Smart Tv

The electronics sector faces growing pressure to adopt Circular Economy (CE) principles. This study explores how environmental regulations, technological innovation, and different business approaches shape this transition, aiming to provide a strategic guide. The study analyzed 78 publications from 2012-2025 using a combined literature review and bibliometric analysis from key academic databases. The findings confirm increasing research interest in this area. Environmental regulations are shown to be powerful drivers for sustainable change in the industry. Key strategies identified include designing products for sustainability, using advanced recycling methods, and adopting circular business models, such as offering products as a service. However, significant challenges remain, including inconsistent policies across regions, differences in infrastructure, and the complexity of global supply chains. Research hotspots focus on recycling, resource recovery, and the roles of various stakeholders. Based on these insights, the study proposes a conceptual framework to help develop regionally appropriate circular economy business models for managing electronic waste. This framework offers practical guidance for businesses and policymakers, emphasizing how regulations can spur innovation and why locally adapted solutions are essential for a successful circular transition, moving beyond one-size-fits-all strategies.

Aging is a new step of life with a lot of changes that could be related with physical, cognitive and social frailties. Rather than addressing autonomy and dependency issues for which a variety of assistive technologies has been designed, our aim is to define how ICTs could alleviate elderly loneliness, in order to cope with their social frailty. We make the hypothesis that TV is a good medium for this purpose and we design Smart TV applications dedicated to foster the social interaction among elderly. We adopt a living lab approach, which assure us of an early engagement of the end-users.

The study objective was to seek the favored tenets betwixt mobile-assisted-language-learning (MALL) listening-reading appliances by video-conferencing-technology (VCT) and direct-listening-reading appliances to Madurese-scholar’s second-language (L2) vocabulary-knowledge (VK) listening-reading competencies. The analysis of variance (ANOVA), which produced concurrences, contained 41 scholars in two distinct emplacements amidst a Madurese-scholars preponderance and the different amounts in groups. Several significant conclusions emerged from the current ANOVA analysis. First, the comprehensive implication betwixt MALL listening-reading-appliance and direct-listening-reading-appliance to scholar’s L2-VK listening-reading competencies was not substantiated because it was more than level significant (0.440>0.05). Second, we convened cognizance by direct perception, inside and outside deliberation, and documented it. Third, the cross-examination eventualities of perception-documentation were coded, and research eventualities established the Madurese-scholar higher education framework to pervade case study evidence vacuity that aims to scrutinize: i) the Madurese-scholar teaching-learning peculiarities performance of MALL-VCT-Zoom and Smart-TV multimedia edification; ii) Madurese-scholar interminable concurrences in MALL-VCT-Zoom and Smart-TV; and iii) impediments obtain by MALL-VCT-Zoom and Smart-TV during participation in edification. Irrevocably, concurrence betwixt MALL-VCT-Zoom and smart-TV to scholars’ L2-VK listening-reading competencies were interrelated impacts as Madurese-scholars can learn conveniently with their necessity and concurrently utilize smart-TV or Zoom despite their impediments.

This study critically assesses monetization challenges and growth strategies of Over the Top (OTT) platforms in Indias growing $5B+ market in 2023. The research identifies price sensitivity, fragmented payment systems, and intense competition using a cross-sectional survey of 120 financial experts from the top OTT firms.  The findings display the dominance of hybrid revenue models, and the key to regional content is diversification. The study results demonstrate how revenue strategies depend heavily on regulatory frameworks and economic factors. As a contribution to this academic gap, this research provides actionable insights for OTT policymakers to help monetize Indias heterogeneous digital landscape, fuelling the growth of the Indian OTT market.

Mineral commodities are indispensable for economic growth and development. In the defense industry, telecommunication, renewable energy production, transportation, health sector and many similar fields, various minerals are used more and more widely with the developing technology.
Although mineral commodities are formed in different parts of the world, some commodities are relatively more abundant in various regions. As a result, the production of many raw materials is concentrated in a few countries. China dominates the market for rare earth elements, while Chile is the largest copper producer. South Africa and Russia are the
largest producers of platinum group elements.

Smart TVs offers new possibilities of interaction, due to the peculiarity of the device and the presence of apps. However, more usability studies on Smart TV apps are needed in order to improve the quality of the user interfaces. So, in this paper the authors focus on the interaction between user and Smart TV through remote control. In detail, they test with the users an e-commerce (or more specifically, t-commerce) application on Smart TV.

Embodied conversational agents (ECA's) have become ubiquitous in human-computer interaction applications. Implementing humanlike multimodal behavior in these agents is difficult, because so little is known about the alignment of facial expression, eye gaze, gesture, speech and dialogue act. The current study used the data from an extensive study of human face-to-face multimodal communication for the development of a multimodal ECA, and tested to what extent multimodal behavior influenced the human-computer interaction. Results from a persona assessment questionnaire showed the presence of facial expressions, gesture and intonation had a positive effect on five assessment scales. Eye tracking results showed facial expressions played a primarily pragmatic role, whereas intonation played a primarily semantic role. Gestures played a pragmatic or semantic role, dependent on their level of specificity. These findings shed light on multimodal behavior within and between human and digital dialogue partners.

La importancia del videojuego como fenómeno cultural es cada vez mayor pero no siempre se refleja en el periodismo televisivo, donde predominan los sucesos y el sensacionalismo. El objetivo es analizar la información emitida sobre videojuegos en los informativos españoles de las cadenas generalistas entre abril de 2023 y marzo de 2024. Se ha realizado un análisis de contenido comparativo sobre las publicaciones de TVE, Antena 3, Telecinco y La Sexta tanto en televisión como en sus webs. Los resultados demuestran que la presencia del ocio interactivo en los informativos tradicionales es escasa y negativa al basarse en sucesos, aunque también está presente la importancia del desarrollo y la industria española. El usuario debe consultar sus homólogas en web si quiere encontrar una difusión mayor sobre el videojuego como cultura, alejada de estigmas y más fuentes y géneros periodísticos.

