Search Results (35)

Gigabit-Capable Passive Optical Network (GPON) reach extension using optical amplification is well established, yet validation of user-facing service performance at the Optical Network Terminal (ONT) Ethernet interface remains limited. This paper addresses this gap by experimentally validating a distributed, circulator-separated reach extender based on two Semiconductor Optical Amplifiers (SOAs) in a controlled laboratory testbed, comparing a passive 50 km baseline with a 60 km reach-extended link. Service performance was assessed at the ONT Ethernet interface using RFC 6349 TCP throughput testing and ITU-T Y.1564 Ethernet service activation testing, with values reported as medians from 10 independent runs. Internet Protocol Television (IPTV) quality was evaluated using estimated Mean Opinion Score—Video (MOS-V) and Estimated Peak Signal-to-Noise Ratio (EPSNR) for H.264 and MPEG-2 streams. The 60 km configuration preserved upstream TCP throughput while reducing downstream throughput from 765.650 to 721.900 Mbit/s. Median latency increased from 1.336 to 1.408 ms, jitter decreased from 0.076 to 0.057 ms, and video-profile frame loss increased from 0 to approximately 0.0064. MOS-V values remained predominantly in the good range. The results indicate feasible 60 km GPON operation with measurable downstream and loss-related trade-offs, providing repeatable service-level validation beyond optical-budget-only reporting rather than introducing a new optical reach-extender architecture. Full article

The rise of streaming services and online story-sharing has led to a vast amount of cinema and television content being viewed and reviewed daily by a worldwide audience. It is a unique challenge to grasp the nuanced insights of these reviews, particularly as context, emotion, and specific components like acting, direction, and storyline intertwine extensively. The aim of this study is to address said complexity with a new hybrid Multi Criteria Decision-Making MCDM model that combines the Deck of Cards Method (DoCM) with the Circular Pythagorean Fuzzy Set (CPFS) framework, retaining the symmetry of information. The study is conducted on a simulated dataset to demonstrate the framework and outline the plan for approaching real-world press reviews. We postulate a more informed mechanism of assessing and choosing the most appropriate deep learning assembler, such as the transformer version, the hybrid Convolutional Neural Network CNN-RNN, and the attention-based framework of aspect-based sentiment mapping in film and television reviews. The model leverages both the cognitive ease of the DoCM and the expressive ability of the Pythagorean fuzzy set (PFS) in a circular relationship setting possessing symmetry, and can be applied to various decision-making situations other than the interpretation of media sentiments. This enables decision-makers to intuitively and flexibly compare alternatives based on many sentiment-relevant aspects, including classification accuracy, interpretability, computational efficiency, and generalization. The experiments are based on a hypothetical representation of media review datasets and test whether the model can combine human insight with algorithmic precision. Ultimately, this study presents a sound, structurally clear, and expandable framework of decision support to academicians and industry professionals involved in converging deep learning and opinion mining in entertainment analytics. Full article

This study presents an exhaustive analysis of LGBTQIA+ audiovisual production available on the main streaming platforms in Spain, covering both Spanish and international content. Using a sample of 1490 works from ten video-on-demand services (Apple TV+, Disney+, Filmin, FlixOlé, Max, Movistar Plus+, Netflix, Prime Video, Rakuten, and SkyShowtime), this study examines how the offered catalogues are configured and structured in response to the commercial dynamics of the LGBTQIA+ production market. Using quantitative methodology, the research addresses the industrial production models, the agents involved and the characteristics of the most widely offered narrative genres and formats, highlighting distribution patterns and visibility in the catalogues. The findings include a marked international abundance, a reflection of the global market guidelines and the hegemony of narratives aimed at transnational audiences. National productions, although less numerous, are a significant contribution to the audiovisual landscape, incorporating cultural identities with an LGBTQIA+ representation that is more aligned with local realities. The central role of independent producers is observed in production models where international agreements are outlined as a key strategy. In addition, it highlights the prevalence of genres such as drama and comedy, together with that of the film format. The visibility and representation of sexual and gender diversity indicates a positive commercial response, although with considerable challenges. Full article

