and control in Nigeria has been diminished because they can no longer regulate the public sphere to control social action and reactions. This study examined how IPOB (Indigenous People of Biafra) resistance and the 2020 #Endsars aborted revolution were able to control public discourse during social upheavals, as well as how the new media have diminished the influence that the government and media owners once had over Nigerians. This study is significant because it recognizes the social transformation brought about by the emergence of new media, particularly with the most widely used social media platform in Nigeria, X, and how citizen media activity is altering the media ecosystem and challenging the government and private media owners' hegemony over news coverage in Nigeria to the point where the government saw X as a blatant threat to its hegemony and banned it in 2021. This study used a triangulation of qualitative and quantitative analysis with 300 respondents (n=300) from different sectors of the media practitioners, scholars, and university students in Nigeria to draw a conclusion in line with Democratic Participant Media Theory, which questions the necessity for centralized media regulated by the government and conglomerates. The contributions to filling the gap in the literature are meant to aid readers in comprehending how X has developed into a dominant force in Nigerian media, particularly during the crisis. The study offers recommendations for media executives, policymakers, and the public on how to manage the media conflict that has developed because of the loss of official government oversight of the mass media due to the emergence of X in the media space.

Keywords: Twitter, new media, regulations, dominance, resistance

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Authors: Chan Ka Lok Sobel

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The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

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Authors: Ibrahim A. Kareem, Sina O. Ayelaagbe

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This study investigated the effects of web-enabled Sculpture package on Colleges of Education students’ psychomotor level in Fine Arts in South-west, Nigeria. The objectives of this study were to: (i) determine the effect of web-enabled Sculpture package on Fine Arts Students’ performance; (ii) find out the effect of ability levels on Fine Arts Students’ performance and (iii) ascertain the interaction effect of treatment and ability levels on Fine Arts Students’ performance. The study was quasi-experimental design. A total of 48 Fine Arts Students participated in the study. There were 26 students in experimental and 22 for the control. The respondents were purposively sampled from Adeyemi College of Education, Ondo and Federal College of Education (Special) Oyo. Sculpture Achievement Test, Sculpture Skill Test and Sculpture ‘on the Spot’ Skill Assessment Instrument were validated by experts while Pearson’s Product Moment Correlation (PPMC) statistics was used to analyse the instrument while the remaining two instruments were subjected to Cronbach alpha statistics. Data were analysed using t-test and ANCOVA were used to test the hypotheses at 0.05 level of significance. The findings of the study revealed that: (i) Fine Arts Students’ in the experimental group performed significantly better than the control group; (ii) there was a significant difference among high, medium and low ability levels mean scores of Fine Arts Students’ performance in Colleges of Education; (iii) there was no significant interaction effect of treatment and ability levels on the mean scores of Fine Arts Students’ performance in Colleges of Education and. The study concluded that Fine Arts Students exposed to web-enabled Sculpture package performed better than those taught using the conventional method. Based on the study it was recommended that lecturers in Colleges of Education should endeavour to adapt and utilise web-enabled Sculpture package for teaching sculpture.

Keywords: fine art, psychomotor, sculpture, web-enabled

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Renata L. C. Leão, João E. Nascimento, Natalia C. E. S. Nascimento, Elaine S. Vasconcelos, Mércia L. Oliveira

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The quality control procedures of a radiopharmaceutical include the assessment of its chemical purity. The method suggested by international pharmacopeias consists of a thin layer chromatographic run. In this paper, the method proposed by the United States Pharmacopeia (USP) is compared to a direct method to determine the final concentration of aminopolyether in Fludeoxyglucose (¹⁸F-FDG) preparations. The approach (no chromatographic run) was achieved by placing the thin-layer chromatography (TLC) plate directly on an iodine vapor chamber. Both methods were validated and they showed adequate results to determine the concentration of aminopolyether in ¹⁸F-FDG preparations. However, the direct method is more sensitive, faster and simpler when compared to the reference method (with chromatographic run), and it may be chosen for use in routine quality control of ¹⁸F-FDG.

Keywords: chemical purity, Kryptofix 222, thin layer chromatography, validation

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Authors: Ibrahim A. H. Barakat, Ahmed R. Al-Himaidi

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The present study was conducted to determine the role and optimum concentration of fenugreek seed extract during in-vitro maturation on in-vitro maturation and developmental competence of Neaimi sheep oocytes following in-vitro fertilization. The Cumulus Oocyte Complexes (COCs) collected from sheep slaughterhouse ovaries were randomly divided into three groups, and they were matured for 24 hrs. in maturation medium containing fenugreek seed extract (0, 1 and 10 µg ml-1). Oocytes of a control group were matured in a medium containing 1 µg ml-1 estradiol 17β. After maturation, half of oocytes were fixed and stained for evaluation of nuclear maturation. The rest of oocytes were fertilized in vitro with fresh semen, then cultured for 9 days for the assessment of the developmental capacity of the oocytes. The results showed that the mean values of oocytes with expanded cumulus cells percentage were not significantly different among all groups (P < 0.05). But nuclear maturation rate of oocytes matured with 10 µg ml-1 fenugreek seed extract was significantly higher than that of the control group. The maturation rate and development to morula and blastocyst stage for oocytes matured at 10 µg ml-1 fenugreek seed extract was significantly higher than those matured at 1µg ml-1 of fenugreek seed extract and the control group. In conclusion, better maturation and developmental capacity rate to morula and blastocyst stage were obtained by the addition of 10 µg ml-1 fenugreek seed extract to maturation medium than addition of 1 µg ml-1 estradiol-17β (P < 0.05).