La publicidad en entornos de Digital Signage demanda el enriquecimiento de la aproximación clásica de recomendación orientada a individuos, a través de la entrega de anuncios para un grupo de personas que observa una pantalla pública. Aunque la precisión que se pueda lograr en las recomendaciones es importante, lo es aún más el grado de novedad que puedan percibir los usuarios. Este balance puede obtenerse no solo a través de la mejora de los algoritmos de recomendación, sino también a través de un adecuado esquema de cooperación multi-pantalla. En este sentido, el presente artículo propone una aproximación para la construcción de un sistema de recomendaciones para entornos de Digital Signage soportado en un esquema de cooperación Smart TV-Smartphone.

There are significant digital inclusion disparities between low- and high-income households across countries. Yet, there is a lack of in-depth research about the relationship between digital and social participation in low-income family households, especially in households facing multiple forms of disadvantage and discrimination due to language, cultural or literacy barriers. This article is based on long-term ethnographic research with low-income, migrant family households in the most culturally diverse region of Australia—Western Sydney. We find that household digital inclusion is perceived as necessary and important by parents—but also as a burden that has social, financial and emotional dimensions. We also find that a lack of targeted and culturally informed digital and social inclusion services constrain what digital connection can achieve for families. We argue that under these conditions, equitable digital inclusion cannot be achieved.

As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a usability perspective. However, these methods are mainly manual, and the potential of automated model-based testing methods for usability testing purposes has not yet been fully explored. In this paper, we propose an approach to test the usability of Smart TV apps based on the automated generation of a Smart TV user interaction model from an existing app by a specialized automated crawler. By means of this model, defined user tasks in the Smart TV app can be evaluated automatically in terms of their feasibility and estimated user effort, which reflects the usability of the analyzed app. This analysis can be applied in the context of regular users and users with various specific needs. The findings from this model-based automated analysis approach can be used to optimize the user interface of a Smart TV app to increase its usability, accessibility, and quality.

By incorporating the digitalization and distribution of information processes in open and collaborative networks, the media have brought about a cultural change in the ways to produce and consume producing and consuming content. The figure of the “prosumer” emerges, putting into crisis the linear and vertical relationship of the traditional mass media and the relationship with brands and their stakeholders.
In this new context, this article proposes to reflect on the new possibilities available for the brand to manage its image, based on understanding this new culture from three main characteristics: participatory culture, media convergence and collective intelligence as essential dimensions from which to develop strategies to strengthen the brand image. The theoretical foundations of this reflection are based on cultural convergence, brand management and complexity.
Keywords: Image; Identity; Brand; Culture; Convergence; Digitization.

This paper reports on an ethnographic study that examined smart TV use in lowincome migrant households in Australia. We find that the smart TV is used by migrant families for diverse forms of social and cultural participation. In addition, we find that YouTube-which is often accessed using the smart TV-is reshaping family media practices. We argue that while digital inclusion scholarship has focussed on access to and use of mobile phones, laptops and computers, the smart TV, perhaps more than any other device in the home, enables digital inclusion through intergenerational media engagement. This paper presents insights for policymakers and offers a new area for investigation for digital inclusion and media scholars.

The current rate at which natural resources are being extracted to meet the demands of the growing population is not sustainable for future generations. The linear economy approach based on the take-make-dispose ideology is being replaced by the circular economy (CE) approach to manage the demand and create a balance between the available resources. The concept of circular economy is believed to be very relevant for E-products and E-waste as it strives to design out the waste by better products, practices, and business models. This paper aims to study how CE can be applied in E-waste management with the implementation of various concepts like the 3Rs, reverse logistics, and urban mining. As the study is focused on India, the current E-waste management practices and legislation support have been discussed in this paper. The paper further explains the complexities prevalent in the E-waste management system in India due to the presence of a huge informal sector primarily responsible for the collection and disposal of E-waste. Finally, the paper present certain strategies that could be helpful to overcome the challenges in the successful implementation of the Circular economy in E-waste management in India.

This paper introduces a approach to emotion recognition from speech signal using SVM as a classifier. Speech Emotion Recognition (SER) is a current research area in the field of Human Computer Interaction (HCI) with wide range of applications. The speech features such as, Mel Frequency cepstrum coefficients (MFCC) and Mel Energy Spectrum Dynamic Coefficients (MEDC) are extracted from speech utterance. The Support Vector Machine(SVM) is used as classifier to classify different emotional states such as anger, happiness, sadness, neutral, fear. The Berlin emotion database and Hindi emotion database are used for extracting the features from emotional speech .wav files. The recognition rates by implemented SVM are 62% and 71.66% for Berlin database and Hindi database respectively. The recognition rates by LIBSVM using RBF for Berlin database are 99.39% for cost value c=8. The recognition rates by LIBSVM using RBF kernel function for Hindi database are 78.33%.The accuracy rates by LIBSVM using Linear RBF kernel function for German independent files is 68.902%.

The paradigm shift around the Mobile phenomenonthe explosion of mobile online users-, Google's response to that trend and the what such changes entail further for website developers are issues around which this paper is built. In the first part of this paper we made an analysis of the literature in order to clarify certain terminology and trends of Mobile Web. Further we illustrate the practical aspects of implementing these technological issues for a faculty institutional website (Faculty of Economics and Business Administration within the West University of Timisoara). In the last part, we analyzed statistical data collected during last five years of operation of that website, emphasizing compliance with the trends in the field worldwide.

