Search results for: TV news networks

Authors: Giselle Maggie Fer Castañeda, Diego Iván González

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The objective of this work was to study the autoshaped choice behavior in the Donahoe, Burgos and Palmer (DBP) neural network model and analyze it under the matching law. Autoshaped choice can be viewed as a form of economic behavior defined as the preference between alternatives according to their relative outcomes. The Donahoe, Burgos and Palmer (DBP) model is a connectionist proposal that unifies operant and Pavlovian conditioning. This model has been used for more than three decades as a neurobehavioral explanation of conditioning phenomena, as well as a generator of predictions suitable for experimental testing with non-human animals and humans. The study consisted of different simulations in which, in each one, a ratio of reinforcement was established for two alternatives, and the responses (i.e., activations) in each of them were measured. Choice studies with animals have demonstrated that the data generally conform closely to the generalized matching law equation, which states that the response ratio equals proportionally to the reinforcement ratio; therefore, it was expected to find similar results with the neural networks of the Donahoe, Burgos and Palmer (DBP) model since these networks have simulated and predicted various conditioning phenomena. The results were analyzed by the generalized matching law equation, and it was observed that under some contingencies, the data from the networks adjusted approximately to what was established by the equation. Implications and limitations are discussed.

Keywords: matching law, neural networks, computational models, behavioral sciences

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Swatantra

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Hinglish, a blended version of Hindi and English, emerged due to the lack of the competence and command of the speakers over the foreign language, i., e., English. But, amazingly, the trend has gained wide acceptance. In India, this acceptance has gone up to the extent that popular news anchors at the prime time shows are frequently using it. At the moment, instead of being considered a flaw of their presentation Hinglish is emerging as a trendy genre. Its pervasive usage and extensive acceptance is motivating youngsters to opt for the similar kind of patterns. The current study is an endeavour to assess the impact of this trend on the new language learners. With the help of semi-structured interviews, the researcher has tried to gauge the level of comfort and desire to be at par with the other fluent English speakers. The results clearly depict a substantiated boost in the confidence level of learners because they are able to use the vocabulary and sentence patterns of their own choice and convenience. The prevalence and acceptance of the trend in the main stream media have really served as a catalyst and the desire to be at par with the other fluent speakers is also fading away. The users of Hinglish find this trend to be closer to their heart as in the earlier times in the absence of exact translation they had to compromise with the meaning or spirit of the word/phrase / sentence. But now enhanced flexibility is leaving them more comfortable and confident.

Keywords: Hinglish, language learners, linguistic trends, media

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Kettawa Boonprakarn, Jedsarid Sangkaphan, Bejapornd Deekhuntod, Nuntharat Suriyo

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This study aimed to investigate the existence of field corn networks on the Thailand-Burma border under the patron-client contract farming system. The data of this qualitative study were collected through in-depth interviews with nine key informants. The results of the study revealed that the existence of the field corn networks was associated with the relationship where farmers had to share their crops with protectors in the areas under the influence of the KNU (Karen National Union) and the DKBA (Democratic Karen Buddhist Army) or Burmese soldiers. A Mae Liang, the person who starts a network has a connection with a Thaokae, Luk Rai Hua Chai or the head of a group of farmers, and farmers. They are under the patron-client system with trust and loyalty that enable the head of the group and the farmers in the Burma border side to remain under the same Mae Liang even though the business has been passed down to later generations.

Keywords: existence, field-corn networks, patron-client system, contract farming

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Authors: Jandot Aurélia

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In France, in the main media, the concern about nuclear safety and security has not really appeared before the beginning of the 1970s. The gradual changes in its perception are studied here through the arguments given in the main French news magazines, linked with several parameters. As this represents a considerable amount of copies and thus of information, are selected here the main articles as well as the main “mental images” aiming to persuade the readers and which have led the public awareness to evolve. Indeed, in the 1970s, in France, these evolutions were not made in one day. Indeed, over the period, many articles were still in favor of nuclear power plants and promoted the technological advances that were made in this field. They had to be taken into account. But, gradually, grew up arguments and mental images discrediting the perception of nuclear technology. Among these were the environmental impacts of this industry, as the question of pollution progressively appeared. So, between 1970 and 1979, the language has changed, as the perceptible objectives of the communication, allowing to discern the deepest intentions of the editorial staffs of the French news magazines. This is all these changes that are emphasized here, over a period when the safety and security concern linked to the nuclear technology, to there a field for specialists, has become progressively a social issue seemingly open to all.

Keywords: environmental impacts, media discourse, nuclear security, public awareness

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

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The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

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Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan

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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.

Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks

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Authors: Abdulmjeid Aljerawi

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This study aimed to investigate the students' attitudes towards the use of social networking in education. Due to the nature of the study, and on the basis of its problem, objectives, and questions, the researcher used the descriptive approach. An appropriate questionnaire was prepared and validity and reliability were ensured. The questionnaire was then applied to the study sample of 434 students from King Saud University.

Keywords: social networks, education, learning, students

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Authors: Vandana Mishra, Niladri Sekhar Dash, Jayshree Charkraborty

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This present paper focuses on the application of corpus linguistics techniques for critical discourse analysis (CDA) of Hindi newspapers. While Corpus linguistics is the study of language as expressed in corpora (samples) of 'real world' text, CDA is an interdisciplinary approach to the study of discourse that views language as a form of social practice. CDA has mainly been studied from a qualitative perspective. However, we can say that recent studies have begun combining corpus linguistics with CDA in analyzing large volumes of text for the study of existing power relations in society. The corpus under our study is also of a sizable amount (1 million words of Hindi newspaper texts) and its analysis requires an alternative analytical procedure. So, we have combined both the quantitative approach i.e. the use of corpus techniques with CDA’s traditional qualitative analysis. In this context, we have focused on the Keyword Analysis Sorting Concordance Lines of the selected Keywords and calculating collocates of the keywords. We have made use of the Wordsmith Tool for all these analysis. The analysis starts with identifying the keywords in the political news corpus when compared with the main news corpus. The keywords are extracted from the corpus based on their keyness calculated through statistical tests like chi-squared test and log-likelihood test on the frequent words of the corpus. Some of the top occurring keywords are मोदी (Modi), भाजपा (BJP), कांग्रेस (Congress), सरकार (Government) and पार्टी (Political party). This is followed by the concordance analysis of these keywords which generates thousands of lines but we have to select few lines and examine them based on our objective. We have also calculated the collocates of the keywords based on their Mutual Information (MI) score. Both concordance and collocation help to identify lexical patterns in the political texts. Finally, all these quantitative results derived from the corpus techniques will be subjectively interpreted in accordance to the CDA’s theory to examine the ways in which political news discourse produces social and political inequality, power abuse or domination.

Keywords: critical discourse analysis, corpus linguistics, Hindi newspapers, power relations

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Authors: Fayaz Moosavi, Saeid Moradyfard

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One of the methods in avoiding management fraud and increasing the quality of financial information, is the notification of qualitative features of financial information, including conservatism characteristic. Although taking a conservatism approach, while boosting the quality of financial information, is able to reduce the informational risk and the cost of capital stock of commercial department, by presenting an improper image about the situation of the commercial department, raises the risk of failure in returning the main and capital interest, and consequently the cost of capital of the commercial department. In order to know if conservatism finally leads to the increase or decrease of the cost of capital or does not have any influence on it, information regarding accepted companies in Tehran stock exchange is utilized by application of pooling method from 2007 to 2012 and it included 124 companies. The results of the study revealed that there is an opposite and meaningful relationship between conditional conservatism and the cost of capital of the company. In other words, if bad and unsuitable news and signs are reflected sooner than good news in accounting profit, the cost of capital of the company increases. In addition, there is a positive and meaningful relationship between the cost of capital and lack of information asymmetry.

Keywords: conditional conservatism, lack of information asymmetry, the cost of capital, stock exchange

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Authors: Yaseein S. Hussein, Victor P. Gil Jiménez, Abdulmajeed Al-Jumaily

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Due to the rapid advancement of technology, there is an increasing demand for wireless connections that are both fast and reliable, with minimal latency. New wireless communication standards are developed every decade, and the year 2030 is expected to see the introduction of 6G. The primary objectives of 6G network and terminal designs are focused on sustainability and environmental friendliness. The International Telecommunication Union-Recommendation division (ITU-R) has established the minimum requirements for 6G, with peak and user data rates of 1 Tbps and 10-100 Gbps, respectively. In this context, Light Fidelity (Li-Fi) technology is the most promising candidate to meet these requirements. This article will explore the various advantages, features, and potential applications of Li-Fi technology, and compare it with 5G networking, to showcase its potential impact among other emerging technologies that aim to enable 6G networks.

