Multimedia Computing

Drug-drug interactions (DDIs) can cause adverse reactions or reduce the efficiency of a drug. Using computers to predict DDIs is now critical in pharmacology, as this reduces risks, improves drug outcomes and lowers healthcare costs. Clinical trials are slow, expensive, and require a lot of effort. The use of artificial intelligence (AI), primarily in the form of machine learning (ML) and its subfield deep learning (DL), has made DDI prediction more accurate and efficient when handling large datasets from biological, chemical, and clinical domains. Many ML and DL approaches are bio-inspired, taking inspiration from natural systems, and are considered part of the broader class of biomimetic methods. This review provides a comprehensive overview of AI-based methods currently used for DDI prediction. These include classical ML algorithms, such as logistic regression (LR) and support vector machines (SVMs); advanced DL models, such as deep neural networks (DNNs) and long short-term memory networks (LSTMs); graph-based models, such as graph convolutional networks (GCNs) and graph attention networks (GATs); and ensemble techniques. The use of knowledge graphs and transformers to capture relations and meaningful data about drugs is also investigated. Additionally, emerging biomimetic approaches offer promising directions for the future in designing AI models that can emulate the complexity of pharmacological interactions. These upgrades include using genetic algorithms with LR and SVM, neuroevaluation (brain-inspired model optimization) to improve DNN and LSTM architectures, ant-colony-inspired path exploration with GCN and GAT, and immune-inspired attention mechanisms in transformer models. This manuscript reviews the typical types of data employed in DDI (pDDI) prediction studies and the evaluation methods employed, discussing the pros and cons of each. There are useful approaches outlined that reveal important points that require further research and suggest ways to improve the accuracy, usability, and understanding of DDI prediction models.

Within the science schooling community and beyond, see "maniplo-spatial arty" carried out by learners as a requisite configuration of science education. Enquiries have been made by some erudite about its effectiveness as a teaching and learning strategy. This erudition explored the effectiveness of maniplo-spatial work by analyzing a sample of 25 idiosyncratic science lessons involving maniplo-spatial work in Nigerian Junior Secondary Schools (JSS III) and Senior Secondary Schools (SSSIII). Statistics took the form of observational field notes and recorded interviews with teachers and learners. The analysis used a model of effectiveness based on work of Millar et al., Otobo and Arku, and Tiberghien. The teachers' enthusiasm in this lesson was predominantly on emerging learners' substantive scientific knowledge, rather than on evolving learners' understanding of scientific enquiry procedures. Maniplo-spatial work was generally effective in the receipt of learners to do what is intended with physical objects, but much less effective in getting them to use little evidence that mental (cognitive) challenges of linking observables to ideas is recognized by those who designed maniplospatial activities for the lesson. Tasks fused explicit strategies to help learners to make such links, or were presented in schoolrooms in ways that reflected the size of the learning demand of the maniplo-spatial tasks, and categorizing those that require specific support for learners' discerning and learning in order to be effective.

Η χρήση της τεχνολογίας για τη συμπερίληψη ατόμων με αναπηρία στην τέχνη, στην επικοινωνία, στην εκπαίδευση και στον πολιτισμό αποτελεί σημαντική πρακτική. Η εργασία αυτή πραγματεύεται το ερώτημα των δυνατοτήτων πρόσβασης και συμπερίληψης ατόμων με αναπηρία σε καλλιτεχνικές και εκπαιδευτικές εμπειρίες μέσα από τη χρήση πολυμεσικών διαδραστικών εφαρμογών και Τεχνητής Νοημοσύνης. Σκοπός της εργασίας είναι να αναδείξει τα οφέλη της χρήσης τεχνολογιών στη συμπερίληψη ατόμων με αναπηρία, αλλά ταυτόχρονα να επισημάνει τις προκλήσεις και τα περιθώρια βελτίωσης και εξέλιξης των μέσων με δεδομένες τις ποικίλες ανάγκες και ικανότητες διαφορετικών ομάδων κοινού. Η συζήτηση επεκτείνεται στην αισθητική ανάλυση και αποτίμηση των εκάστοτε προσαρμογών που συμβάλλουν στη συνολική εμπειρία. Μέσα από παραδείγματα πολυμεσικής τέχνης, εκθεμάτων και εκπαιδευτικών πολυμεσικών εφαρμογών, αναδεικνύεται ότι τα πολυμέσα και η Τεχνητή Νοημοσύνη έχουν διανοίξει πολλές διόδους προς την υποστήριξη της πρόσβασης και συμπερίληψης ατόμων με αναπηρία, πράγμα που συμβάλλει στον εμπλουτισμό της εμπειρίας για όλους.