James Michael Walker (2023) found that several structural, technological, trade and behavioral changes on the one hand and the move towards Sustainability on the second hand are transforming the 21st century into a Metal-centric and Mineral-centric Economy and Civilization mainly due to the growing demand of  " Critical Raw Materials (CRMs).
However, the concentration of Mineral and Metal Resources on the one hand and the current acceleration of the Era of Systemic Risks with its associated high risk of Supply Chain Disruptions on the second hand could prevent the Metal-centric and Mineral-centric Economy to bear all the fruits expected. For example, any further shortage of SRMs, Supply chains disruptions, high risk of systemic risks  and deglobalization could prevent the current hift away from the Oil-centric and Human's Driver Cars, Planes, Trains, Ships and Trucks to the Clean-Electric and Fully Autonomous Cars, Planes, Trains, Ships and Trucks to bear all the fruits expected.
Unfortunately, the challenges of the  Metal-centric and Mineral-centric Economy are not limited to the spatial concentration of the SRMs. In fact, in fact, despite the prioritization of the  Geophysical Methods and Remote Sensing Exploration Methods, the prospection and exploration of the Strategic Raw Materials (SRMs) have remained  " Cost-producing, Risky and Time-consuming Activities ". Furthermore, major environmental, social, geopolitics, Spatial and structural challenges faced by the Mining Industries have made it easier for the Mining Industry to be :
- One of the Top Waste Generators Industry of the World.
- One of the Most Unsafe Industry of the World.
- One of the Industry with a ‘ Relative High Carbon Footprint, Water Footprint and Resource Footprint.
Fortunately, the current rise of the AI-driven Innovation and Robotics-driven Automation Era is revolutionizing the Mining Industry mainly throughout the fixation of the challenges of the sector. In fact, AI-driven Technologies are improving the Operational Efficiency Management (OEM) of corporates and enhancing the resource management. Furthermore, several studies have found that AI plays a pivotal role in driving the high-quality development of  the geological exploration industry (Yin Yan, 2022; Yin Yan, 2022; Yu Yang, 2018; Li Senrong. , 2022 and Shi Shuaihang, 2022). By so doing, the effective Data-driven Management is stimulating the rise of Smarter Mining that beside the above benefits will help make transparent and faster decision-making.
However, the  rise of the AI-driven Innovation and Robotics-driven Automation Era not only has stimulated the rise of the  Smarter Mines but also is accelerating the automation of the whole value chain of the Mining Industry mainly throughout the rise and use of the Clean-Electric and Fully Autonomous Mining Trucks.
By so doing, the simultaneous use of AI-powered Technologies,  Clean-Electric and Fully Autonomous Mining Trucks and Airborne Electromagnetic System  (AES) are improving the exploration and extraction of surface, near-surface and underground mineral resources on the one hand and helping get access to cheap and abundant Strategic Raw Materials (SRMs) that in turn could guarantee the Energy Revolution needed for the 21st century.
Fortunately, " Capitalisation Effects of the AI-driven Technologies" are not limited only to the Energy Revolution and the improvement of the Operational Effectiveness Management (OEM) and Data-driven Management. In fact, Wearable, Geolocation and AI-driven Technologies are also helping the Mining Industry to provide a " Labor Safety and Healthy Environment " for its employees.
Furthermore, the AI-driven Technologies are also reducing the Carbon Footprint of the Mining Industry and helping it become Zero Dust Pollution sector. Moreover, AI-driven Technologies are also helping build a " Labor Safety and Healthy Environment, Resource-saving, Waste-saving, Time-saving Mining Industry ".
As a result, the simultaneous improvement of the Operational Effectiveness Management (OEM) and Data-driven Management on the one hand and the use of AI-powered Technologies,  Clean-Electric and Fully Autonomous Mining Trucks and Airborne Electromagnetic System  (AES) on the second hand are helping build a " Cost-effective, Personalized, Smart, Connected, Clean, Green, Labor Safety and Healthy Environment, Automated, Resource-saving, Waste-saving, Time-saving Mining Industry " that will dramatically reduce the  Ecological Footprint (EF) of the sector, guarantee the Energy Revolution of the 21st century and minimize the risk of the " Supply Chain Disruption ".  Furthermore, the AI-driven Technologies will also fix the current talent shortage of the  Mining Industry.

Key Words : Sustainability; Metal-centric and Mineral-centric Economy and Civilization; Critical Raw Materials (CRMs); The Concentration of Mineral and Metal Resources; Era of Systemic Risks; Supply Chain Disruptions; Mineralization; Geological Structure; Concentration of The Lithium Resources; Resource Nationalism; Geopolitics Tensions; Deglobalization Process; Top Waste Generators Industry; Ecological Footpring (EF); Water-stress Hotspots; Cost-effective, Personalized, Smart, Connected, Clean, Green, Labor Safety and Healthy Environment, Automated, Resource-saving, Waste-saving, Time-saving Mining Industry.

Depression is a concerning issue then can even lead to suicide. So, depression screening should be done mor efficiently. Recent studies indicate that EEG can be used for depression screening. It has the potential to deal with the barriers of traditional screening methods. A machine learning-based method for screening depression among young adults using wireless EEG is proposed in this study. EEG signal was recorded using a wireless 14 channel EEG headset from 32 young adults. For initial screening PHQ9 was used to select depressed and depression control participants. Among the participants 19 were identified as depressed and 13 were identified as depression control. The EEG data was filtered into 6 frequency bands then Hjorth Activity, Hjorth Mobility, Hjorth Complexity, Shannon entropy, and Log energy entropy features were extracted. For classification Cubic SVM with 5-fold cross validation was used. Using the Beta band (12-30Hz) the model can predict depressed and control individual 97.22% accurately with the Precision of 97.2%, NPV of 97.3%, Sensitivity of 98.2%, Specificity of 95.8%, and F1 score 0.970, which is also the highest among other frequency bands. So, it can be concluded that the EEG based depression screening can detect depression among young adults and the findings can complement the findings from questionnaire-based depression screening.