Keywords: 6G networks, artificial intelligence (AI), Li-Fi technology, Terahertz (THz) communication, visible light communication (VLC)

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Authors: Ladaporn Pithuk

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This study aims to investigate the marketing mixed factors that affecting on expectations about commercial transactions through social networks. The research method will using quantitative research, data was collected by questionnaires to person have experience access to trading over the internet for 400 sample by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and using quality function deployment for hypothesis testing. Finding the most significant interrelationship between marketing mixed factors and commercial transactions expectations through social networks are product and place the relationship of five ties product and place (location) is involved in almost all will make the site a model that meets the needs of the user visit. In terms of price, the promotion, privacy, personalization and providing a process technical. This will make operations more efficient, reduce confusion, duplication, delays in data transmission, including the creation of different elements in products and services.

Keywords: commercial transactions expectations, marketing mixed factors, social networks, consumer behavior

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Authors: Pamela Aimee Rigor

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This study aims to examine the representation of Syrian refugees resettled in Vancouver and the Lower Mainland in local community and major newspapers. While there is strong support for immigration in Canada, public opinion towards refugees and asylum seekers is a bit more varied. Concerns about the legitimacy of refugee claims are among the common concerns of Canadians, and hateful or negative narratives are still present in Canadian media discourse which affects how people view refugees. To counter the narratives, these Syrian refugees must publicly declare how grateful they are because they are resettled in Canada. The dominant media discourse is that these refugees should be grateful as they have been graciously accepted by Canada and Canadians, once again upholding the image of Canada being a generous and humanitarian nation. The study examined the representation of Syrian refugees and the Syrian refugee resettlement in Canadian newspapers from September 2015 to October 2017 – around the time Prime Minister Trudeau came into power up until the present. Using a combination of content and discourse analysis, it aimed to uncover how local community and major newspapers in Vancouver covered the Syrian refugee ‘crisis’ – more particularly, the arrival and resettlement of the refugees in the country. Using the qualitative data analysis software Nvivo 12, the newspapers were analyzed and sorted into themes. Based on the initial findings, the discourse of Canada being a humanitarian country and Canadians being generous, as well as the idea of Syrian refugees having to publicly announce how grateful they are, is still present in the local community newspapers. This seems to be done to counter the hateful narratives of citizens who might view them as people who are abusing help provided by the community or the services provided by the government. However, compared to the major and national newspapers in Canada, many these local community newspapers are very inclusive of Syrian refugee voices. Most of the News and Community articles interview Syrian refugees and ask them their personal stories of plight, survival, resettlement and starting a ‘new life’ in Canada. They are not seen as potential threats nor are they dismissed – the refugees were named and were allowed to share their personal experiences in these news articles. These community newspapers, even though their representations are far from perfect, actually address some aspects of the refugee resettlement issue and respond to their community’s needs. There are quite a number of news articles that announce community meetings and orientations about the Syrian refugee crisis, ways to help in the resettlement process, as well as community fundraising activities to help sponsor refugees or resettle newly arrived refugees. This study aims to promote awareness of how these individuals are socially constructed so we can, in turn, be aware of the certain biases and stereotypes present, and its implications on refugee laws and public response to the issue.

Keywords: forced migration and conflict, media representations, race and multiculturalism, refugee studies

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Authors: Vivek Kumar Singh, Tripti Singh

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An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

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Authors: Yong Xue, Daniel A. Menascé

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Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.

Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Tianle Yang

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As a common mental disorder, depression is a leading cause of various diseases worldwide. Early detection and treatment of depression can dramatically promote remission and prevent relapse. However, conventional ways of depression diagnosis require considerable human effort and cause economic burden, while still being prone to misdiagnosis. On the other hand, recent studies report that physical characteristics are major contributors to the diagnosis of depression, which inspires us to mine the internal relationship by neural networks instead of relying on clinical experiences. In this paper, neural networks are constructed to predict depression from physical characteristics. Two initialization methods are examined - Xaiver and Kaiming initialization. Experimental results show that a 3-layers neural network with Kaiming initialization achieves 83% accuracy.

Keywords: depression, neural network, Xavier initialization, Kaiming initialization

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Authors: Sónia Ribeiro, Diana Farinha, Hélia Sales, Rita Pontes, João Nunes

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The demand and commitment to sustainability in the agrifood sector introduce news opportunities for new composite materials. Composite materials are emerging as a vital entity for the sustainable development. Polylactic acid (PLA) has been recognized as a potential polymer with attractive characteristics for agrifood sector applications. PLA that can be beneficial for the development of composites, biocomposites, films, porous gels, and so on. The production of PLA from lignocellulosic biomass residues matrix is a key option towards a sustainable and circular bioeconomy and a non-competitive application with feed and food sector. The Flui and BeirInov projects presents news developments in the production of PLA composites to value the Portuguese forest ecosystem, with high amount of lignocellulosic biomass residues and available. A performance production of lactic acid from lignocellulosic biomass undergoes a process of autohydrolysis, saccharification and fermentation, originating a lactic acid fermentation medium with a 72.27g.L-1 was obtained and a final purification of 72%. The high purification PLA from multi lignocellulosic residues representing one economic expensive process, and a new materials and application for the polymers and a combination with others types of composites matrix characteristic is the drive-up for this green market.