As financial technology and digital transaction volumes expand globally, the limitations of centralized, monolithic architectures for real-time fraud detection have become critically apparent. Traditional systems struggle to maintain low-latency inference under high-throughput conditions, often resulting in delayed interventions and increased financial losses. This paper investigates the scalability, resilience, and latency optimization of a unified real-time fraud detection platform leveraging Apache Kafka for high-throughput event streaming and Kubernetes for the dynamic orchestration of microservices. Furthermore, the architecture integrates edge-enabled distributed Artificial Intelligence (AI) models to push inference capabilities closer to the data source, thereby decentralizing computational loads. Utilizing a rigorously generated synthetic dataset of simulated global financial transactions, this study conducts an empirical analysis of system performance across varied volumetric stress tests. The methodology isolates and measures end-to-end latency, throughput stability, and resource utilization during sudden transaction spikes. The findings suggest that coupling Kafka's partitioned log architecture with Kubernetes' horizontal pod autoscaling significantly enhances fault tolerance and throughput. Moreover, deploying lightweight machine learning models at the edge reduces central cluster bandwidth consumption and decreases inference latency by offloading preliminary anomaly detection. This research provides a foundational blueprint for engineering scalable, next-generation fraud detection ecosystems capable of adapting to complex, real-time adversarial threats.

This qualitative systematic review explores the role of Information and Communication Technology (ICT) in fostering 21st-century skills, critical thinking, creativity, collaboration, communication, digital literacy, problem-solving, and responsible citizenship among adolescents, with a primary focus on the Indian educational context. Drawing on thematic analysis of 68 scholarly articles, policy documents, and international reports published between 2005 and 2024, the study synthesises global evidence while foregrounding India's unique socioeconomic , infrastructural, and cultural realities. Findings confirm that ICT acts as a powerful catalyst for higher-order cognitive development, multimodal communication, collaborative learning, creative expression, and self-regulated behaviour when integrated through constructivist and inquiry-based pedagogies. Platforms such as DIKSHA, SWAYAM, virtual labs, and EdTech applications demonstrate significant potential to enhance adolescent motivation, cognitive flexibility, and real-world skill application. However, persistent challenges, including infrastructural deficits, the rural-urban and socioeconomic digital divides, inadequate teacher TPACK, gendered restrictions, linguistic barriers, and weak digital citizenship education, severely limit transformative outcomes, particularly in government and rural schools. The study concludes that realising ICT's full potential requires universal connectivity, equity-focused infrastructure, pedagogy-centred teacher development, curriculum-wide integration, inclusive design, and robust digital citizenship education. Strategic, inclusive, and ethically guided ICT integration is essential for equipping India's 253 million adolescents with the competencies needed for personal growth, democratic participation, and global competitiveness in the 21st-century knowledge society.

Mobile network operators are experiencing a tremendous increase in data traffic due to the growing popularity of bandwidth-intensive video services. This challenge can be faced either by boosting the capacity of the network infrastructure, or by means of offloading traffic from the backhaul and core network and serving contents from distributed cache servers close to the users. Network operators can extend the coverage of traditional CDNs by making usage of caching locations much closer to the users than traditional CDNs. Additionally, network operators can optimize the caching and delivery of contents by exploiting the complete knowledge of their network for designing a cost-effective infrastructure able to achieve both improved user satisfaction and cost savings. This article provides thoroughly justified design principles for a highly distributed operator-owned CDN while focusing on four key aspects: the optimal location of cache servers, mechanisms for request routing, content replica placement, and content outsourcing and retrieval.

Orang tua memiliki tanggung jawab yang sangat penting dalam membentuk sikap dan tingkah laku anaknya. orang tua dapat, membentuk tingkah laku anaknya dengan melakukan pengawasan dari kegiatan sehari -harinya, seperti kemana dia pergi beserta lokasi mana saja yang telah dikunjungi oleh anak. namun terkadang dari setiap orang tua tidak dapat mengontrol anaknya yang pergi kemana saja dikarenakan kesibukan beserta terkadang anak yang ditanya bisa saja berbohong. Untuk membantu dalam mengawasi anak dalam kegiatan sehari -harinya terkhususnya lokasi yang di datanginya, maka dibutuhkan suatu sistem monitoring lokasi atau pemantau posisi anak berdasarkan smartphone android yang digunakannya dengan pemanfaatan teknologi Global Positioning System (GPS) sebagai alat pelacak. Dengan adanya sistem monitoring lokasi anak ini, dapat membantu orang tua dalam mengetahui lokasi -lokasi yang telah dikunjungi anaknya dan ditampilkan dalam bentuk interface Google Maps sehingga membantu pengawasan orang tua terhadap anaknya secara realtime.