James Michael Walker (2023) found that several structural, technological, trade and behavioral changes on the one hand and the move towards Sustainability on the second hand are transforming the 21st century into a Metal-centric and Mineral-centric Economy and Civilization mainly due to the growing demand of  " Critical Raw Materials (CRMs).
However, the concentration of Mineral and Metal Resources on the one hand and the current acceleration of the Era of Systemic Risks with its associated high risk of Supply Chain Disruptions on the second hand, could prevent the Metal-centric and Mineral-centric Economy to bear all the fruits expected. In fact, Brown et al. (2020) found that the large variety of raw materials in the USA and China result from the massive area of both countries, amounting to over 9 million km2 because the wide range of latitude and longitude determines a broad climatic spectrum for those countries, which is conductive to the conditions for the formation of raw materials in the past and now (Lieder, Marek, 2022). Furthermore, Mann et al. (2005) found that it is worth emphasizing that the United States is situated on active tectonic plates, e.g., the San Andreas Fault, which runs through western and southern California, which is characterized by rich sources of oil and natural gas. Moreover, in the case of  China, Song et al. (2018) found that the most active places (for CRMs) result from 3 tectonic faults: Webschuan, Pengguan, Baichuan, causing cyclical shocks (4 000 movements in 15 years), contributing to mineralization and filling in the resulting void spaces in rocks.
Since then, for example , Geological Structure of nations and cities are explaining the spatial concentration of the Lithium resources. In fact, US Geological Survey (2021) found that Lithium is widely used for energy storage (Li-ion rechargeable batteries, around 70 % global lithium consumption) in ceramics, glass and lubricating grease.
However, despite this global use of Lithium, US Geology Survey (USGS) (2022) found that owing to continuing exploration, identified lithium resources have increased substantially worldwide and total about 89 million tons.
Identified lithium resources in the United States-from continental brines, geothermal brines, hectorite, oilfield brines, pegmatites, and searlesite-are 9.1 million tons.
Identified lithium resources in other countries have been revised to 80 million tons.
Identified lithium resources are distributed as follows : Bolivia, 21 million tons ; Argentina, 19 million tons ; Chile, 9.8 million tons ; Australia, 7.3 million tons ;  China, 5.1 million tons ;  Congo (Kinshasa), 3 million tons ; Canada, 2.9 million tons ;  Germany, 2.7 million tons ; Mexico, 1.7 million tons ;  Czechia, 1.3 million tons ; Serbia, 1.2 million tons ; Russia, 1 million tons ; Peru, 880, 000 tons ; Mali, 700, 000 tons ;  Zimbabwe , 500, 000 tins ; Brazil, 470, 000 tons ;  Spain, 300, 000 tons, Portugal, 270, 000 tons, Ghana, 130, 000 tons, Austria, 60, 000 tons ; and Finland, Kazakhstan and Namibia, 50, 000 tons each. Unfortunately, in the current context of acceleration of the Era of Systemic Risks with its associated  Supply Chain Disruptions on the one hand and the concentration of the Lithium resources on the second hand could put the world at the greater risk of shortage of Lithium.
Doing so could prevent the current  shift away from the Oil-centric and Human's Driver Cars, Planes, Trains, Ships and Trucks to the Clean-Electric and Fully Autonomous Cars, Planes, Trains, Ships and Trucks to bear all the fruits expected.
The spatial concentration of other Strategic Raw Materials (SRMs) such as Coal, Steel, Copper, Gold, Oil, Gas among others could also prevent the Metal-centric and Mineral-centric Economy to bear all the fruits expected. In fact, the spatial concentration of the SRMs can put the world at greater risk of the risk of  ' Resource Nationalism' that in turn can put the world at a greater risk of Deglobalization Process, Supply Chain Disruption, Shortage of SRMs and Geopolitics Tensions that can end to the WWIII.
Unfortunately, the challenges of the  Metal-centric and Mineral-centric Economy are not limited to the spatial concentration of the SRMs. In fact, major environmental, social, geopolitics,Spatial and structural challenges faced by the Mining Industries have made it easier for the Mining Industry to be :
- One of the Top Waste Generators Industry of the World.
- One of the Most Unsafe Industry of the World.
- One of the Industry with a ‘ Relative High Carbon Footprint, Water Footprint and Resource Footprint.
Regarding the Carbon Footprint, McKinsey (2020) found that the Mining Industry is currently responsible for 4 to 7 percent of greenhouse gas (GHG) emissions globally. The Scope 1 and Scope 2 CO2 emissions from the sector (those incurred through mining operations and power consumption, respectively) amount to 1 percent, and fugitive-methane emissions from coal mining are estimated at 3 to 6 percent.
Since then, it became relevant to focus on the Input-Output Analysis regarding the Carbon Footprint of the Mining Industry. In fact, the World Population Review considers coal as the ‘ dirtiest’ fossil fuels as it is known to emit significant amounts of greenhouse gases and other pollutants when burned. The burning of coal in power plants accounts for 30 % of global warming, and while countries pledged to reduce their coal consumption during the COP 26 summit held in the UK, there is still work to do .
However, WEF (2022) found that steel is the largest emitting manufacturing sector, generating 7 % of all man-made emissions. More than 85 % of its energy consumption comes from fossil fuels. Moreover, not only the whole sector is one of the Top emitter of the world but also its Top MNCs are also among the Top polluters of the world.This sad performance is mainly due to the three ' Corrosive Environments ' in which the Mining operations take place.
Unfortunately, the existence of the ' Three Corrosive-intensive Environments ' on the one hand and the relative high Carbon Footprint of the Mining Industry on the second hand put its employees and the whole world at a greater risk Urban-related Diseases including Chronic Diseases, Obesity, Suicide, Mental Health and Behavioral Disorders and Addictions that are the major driving causes of mortality in the U.S. and Worldwide.
Since then, Vaz et al. (2022) have concluded that the mineralogical and chemical composition, as well as mass and surface area of dust particles have direct impacts on health. 
However, the ecological challenge of the Mining Industry is not limited to the relative high Carbon Footprint only. In fact, the Mining Industry has a relative high Water Footprint. Furthermore, while the Mining Industry is one of the most waste generators sector, its Resource Footprint continues to be also one of the highest of the world. Key Words : Structural, Technological, Trade and Behavioral Changes; Sustainability; Metal-centric and Mineral-centric Economy and Civilization; Critical Raw Materials (CRMs); The Concentration of Mineral and Metal Resources; Era of Systemic Risks; Supply Chain Disruptions; Mineralization; Geological Structure; Concentration of The Lithium Resources;  Identified lithium resources in the United States; Concentration of  other Strategic Raw Materials (SRMs) such as  Gold, Coal, Copper, Oil and Zinc Resources; Energy Crisis; High rate of inflation; Food and Supply Chain Crises; Resource Nationalism; Geopolitics Tensions; Deglobalization Process; Major Environmental, Social, Geopolitics, Spatial and Structural Challenges of the Mining Industry;  Metal-centric and Mineral-centric Economy; Top Waste Generators Industry; Most Unsafe Industry; Ecological Footpring (EF); Carbon Footprint; Water Footprint; Resource Footprint; Urban-related Diseases; Corrosion Management System (CMS); Water-stress Hotspots; Unsafe Industry.