Keywords: fenugreek seed extract, in vitro maturation, sheep oocytes, in vitro fertilization, embryo development

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Authors: M. Akif Ceviz, Alirıza Kaleli, Erdoğan Güner

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LPG pressure regulator is a device which is used to change the phase of LPG from liquid to gas by decreasing the pressure. During the phase change, it is necessary to supply the latent heat of LPG to prevent excessive low temperature. Engine coolant is circulated in the pressure regulator for this purpose. Therefore, pressure regulator is a type of heat exchanger that should be designed for different engine operating conditions. The design of the regulator should ensure that the flow of LPG is in gaseous phase to the injectors during the engine steady state and transient operating conditions. The pressure regulators in the LPG gaseous injection systems currently used can easily change the phase of LPG, however, there is no any control on the LPG temperature in conventional LPG injection systems. It is possible to increase temperature excessively. In this study, a control unit has been tested to keep the LPG temperature in a band. Result of the study showed that the engine performance characteristics can be increased by using the system.

Keywords: temperature, pressure regulator, LPG, PID

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Authors: Kalu Samuel Ukanwa, Kumar Patchigolla, Ruben Sakrabani

Abstract:

The use of biosolids from thermal conversion of palm waste for soil fertility enhancement was tested in acidic soil of Southern Nigeria for the growing of Habanero chili pepper (Capsicum chinense jacq.). Soil samples from the two sites, showed pH 4.8 and 4.8 for site A and B respectively, below 5.6-6.8 optimum range and other fertility parameters indicating a low threshold for pepper growth. Nursery planting was done at different weeks to determine the optimum planting period. Ash analysis showed that it contains 26% of total K, 20% of total Ca, 0.27% of total P, and pH 11. The two sites were laid for an experiment in randomized complete block design and setup with three replications side by side. Each plot measured 3 x 2 m and a total of 15 plots for each site, four treatments, and one control. Outlined as control, 2, 4, 6 and 8 tonnes/hectare of palm waste ash, the combined average for both sites with correspondent yield after six harvests in one season are; 0, 5.8, 6, 6, 14.5 tonnes/hectare respectively to treatments. Optimum nursery survival rate was high in July; the crop yield was linear to the ash application. Site A had 6% yield higher than site B. Fruit development, weight, and total yield in relation to the control plot showed that palm waste ash is effective for soil amendment, nutrient delivery, and exchange.

Keywords: ash, palm waste, pepper, soil amendment

Procedia PDF Downloads 130

Authors: Sebastian Hiergeist

Abstract:

It is a common view that Unmanned Aerial Vehicles (UAV) tend to migrate into the civil airspace. This trend is challenging UAV manufacturer in plenty ways, as there come up a lot of new requirements and functional aspects. On the higher application levels, this might be collision detection and avoidance and similar features, whereas all these functions only act as input for the flight control components of the aircraft. The flight control computer (FCC) is the central component when it comes up to ensure a continuous safe flight and landing. As these systems are flight critical, they have to be built up redundantly to be able to provide a Fail-Operational behavior. Recent architectural approaches of FCCs used in UAV systems are often based on very simple microprocessors in combination with proprietary Application-Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) extensions implementing the whole redundancy functionality. In the future, such simple microprocessors may not be available anymore as they are more and more replaced by higher sophisticated System on Chip (SoC). As the avionic industry cannot provide enough market power to significantly influence the development of new semiconductor products, the use of solutions from foreign markets is almost inevitable. Products stemming from the industrial market developed according to IEC 61508, or automotive SoCs, according to ISO 26262, can be seen as candidates as they have been developed for similar environments. Current available SoC from the industrial or automotive sector provides quite a broad selection of interfaces like, i.e., Ethernet, SPI or FlexRay, that might come into account for the implementation of a redundancy network. In this context, possible network architectures shall be investigated which could be established by using the interfaces stated above. Of importance here is the avoidance of any single point of failures, as well as a proper segregation in distinct fault containment regions. The performed analysis is supported by the use of guidelines, published by the aviation authorities (FAA and EASA), on the reliability of data networks. The main focus clearly lies on the reachable level of safety, but also other aspects like performance and determinism play an important role and are considered in the research. Due to the further increase in design complexity of recent and future SoCs, also the risk of design errors, which might lead to common mode faults, increases. Thus in the context of this work also the aspect of dissimilarity will be considered to limit the effect of design errors. To achieve this, the work is limited to broadly available interfaces available in products from the most common silicon manufacturer. The resulting work shall support the design of future UAV FCCs by giving a guideline on building up a redundancy network between SoCs, solely using on board interfaces. Therefore the author will provide a detailed usability analysis on available interfaces provided by recent SoC solutions, suggestions on possible redundancy architectures based on these interfaces and an assessment of the most relevant characteristics of the suggested network architectures, like e.g. safety or performance.

Keywords: redundancy, System-on-Chip, UAV, flight control computer (FCC)

Procedia PDF Downloads 215

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

Procedia PDF Downloads 206

Authors: Suglo Tohari Luri

Abstract:

Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

Procedia PDF Downloads 191