Public transportation systems play a vital role in modern cities, but they face growing security challenges, particularly related to incidents of violence. Detecting and responding to violence in real time is crucial for ensuring passenger safety and the smooth operation of these transport networks. To address this issue, we propose an advanced artificial intelligence (AI) solution for identifying unsafe behaviours in public transport. The proposed approach employs deep learning action recognition models and utilises technologies like NVIDIA DeepStream SDK, Amazon Web Services (AWS) DirectConnect, local edge computing server, ONNXRuntime and MQTT to accelerate the end-to-end pipeline. The solution captures video streams from remote train stations closed circuit television (CCTV) networks, processes the data in the cloud, applies the action recognition model, and transmits the results to a live web application. A temporal pyramid network (TPN) action recognition model was trained on a newly curated video dataset mixing open-source resources and live simulated trials to identify the unsafe behaviours. The base model was able to achieve a validation accuracy of 93% when trained using open-source dataset samples and was improved to 97% when live simulated dataset was included during the training. The developed AI system was deployed at Wollongong Train Station (NSW, Australia) and showcased impressive accuracy in detecting violence incidents during an 8-week test period, achieving a reliable false-positive (FP) rate of 23%. While the AI correctly identified 30 true-positive incidents, there were 6 cases of false negatives (FNs) where violence incidents were missed during the rainy weather suggesting more data in the training dataset related to bad weather. The AI model’s continuous retraining capability ensures its adaptability to various real-world scenarios, making it a valuable tool for enhancing safety and the overall passenger experience in public transport settings. Full article

After a decade of dormancy following the release of Tōhō Studios’ Godzilla: Final Wars (2004), Godzilla and other kaijū burst back onto the scene with Legendary Pictures’ Godzilla (2014). Several American sequels and a television series set in Legendary’s MonsterVerse quickly followed over the next ten years. Meanwhile, Japan’s Tōhō used their radioactive creation’s global success to reignite their own films with Shin Godzilla (2016), an animated trilogy, and Godzilla Minus One (2023). Short-format media like Chibi Godzilla and Godziban also circulated thanks to streaming services. Similarly, Godzilla’s longtime competitor Gamera also emerged from hibernation in an animated series produced by Kadokawa Corporation, Gamera Rebirth (2023). But how do these new installations relate to or depart from their predecessors’ predilection to address environmental concerns? This article continues the ecocritical analysis of kaijū eiga, expanding it to the 2010s and 2020s, as a coda to our duograph Japan’s Green Monsters (2018). This article picks up where we left off, examining the recent releases from an ecocritical standpoint. This analysis reveals that today’s films remain steeped in environmental commentary, but both fragmented and updated for the new concerns of the twenty-first century. Full article

Television series enhance the social visibility of their content, as is the case with Queen Elizabeth II and The Crown. Netflix is the streaming television platform that has turned Peter Morgan’s successful series (2016) into a television icon where the monarch is the main protagonist, taking us on a biographical journey that mixes the historical and the political with fiction. The main character is made to seem more humane and is brought closer to the general public, all of which leads to a transmedia narrative. This research aims to analyze the content of the messages published on Twitter during the days surrounding the Queen’s State funeral in September 2022 and their connection with the series through the hashtag #TheCrown. The topics that have become trends worldwide are quantitatively analyzed, using different digital tools. The sample collected 1,489,279 tweets published during the days from the announcement of the death of Elizabeth II to the day of her funeral (from 8 to 19 September 2022). The results show nodes of connection between different players and linked communities to #TheCrown while offering the traffic generated by the hashtag with different nodes and edges. Full article

Public service media (PSM) are grappling with structural shifts in the audio-visual sector, notably the shift of audiences towards over-the-top (OTT) or subscription video-on-demand (SVOD) services. They have also heavily invested in online platforms, adapting their policies to engage digital users on their video-on-demand (VOD) platforms. This paper assesses PSM policies in Britain, Denmark, and Greece, examining initiatives regarding adaptation to the digital era. It explores whether they implement new strategies to expand their digital reach. Data from policy documents and interviews with BBC, DR, and ERT leading executives inform the analysis. Findings showed varied responses among PSM organisations, influenced by market dynamics and the evolution of broadcasting traditions. Full article