A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with Humane-Machine interaction (HMI) has advanced machine intelligence. An emotion precise HMI is designed by integrating speech processing and machine learning algorithm which is sculpted to formulate an automated smart and secure application for detecting emotions in a household as well as in commercial application. This project presents a study of distinguishing emotions by acoustic speech recognition (ASR) using K-means nearest neighbor (K-NN), a machine learning (ML) technique. The most significant paralinguistic information obtained from spectral features is presented by ASR i.e. by using Mel frequency cepstrum coefficient (MFCC). The most important processing techniques methods include feature extraction, feature selection, and classification of emotions. A customized dataset consisting of speech corpus, simulated emotion samples in the Sanskrit language is used to classify emotions in different emotional classes i.e. happy, sad, excitement, fear, anger and disgust. The emotions are classified using a K-NN algorithm over 2 separate models, based on the soft and high pitch voice. Model 1 and 2 achieved about 72.95% and 76.96% recognition

Software agents and assistants, together with their adequate visual representations, lead to so-called social user interfaces, incorporating natural language interaction, context awareness and anthropomorphic avatars. Today's challenge is to build a suitable visualization architecture for anthropomorphic conversational user interfaces, and to design believable and appropriate faceto-face interactions, including human attributes, such as emotions. An integrated approach to these tasks is presented.

More and more popular, Smart TVs and set-top boxes open new ways for richer experiences in our living rooms. But to offer richer and novel functionalities, a better understanding of the multimedia content is crucial. If many works try to automatically annotate videos at object level, or classify them, we think that investigating the emotions through the use of digital analysis and processing techniques will allow great TV experience improvements. With our work, we propose a temporal saliency detection approach capable of defining the most exciting parts of a video that will be of the most interest to the users. To identify the most interesting events, without performing their classification (in order to be independent from the video domain), we compute a time series of arousal (excitement level of the content), based on audiovisual features. Our goal is to merge this preliminary work with user emotions analysis, in order to create a multimodal system, allowing to bridge the gap between users' needs and multimedia contents.

This paper presents the principal phase of extraction and recognition of the basic emotions in the Arabic speech applied to five emotional states were taken into effect; neutral, sadness, fear, anger and happiness. Emotional speech database REGIM_TES was created and evaluated to provide all practical experiences of extraction. The database described in section 3 has been recorded and processed in this vein. The selected descriptors in our study are; Pitch of voice, Energy, MFCCs, Formant, LPC and the spectrogram. Descriptors showed the importance of the Arabic language on the physiological events and the influence of culture on emotional behavior. Results performed in this work showed that pooling together features extracted at different sites indeed improved classification performance. A comparative study between the kernel functions has enabled us to promote the RBF kernel SVMs multiclass classifier performing the classification phase.

Collection of patient-reported outcomes (PROs) remotely and their usage in the clinical workflow provide an improvement on both patient’s quality of life and cancer care. However, adoption of collecting PROs into the clinical workflow is rare, and existing works still have a lot of issues providing a holistic approach. This paper offers enhancements in the process of collecting PROs by utilization of conversational systems that still provide quite a new but promising way to collect PROs remotely with spoken interaction. Our proposed system provides an interoperability with Fast Healthcare Interoperability Resources (FHIR) server by using a multimodal sensing network (MSN) prepared for the project PERSIST. We introduce components of multimodality while collecting PROs with the help of the mHealth App and Open Health Connect (OHC) platform. As a result, chatbots and 3D embodied conversational agents (ECA) were prepared to interact with the cancer patients in 5 different languages. The...