The integration of technology in teaching computing is crucial in preparing students for the digital age. This paper discusses the importance of incorporating technology in computing education, highlighting its benefits, challenges, and best practices. We argue that technology integration enhances student engagement, improves learning outcomes, and equips students with essential skills for the 21st-century workforce.

Images shared on social media help crisis managers in terms of gaining situational awareness and assessing incurred damages, among other response tasks. As the volume and velocity of such content are really high, therefore, real-time image classification became an urgent need in order to take a faster response. Recent advances in computer vision and deep neural networks have enabled the development of models for real-time image classification for a number of tasks, including detecting crisis incidents, filtering irrelevant images, classifying images into specific humanitarian categories, and assessing the severity of the damage. For developing real-time robust models, it is necessary to understand the capability of the publicly available pretrained models for these tasks. In the current state-of-art of crisis informatics, it is under-explored. In this study, we address such limitations. We investigate ten different architectures for four different tasks using the largest publicly av...

Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response purposes, the research has been mostly focused on analyzing only the text modality in the past. In this paper, we propose to use both text and image modalities of social media data to learn a joint representation using state-of-the-art deep learning techniques. Specifically, we utilize convolutional neural networks to define a multimodal deep learning architecture with a modality-agnostic shared representation. Extensive experiments on real-world disaster datasets show that the proposed multimodal architecture yields better performance than models trained using a single modality (e.g., either text or image).

Although the National ICT Policy for Education in Namibia was adopted in 2005, immediately followed by the National ICT Policy Implementation Plan in 2006, no known studies have been undertaken so far to evaluate its implementation. This has made it difficult to ascertain the ICT/mobile learning readiness of teachers and learners. This study analyzed the perceptions of learners and teachers towards mobile learning in Namibian High Schools. A mixed method approach, comprising a baseline survey and interviews with randomly sampled learners and teachers from three high schools in the Hardap region of Namibia was undertaken. Both qualitative and quantitative data was solicited on learner and teacher perceptions on mobile learning. The survey questionnaire, which was based on modified version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model to make the questions suitable to the context of mobile learning was used. Unstructured interviews were used to supplement the questionnaire where gaps were identified. The data collected was then analyzed for descriptive and inferential statistics using Statistical Package for Social Sciences (SPSS).The results among others showed that even though that majority of teachers and learners in Namibia own mobile devices which can be used for mobile learning, introduction of mobile technology in schools would only work in an environment where there is a sound ICT infrastructure. Affordable internet access and skilled ICT teachers are also a challenge.

Traditionally, sign languages used by the deaf can be learned from teachers, books or video tapes. Digital multimedia together with CD ROM technology now enables production of interactive textbooks and dictionaries for sign languages on personal computers. The paper presents the key technological and contents requirements for learning to sign from a point of view of deaf as well as hearing persons. The technological requirements are then measured up with the current Multimedia PC Level 2 specifications. An alternative representation for sign language based on edge images derived from sequences of video frames is proposed to achieve higher video compression ratios. The fulfillment of contents requirements is demonstrated by an example of Sign Language Dictionary and Tutor.

This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties such as bubble-point pressure and oil formation volume factor is important in the primary and subsequent development of an oil field. In this work, we develop Sensitivity Based Linear Learning method prediction model for PVT properties using two distinct databases, while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. Empirical results from simulation show that the newly developed SBLLM based model produced promising results and outperforms others, particularly in terms of stability and consistency of prediction.

Content Delivery Network (CDN) is a large distributed system of servers deployed in multiple data centers on the Internet. Its main goal is to serve requests from users providing high availability and performance. It also reduces the system failure risk providing redirection to many replica servers. It can provide load balancing between servers, avoiding network bottlenecks and, therefore, ensuring greater performance and QoE (Quality of Experience) to the end user. One of the critical issues involving CDN networks is the algorithm used to choose the replica server, because it directly influences the performance and scalability of the network. In this paper, an algorithm for choosing the best replica server is proposed. The proposal is compared in simulation against other algorithms in the literature. Finally, we show the effectiveness of the proposed algorithm to improve the choice of the best replica server in CDN.