The Nigerian media have, over the years, moved back and forth via all manners of experience of leadership, from military to democratic, until they finally settled into the present democratic governance. Experience from previous regimes exposed them to the vagaries of power and how to cope with them. These traditional news media, newspapers/magazines, radio, and television, were then the major and authentic news sources for Nigerians. The coming of the internet with its social media handles threw the journalists of these media into confusion as the citizens have taken the reigns of news/information peddling from under them, turning them into agents of confirmation and authenticity of information. Ironically, these traditional media, television, radio, and print, have adjusted to online media streaming, thus liberating themselves from the vagaries of temporal and spatial limitedness. Deploying a survey method (opinion poll, OPL) and relying on a purposive sampling technique, the authors purposively selected WhatsApp group platforms (WGP) as the most suitable of the new/social media with access to all manners of news sources. These were used to interrogate how online media/information/news streaming has taken the audience away from traditional media by being on the ‘spot’ at all hours with their avalanche of “Breaking News”. The findings revealed that audiences currently resort to traditional media to confirm the authenticity of news and information carried online in a sort-of-when-in-doubt-watch-the television manner or listen to radio or read the newspapers/magazines. It concludes that online news streaming has become the coveted bride of present-day information and news seekers, albeit an unreliable one. Full article

Due to the ever increasing number of closed circuit television (CCTV) cameras worldwide, it is the need of the hour to automate the screening of video content. Still, the majority of video content is manually screened to detect some anomalous incidence or activity. Automatic abnormal event detection such as theft, burglary, or accidents may be helpful in many situations. However, there are significant difficulties in processing video data acquired by several cameras at a central location, such as bandwidth, latency, large computing resource needs, and so on. To address this issue, an edge-based visual surveillance technique has been implemented, in which video analytics are performed on the edge nodes to detect aberrant incidents in the video stream. Various deep learning models were trained to distinguish 13 different categories of aberrant incidences in video. A customized Bi-LSTM model outperforms existing cutting-edge approaches. This approach is used on edge nodes to process video locally. The user can receive analytics reports and notifications. The experimental findings suggest that the proposed system is appropriate for visual surveillance with increased accuracy and lower cost and processing resources. Full article

In this study, the possibility of applying the hyperspectral imaging (HSI) technique in the Short-Wave InfraRed (SWIR) spectral range to characterize polymeric parts coming from Waste from Electric and Electronic Equipment (WEEE) is explored. Different case studies are presented referring to the identification of (i) plastic flakes inside a mixed waste stream coming from a recycling plant of monitors and flat screens, (ii) different polymers inside a mixed plastic waste stream coming from End-Of-Life (EOL) electronic device housings and trims, (iii) contaminants (i.e., metals) in a mix of shredded plastic particles coming from a recycling line of electrical cables, and (iv) brominated plastics in mixed streams constituted by small appliances (i.e., cathode-ray tube televisions and monitors). The application of chemometric techniques to hyperspectral data demonstrated the potentiality of this approach for systematic utilization for material characterization, quality control and sorting purposes. The experimental findings highlight the feasibility of employing this method due to its user-friendly nature and quick detection response. To increase and optimize WEEE valorization avoiding disposal in landfills or incineration, recycling-oriented characterization and/or quality control of the processed products are fundamental to identify and quantify substances to be recovered. Full article

This article examines the tension between journalistic and entertainment values in live soccer TV commentary from the perspective of German commentators. We situate journalistic and entertainment values within the commentators’ wider understanding of their roles as sports journalists and commentators, looking at a specific type of sports journalist who has different responsibilities from the general sports reporter. We asked how soccer commentators assess the role of journalistic and entertainment values in their work, and what constraints they face, such as how the perceived expectations of their employer affect this assessment. We interviewed 28 TV commentators, one radio commentator, and one expert working for relevant German TV channels and streaming platforms, such as ZDF, Sky, and DAZN. While all interviewees see themselves as companions telling the story of the match, most commentators in the sample value journalistic values over entertainment values, a surprising finding in the hyper-commercialized world of sports television. Well-founded journalistic expertise and soccer knowledge are considered most important. However, this assessment depends on factors such as the broadcaster’s guidelines and the nature of the match. In summary, the role of the commentator is either an ‘objective mediator’ or an ‘emotional entertainer’, but this is a balancing act. Full article