As a result of the convergence of different services delivered over the internet protocol, internet protocol television (IPTV) may be regarded as the one of the most widespread user interfaces accepted by a highly diverse user domain. Every generation, from children to the elderly, can use IPTV for recreation, as well as for gaining social contact and stimulating the mind. However, technological advances in digital platforms go hand in hand with the complexity of their user interfaces, and thus induce technological disinterest and technological exclusion. Therefore, interactivity and affective content presentations are, from the perspective of advanced user interfaces, two key factors in any application incorporating human-computer interaction (HCI). Furthermore, the perception and understanding of the information (meaning) conveyed is closely interlinked with visual cues and non-verbal elements that speakers generate throughout human-human dialogues. In this regard, co-verbal behavior provides information to the communicative act. It supports the speaker's communicative goal and allows for a variety of other information to be added to his/her messages, including (but not limited to) psychological states, attitudes, and personality. In the present paper, we address complexity and technological disinterest through the integration of natural, human-like multimodal output that incorporates a novel combined data-and rule-driven co-verbal behavior generator that is able to extract features from unannotated, general text. The core of the paper discusses the processes that model and synchronize non-verbal features with verbal features even when dealing with unknown context and/or limited contextual information. In addition, the proposed algorithm incorporates data-driven (speech prosody, repository of motor skills) and rule-based concepts (grammar, gesticon). The algorithm firstly classifies the communicative intent, then plans the coverbal cues and their form within the gesture unit, generates temporally synchronized co-verbal cues, and finally realizes them in the form of human-like co-verbal movements. In this way, the information can be represented in the form of both meaningfully and temporally synchronized co-verbal cues with accompanying synthesized speech, using communication channels to which people are most accustomed.

Background This paper addresses the escalating global issue of electronic waste (e-waste), a consequence of the burgeoning demand for electronic products coupled with their transient lifespan. The rapid accumulation of e-waste is a significant concern, especially in the context of climate change, necessitating a detailed analysis of current management strategies and the development of sustainable management practices. The intricate relationship between e-waste and climate change is emphasized, illustrating how improper disposal and recycling practices substantially contribute to greenhouse gas emissions. Main body of the abstract A meticulous analysis is conducted to critique the prevailing e-waste management strategies, identifying their shortcomings and the urgent need for enhancement and globalization of these protocols. The paper argues for a fortified, universal approach to e-waste management to address the deficiencies in current methodologies. A set of strategic, sustainable ...

In machine interaction with human being is yet challenging task that machine should be able to identify and react to human non-verbal communication such as emotions which makes the human computer interaction become more natural. In present research area automatic emotion recognition using speech is an essential task which paid close attention. Speech signal is a rich source of information and it is an attractive and efficient medium due to its numerous features of expressing approach & extracting emotions through speech is possible. In this paper emotions is recognized through speech using spectral features such as Mel frequency cepstrum coefficient prosodic features like pitch , energy and were utilized & study is carried out using K-Nearest Neighbor classifiers and Gaussian mixture model classifier which is used for detection of six basic emotional states of speaker's such as anger ,happiness , sadness , fear , disgust and neutral using Berlin emotional speech database.

In machine interaction with human being is yet challenging task that machine should be able to identify and react to human non-verbal communication such as emotions which makes the human computer interaction become more natural. In present research area automatic emotion recognition using speech is an essential task which paid close attention. Speech signal is a rich source of information and it is an attractive and efficient medium due to its numerous features of expressing approach & extracting emotions through speech is possible. In this paper emotions is recognized through speech using spectral features such as Mel frequency cepstrum coefficient prosodic features like pitch , energy and were utilized & study is carried out using K- Nearest Neighbor classifiers and Gaussian mixture model classifier which is used for detection of six basic emotional states of speaker's such as anger ,happiness , sadness , fear , disgust and neutral using Berlin emotional speech database.

Fecha de recepción del artículo: 01/09/2016 Fecha de aceptación definitiva: 08/10/2016 RESUMEN Redes sociales, como Facebook y Twitter, y aplicaciones móviles, como Periscope, Snatch, WhatsApp, entre otras, son algunas de las vías de comunicación y de acceso a la información en auge en los últimos tiempos, tanto para los usuarios en general, como para los profesionales de la información. Los avances tecnológicos y las innovaciones derivadas fundamentalmente de la web 2.0 han sumado nuevas pantallas a los medios de comunicación tradicionales, de modo que el periódico ya no solo se lee, sino que ahora puede verse y oírse, al tiempo que la televisión, además de verse y oírse, también se lee. A todo ello se suma la movilidad y portabilidad, tan demandada por los usuarios en la actualidad, y en los que la pantalla del móvil tiene un protagonismo e influencia destacada, sobre todo, de la mano de las redes sociales. En esta aportación se describe cuál es la producción y el consumo de noticias de actualidad que se realiza a partir de la información proporcionada por las principales cadenas de televisión generalista en España a través de la red social más móvil, Twitter.

Fecha de recepción del artículo: 01/09/2016 Fecha de aceptación definitiva: 08/10/2016 RESUMEN Redes sociales, como Facebook y Twitter, y aplicaciones móviles, como Periscope, Snatch, WhatsApp, entre otras, son algunas de las vías de comunicación y de acceso a la información en auge en los últimos tiempos, tanto para los usuarios en general, como para los profesionales de la información. Los avances tecnológicos y las innovaciones derivadas fundamentalmente de la web 2.0 han sumado nuevas pantallas a los medios de comunicación tradicionales, de modo que el periódico ya no solo se lee, sino que ahora puede verse y oírse, al tiempo que la televisión, además de verse y oírse, también se lee. A todo ello se suma la movilidad y portabilidad, tan demandada por los usuarios en la actualidad, y en los que la pantalla del móvil tiene un protagonismo e influencia destacada, sobre todo, de la mano de las redes sociales. En esta aportación se describe cuál es la producción y el consumo de noticias de actualidad que se realiza a partir de la información proporcionada por las principales cadenas de televisión generalista en España a través de la red social más móvil, Twitter.

Responsive Web Design (RWD) is a design which focuses on responsively fitting in whatever device the website is accessed from. It involves writing code for all possible screen sizes and bundling them together. Hence when the website is accessed, the whole bundle alongside the code for all screen sizes are downloaded to the user's device and acts responsively when the browser window is resized, or the mobile device is rotated to portrait or landscape orientation. RWD can provide a far better user experience than the other designs because it primarily focuses on the user experience. Despite the bundle size being large, this method has proved to be robust in providing a better user experience and has evolved with evolution of web technologies. Latest CSS Media Queries make it possible to even target devices with limited accuracy. CSS Media Queries form the fundamentals of RWD because it is the most used way of targeting devices with various screen sizes.