Keywords: polylactic acid, lignocellulosic biomass, agrifood, composite materials

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

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Authors: Kenny Onayemi

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In an era where academic institutions increasingly rely on information technology, the security of academic networks has emerged as a paramount concern. This comprehensive study delves into the effectiveness of security practices, including network mapping, vulnerability scanning, and penetration testing, within academic networks. Leveraging data from surveys administered to faculty, staff, IT professionals and IT students in the university, the study assesses their familiarity with these practices, perceived effectiveness, and frequency of implementation. The findings reveal that a significant portion of respondents exhibit a strong understanding of network mapping, vulnerability scanning, and penetration testing, highlighting the presence of knowledgeable professionals within academic institutions. Additionally, active scanning using network scanning tools and automated vulnerability scanning tools emerge as highly effective methods. However, concerns arise as the respondents show that the academic institutions conduct these practices rarely or never. Notably, many respondents have reported significant vulnerabilities or security incidents through these security measures within their institution. This study concludes with recommendations to enhance network security awareness and practices among faculty, staff, IT personnel, and students, ultimately fortifying the security posture of academic networks in the digital age.

Keywords: network security, academic networks, vulnerability scanning, penetration testing, information security

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Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

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An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio

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Authors: Jorge Fernandes Teixeira Filho, André Oliveira Alcantara Fontenele, Érick Aragão Ribeiro

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The constant emergence of new technologies used in automated processes makes it necessary for teachers and traders to apply new technologies in their classes. This paper presents an application of a new technology that will be employed in a didactic plant, which represents an effluent treatment process located in a laboratory of a federal educational institution. At work were studied in the first place, all components to be placed on automation laboratory in order to determine ways to program, parameterize and organize the plant. New technologies that have been implemented to the process are basically an AS-i network and a Profinet network, a SCADA system, which represented a major innovation in the laboratory. The project makes it possible to carry out in the laboratory various practices of industrial networks and SCADA systems.

Keywords: automation, industrial networks, SCADA systems, lab automation

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Mohamed Idris S. Abozaed, Suliman Mohamed Elrajoubi

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Researches and concerns in power quality gained significant momentum in the field of power electronics systems over the last two decades globally. This sudden increase in the number of concerns over power quality problems is a result of the huge increase in the use of non-linear loads. In this paper, power quality evaluation of some distribution networks at Misurata - Libya has been done using a power quality and energy analyzer (Fluke 437 Series II). The results of this evaluation are used to minimize the problems of power quality. The analysis shows the main power quality problems that exist and the level of awareness of power quality issues with the aim of generating a start point which can be used as guidelines for researchers and end users in the field of power systems.

Keywords: power quality disturbances, power quality evaluation, statistical analysis, electrical distribution networks

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Authors: Marchant Van Der Schyff

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South Africa remains one of the most dangerous places for women – lesbians in particular – to live freely and safely, where a culture of patriarchy and a lack of socio-economic opportunity are ubiquitous throughout its communities. While the Internet has given a wider platform to provide insights to issues plaguing lesbians, very little information exists regarding the elements used in the construction of these online reports. This is not only due to the lack of language required to contextualise lesbian issues, but also persistent institutional and societal homophobia. This article describes the technical frames used in the online news reporting of four case studies of ‘queercide’. Through using a thematic coding sheet, data was collected from 70 online articles purposively selected based on priori population characteristics. The study found technical elements, such as the length of online reports, credible sources used, ‘code driven’-, and ‘user driven’ elements which were identified in the coded online articles. From the conclusions some clear trends emerged enabling the construction of a Venn-type diagram which present insights to how the murder of lesbians (referred to as ‘queercide’ in the article) is being reported on by online news media compared to the contemporary theoretical discussions on how these cases should be reported on.

Keywords: journalism, lesbian murder, queercide, technical frames, reporting, online

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Atabak Faramarzpour, Mohsen Mohammadian

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In this article, we introduce the stability of power system voltage and state DG power plants placement and its effect on improving voltage security margin in radial distribution networks. For this purpose, first, important definitions in voltage stability area such as small and big voltage disturbances, instability, and voltage collapse, and voltage security definitions are stated. Then, according to voltage collapse time, voltage stability is classified and each one's characteristics are stated.

Keywords: DG power plants, evaluation, voltage security, radial distribution networks

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