Currently, Korea is undergoing significant local extreme rainfall, which contributes to more than 80% of flood disasters. Additionally, there is an increasing occurrence of such extreme rainfall in small stream basins, accounting for over 60% of flood disasters. Consequently, it becomes imperative to forecast runoff and water levels in advance to effectively mitigate flood disasters in small streams. The Flood Early Warning Framework (FEWF) presents one solution to reduce flood disasters by enabling the forecast of discharge and water levels during flood events. However, the application of FEWF in existing research is challenging due to the short flood travel time characteristic of small streams. This research proposes a methodology for constructing FEWF tailored to small streams using the nomograph and rating curve method. To evaluate the effectiveness of FEWF, a 6-year dataset from the Closed-circuit television-based Automatic Discharge Measurement Technique (CADMT) was utilized. The results indicate that FEWF successfully forecasts discharge and depth during flood events. By leveraging CADMT technology and real-time data, the development of precise and dependable FEWFs becomes possible. This advancement holds the potential to mitigate the consequences of extreme rainfall events and minimize flood-related casualties in small stream basins. Full article

In its meticulous, freewheeling adaptation of the life and work of celebrated poet Emily Dickinson, the television series Dickinson (Apple TV+, 2019–2021) manifests a twenty-first-century disruption of high and low culture afforded by digital media, including streaming video and music platforms. This article argues that the fanciful series models a mixed-media, multimodal aesthetic form that invites a diverse range of viewers to find pleasure in Dickinson’s poetry itself and in the foibles of its author, regardless of their familiarity with the literary or cultural histories of the US American 19th century. Dickinson showcases creator Alena Smith’s well-researched knowledge of the poet and her work, while simultaneously mocking popular (mis)conceptions about her life and that of other literary figures such as Walt Whitman and Sylvia Plath, all set to a contemporary soundtrack. This analysis of Dickinson proposes to bring into conversation shifting boundaries of high and low culture across generations and engage with critical debates about the utility of the popular (and of studies of the popular) in literary and cultural studies in particular. Full article

Indonesia has the third highest number of motorcycles, which means the traffic flow in Indonesia is heterogeneous. Traffic flow can specify its condition, whether it is a free flow or very heavy traffic. Traffic condition is the most important criterion used to find the best route from an origin to a destination. This paper collects the traffic condition for several road segments which are calculated based on the degree of saturation by using two methods, namely, (1) by counting the number of vehicles using object detection in the public closed-circuit television (CCTV) stream, and (2) by requesting the traffic information (vehicle’s speed) using TomTom. Both methods deliver the saturation degree and calculate the traffic condition for each road segment. Based on the experiments, the average error rate obtained by counting the number of vehicles on Pramuka–Cihapit and Trunojoyo was 0–2 cars, 2–3 motorcycles, and 0–1 for others. Meanwhile, the average error on Merdeka-Aceh Intersection reached 6 cars, 11 motorcycles, and 1 for other vehicles. The average speed calculation for the left side of the road is more accurate than the right side, and the average speed on the left side is less than 3.3 km/h. Meanwhile, on the right side, the differences between actual and calculated vehicle speeds are between 11.088 and 22.222 km/h. This high error rate is caused by (1) the low resolution of the public CCTV, (2) some obstacles interfering with the view of CCTV, (3) the misdetection of the type of vehicles, and by (4) the vehicles moving too fast. The collected dataset can be used in further studies to solve the congestion problem, especially in Indonesia. Full article

This paper reported a study based on the application of SWIR (shortwave infrared) spectroscopy to assess the presence of brominated flame retardants (BFRs) in plastic scraps coming from an e-waste stream composed by CRT (i.e., cathode-ray tube) monitors and televisions. An X-ray fluorescence (XRF) analysis was performed on plastic scraps to determine the presence and content of bromine (Br). The presence in plastic waste-flow streams, fed to or resulting from a recycling process, of individuals characterized by high concentrations of Br does not allow their use as secondary raw materials, imposing the need for an ad hoc separation processes. Chemometric methods were adopted for setting up models able to discriminate Br content. In more detail, principal component analysis (PCA) was used as an exploratory tool, while partial least squares (PLS) and locally weighted regression based on PLS regressions (LWRPLS) were used as multivariate regression models to test the ability of the spectra to predict Br content. The LWRPLS, showing an R_p² of about 0.9, demonstrates the ability of this algorithm to establish a good correlation between the spectral signatures of plastic scraps and their Br content. Full article