In adaptivity, the interface of the device automatically adjusts and assists the user. The adaptive user interfaces can adapt their activities by monitoring user status, the state of the system, and the current situation according to the adaptation strategy. Usually, the intensity of adaptation is measured in effectiveness, efficiency, and satisfaction to analyze the smartphone’s adaptive features. The adaptive features of light-emitting diode (LED) notifications, voice commands, face recognition, screen rotation, kid mode, drive mode, night mode, Swift Keyboard, s-health, gesture recognition, and fingerprint are selected for both iOS and Android platforms. Task completion within a specific time frame is used to measure effectiveness and efficiency, while satisfaction is calculated using the after-scenario questionnaire (ASQ). A total of 550 users are involved in the experimentation. The usability evaluation is measured for smartphone features. The effectiveness of adaptive features...

In adaptivity, the interface of the device automatically adjusts and assists the user. The adaptive user interfaces can adapt their activities by monitoring user status, the state of the system, and the current situation according to the adaptation strategy. Usually, the intensity of adaptation is measured in effectiveness, efficiency, and satisfaction to analyze the smartphone’s adaptive features. The adaptive features of light-emitting diode (LED) notifications, voice commands, face recognition, screen rotation, kid mode, drive mode, night mode, Swift Keyboard, s-health, gesture recognition, and fingerprint are selected for both iOS and Android platforms. Task completion within a specific time frame is used to measure effectiveness and efficiency, while satisfaction is calculated using the after-scenario questionnaire (ASQ). A total of 550 users are involved in the experimentation. The usability evaluation is measured for smartphone features. The effectiveness of adaptive features...

We propose a network and visual quality aware N-Screen content recommender system. N-Screen provides more ways than ever before to access multimedia content through multiple devices and heterogeneous access networks. The heterogeneity of devices and access networks present new questions of QoS (quality of service) in the realm of user experience with content. We propose, a recommender system that ensures a better visual quality on user's N-screen devices and the efficient utilization of available access network bandwidth with user preferences. The proposed system estimates the available bandwidth and visual quality on users N-Screen devices and integrates it with users preferences and contents genre information to personalize his N-Screen content. The objective is to recommend content that the user's N-Screen device and access network are capable of displaying and streaming with the user preferences that have not been supported in existing systems. Furthermore, we suggest a ...

In this paper, we propose a user social network and device capabilities aware recommender system to personalize content to the current device of a user. The proposed recommender system presents some novelties that are not provided in existing collaborative and content-based filtering. First of all, we incorporate the user social network data to find similar users not only using the conventional similarities approach but also based on the social importance of the users. Furthermore, it considers the user access device to ensure that the device is capable to stream and display. We present an approach that considers user experienced items, users direct trust and the capability of contributing to the content network for finding similarity. We improve the accuracy, precision and recall of the conventional recommender system. The proposed system can be used anywhere; however, we mainly focus on IPTV content personalization.

The Internet is gradually expanding to many new devices, in addition to its original native environment that was the Personal Computer. This wave started with mobile devices and as we enter the Internet of Things era, connectivity is possible from cars to light switches. One of the first devices, to follow mobiles, is the Television. Connectivity and two-way interaction on the TV device has in fact started even in the first days of the medium, but had failed to make it widely available, due to technological limitations of the past. Now, this has changed, with the Smart TV devices that can utilize the fast internet connections that are available in most developed countries. However, even though the technology and devices are now widely available there are still challenges in order to make the vast Internet and web content available in the Smart TVs. These challenges, have a familiar resemblance to what happened a few years ago, when internet connectivity was introduced on the mobile phone. Although, it was "feasible" to access any webpage from your mobile device, the experience for the user was often very frustrating, due to many factors, that derived from the fact that the web was designed for large screens and mice of the desktop computers, not the small touch screens and limited hardware of the phone. Nonetheless, these obstacles were successfully overcome, by introducing techniques and methodologies (e.g. Responsive

The crimes using computers is growing with rapid speed. As computer crimes have hit up to a high mark, the tools used to fight such crimes is budding faster. In today's world the use of Digital Forensics have also become vital. Digital Forensics is a step-by-step process of scientific methods and techniques to investigate crime obtained from digital evidences. For investigating the digital evidence there are many Digital Forensic tools which are used to investigate digital crimes by identifying the digital evidences. The study results in giving the solutions for Digital Forensic tools for investigators looking to spread out their serviceability in using Digital Forensic tools.

Este libro tiene su origen en el interés personal de un investigador por reflexionar y debatir del alcance y trascendencia de las narrativas transmedia en la vida cotidiana de las personas. A partir de un caso concreto, pero de alcance mundial, el fenómeno Marvel, se medita sobre la aportación que realiza el espectador, el prosumidor, el fan al universo de ficción, no sólo en forma de contenidos aislados, sino también en la generación de puntos de encuentro. En ellos se pone en común un sentido de la historia consumida, pero también de la vida en general, lo que contribuye, en el fondo, a la creación de una comunidad más humana e integrada.

El presente estudio versa sobre el efecto del mensaje propagandístico en los estudiantes Universitarios Argentinos en 2015 tomando en cuenta la actualidad del tema dadas las elecciones presidenciales de Octubre. La finalidad del mismo es de tipo Aplicada, ya que la información obtenida sirve para tomar acciones, establecer políticas o estrategias según sea el caso. El proyecto se encuadra como de tipo Cuantitativo, ya que sigue una secuencia lógica donde los conceptos son de tipo operativos, se administra un instrumento común a todos con características de encuesta. La Muestra tendrá un n=69 (estudiantes) de tipo No probabilístico. La profundidad del estudio es de tipo Correlacional, ya que la principal utilidad es saber cómo se puede comportar un concepto o una variable al conocer el comportamiento de otras variables relacionadas. El alcance temporal del mismo, es Transversal ya que se realizará en un breve lapso de tiempo. Justifica este estudio, la necesidad de comprender un fenómeno que es totalmente actual y se suma a otros que permiten comprender el rol de las redes sociales en la sociedad, pero este a diferencia de los otros, toma como unidad de análisis a los argentinos. Entre los principales resultados el 84,1% de los participantes reconoce que se ha modificado la forma en la acceden a la información. El 94% de la gente que es afín a un candidato valorarán mejor las acciones y propaganda de su candidato que del resto, un 63,70% lo hará de forma consistente, mientras un 36,30% no será consistente. El 69,6% suele mirar los afiches y carteles en la vía pública. El 69,6% al leer noticias online, lee los comentarios. Valores como la honestidad, coherencia y ética son valorados por 95,7% de las personas. La relación de las personas con la propaganda es de tipo negativa, es considerada desagradable, Inútil, Sin Valor y Falsas, aunque se reconoce que aportan información. La principal vía de información son los periódicos Online para el 84% de las personas, seguido por los canales de televisión abierta (62,3%) y Facebook (56,5%). De los 3 principales medios informativos, 2 son a través de Internet. Lo más valorado del medio, es la capacidad de análisis que tienen de la información, la seriedad y la confiabilidad.

In this paper we propose a modular structure to define communication acts with verbal and nonverbal elements inspired in the SAIBA model. Our modular structure is a conceptual interpretation of the functional features of a multimodal interaction platform we have developed, with an ...

Software agents and assistants, together with their adequate visual representations, lead to so-called social user interfaces, incorporating natural language interaction, context awareness and anthropomorphic avatars. Today's challenge is to build a suitable visualization architecture for anthropomorphic conversational user interfaces, and to design believable and appropriate faceto-face interactions, including human attributes, such as emotions. An integrated approach to these tasks is presented.

El presente ensayo ofrece una reflexión amplia sobre la problemática de las culturas de pantalla, a partir de la recuperación de algunos insumos analíticos desarrollados principalmente en los estudios comunicacionales durante las últimas tres décadas. Siendo aún demasiado vastos los términos de tal objeto de análisis, abordamos específicamente los actos de transición de una forma de consumo de la televisión tradicional hacia las nuevas experiencias asociadas a las narrativas transmediáticas. Nos referimos en este segundo caso a la disponibilidad técnica, a los recursos consistentes en la construcción incluso virtual y efímera de comunidades interpretativas, a los contenidos ya presentes, y a los códigos abiertos de consumo. Si bien asumimos una extensión generalizada del anecdotario en las acciones reseñadas, nos remitimos con alguna frecuencia al caso mexicano a fin de ganar concreción. Añadimos un apartado con un breve razonamiento sobre el capitalismo contemporáneo a la luz del desarrollo de las culturas de pantalla y proponemos un modelo de observación como síntesis de ciertas tradiciones comunicológicas.

In human-to-human communication, speech signals carry rich emotional cues that are further emphasized by affect-expressive gestures. In this regard, automatic synthesis and animation of gestures accompanying affective verbal communication can help to create more naturalistic virtual agents in human-computer interaction systems. Speech-driven gesture synthesis can map emotional cues of the speech signal to affect-expressive gestures by modeling complex variability and timing relationships of speech and gesture. In this paper, we investigate the use of continuous affect attributes, which are activation, valence and dominance, for speech-driven affective synthesis and animation of arm gestures. To this effect, we present a statistical framework based on hidden semi-Markov models (HSMM), where states are gestures and observations are speech-prosody and continuous affect attributes. The proposed framework is evaluated considering four distinct HSMM structures which differ by their emission distributions. Evaluations are performed over the USC CreativeIT database in a speaker-independent setup. Among the four statistical structures, the conditional structure, which models observation distributions as prosody given affect, achieves the best performance under both objective and subjective evaluations.

OTT video services, which were formerly seen as a luxury, are now commonplace.
Consumers in India are adjusting to it in greater and greater numbers. While
homegrown rivals like Hotstar and JIO Cinema have gained footing, global streaming
goliaths like Netflix and Amazon Prime have steadily expanded their market share in
India. The emergence, advantages, and possibilities of streaming services in India are
investigated in this article using research.
Additionally, we discuss the various OTT services, as well as their drivers of growth,
technological foundation, audience makeup, content, censorship, and anticipated future
changes.
If we go back a few years, the growth rate of OTT platform users has been rising up
to the lockdown during the Covid-19 epidemic, and this development is based on the
significant technological advancements that enable OTT providers to offer high-quality
services. The content displayed on our nearby screens online. OTT companies spend a
lot of money producing content rather than just relying on their library.
A few of the numerous variables include new technology, falling data prices, and
faster internet at home and online. devices including tablets, computers, and phones.
Modern smart TVs are built with entertainment in mind and make it simple to watch
video from OTT sources. This article is a component of an innovative approach for
comprehending Indian consumer preferences and characteristics.

The objective of this research is to explore and identify Smart TV user experience (UX) factors over different time periods employing multiple methods so as to overcome the weakness of a single study approach. To identify the effect of contextual dimensions on the Smart TV UX, we conducted empirical studies exploiting different methods of think-aloud and diary method under two usage conditions: laboratory and real-life in the participants' residence. The factors identified through each study were integrated into a single set and further refined through peer review resulting in a final set of 19 UX factors. Metrics for these 19 UX factors were generated and used in an online survey, in which over 300 Smart TV users participated. The empirical evidences from each study suggest that the UX factors vary with respect to product temporality. The findings indicate practical implications for Smart TV manufacturers, marketing managers, application developers, and service providers.