Sport video is an important video genre. Content-based sports video analysis attracts great interest from both industry and academic fields. A sports video is characterised by repetitive temporal structures, relatively plain contents, and strong spatio-temporal variations, such as quick ...

Stress is the body and mind disorders caused by the changes and demands of life. Personality is a typical pattern in a person to think, act, and said in response to an event. Students involved in the organization get more stressors when compared with students who are not involved organizations. The aim of this research is to know the comparison of stress level between personality type melancholy, choleric, phlegmatic, and sanguine at the students involved organization in TKK SMFK UNSRAT. The samples in this research was taken with an total sampling technique which is 41 peoples who met the inclusion criteria. The study design used is cross sectional study and the data collected from respondents using a questionnaire DASS and personality type questionnaire by Florence Littauer. The result of Pearson Chi Square test founded p value= 0,301 > α = 0.05 so that there is no correlation between stress level and personality type Hippocrates-Galenus. Based on the results of the data analysis with One Way Anova, known F value= 2,352 with a significance= 0.088 (p> 0.05), this indicates that there is no difference in stress level between personality type melancholy, choleric, phlegmatic, and sanguine to the students involved organization TKK SMFK UNSRAT. Recommendations for further research is expected to examine other factors that may cause differences in the level of stress.

Efficiency and Network time is important in wireless sensor network. Is is possible to improve the performance of network by using Zigbee. The main features of Zigbee are low cost, low data rate, low power consumption. We are using this feature to increase the strength of small batteries of the node in the network. We are using tree structure to transmit the data packet from zigbee end device to destination. Ad-hoc on demand distance vector routing and Shortcut tree routing are compared, Number of nodes with respect to performance parameters Average energy, Delay, Packet delivery ratio, packet dropped, Residual energy, throughput. Simulation in 2.34 version is carried out and ESTR is better than AODV in this study. The performance of the multi-package delivery ratio of ESTR can also be relatively small compared to AODV. The end-to-end performance of STR delays is not good compared to AODV. So we propose the new system ASTR (Advanced Shortcut Tree Routing. The main goal is the improv...

In this literature, we present a slightly different approach to multimedia processing while leveraging the modern container and container orchestration technology to cluster computing using AWS known cloud platform. This approach optimizes multimedia processing over cloud clusters using modern container and container orchestration technology. In this approach, we first outlined the multimedia components and developed the architecture for our multimedia processing technology using modern container and container orchestration technology over cloud clusters, then we integrated and deployed the framework over AWS platform. The result of our work provided a new technique for optimizing large scale multimedia processing solutions which demonstrated the power of modern container and container orchestration technology to cluster computing using known cloud platform AWS. We simulated our multimedia processing model and generated optimized results.

Generation Networks (MNGN). It adds value to the mobile services and applications by integrating mobile network resources, such as location, billing and authentication. This is achieved by enabling a third party access to network resources. In previous work we have presented a testbed to be used as platform for testing mobile application prior to actual deployment. We have chosen a novel IMS based MObile Mass EXamination (MOMEX) system to showcase the benefit of designing an IMS based mobile application. We identify two aspects essential to of the application namely security threats and delay analysis. In this paper we identify MOMEX security threats and suggest strategies to mitigate system vulnerabilities. We then evaluate the performance of MOMEX system in terms of delay and security threats and vulnerabilities. The results presented show system performance limitation and tradeoffs.

❑Aset digital hadir dalam berbagai format, masing-masing dengan karakteristik dan penggunaan yang berbeda. ❑Memahami format aset digital adalah langkah penting dalam mengelola aset secara efektif. ❑Materi ini akan membahas kategori, format, dan contoh aset digital, serta aplikasinya dalam MAD.

This paper studies the problem of estimating geographical locations of images. To build reliable geographical estimators, an important question is to find distinguishable geographical clusters in the world. Those clusters cover general geographical regions and are not limited to landmarks. The geographical clusters provide more training samples and hence lead to better recognition accuracy. Previous approaches build geographical clusters using heuristics or arbitrary map grids, and cannot guarantee the effectiveness of the geographical clusters. This paper develops a new framework for geographical cluster estimation, and employs latent variables to estimate the geographical clusters. To solve this problem, this paper employs the recent progress in object detection, and builds an efficient solver to find the latent clusters. The results on beach datasets validate the success of our method.

ABSTRACT: The system presented in this article was developed with the aim of generating coherent summaries and transcripts by identifying relevant events in multimodal videos from multiple sources, mitigating computational costs and information overload, and promoting inclusive access to information in an assisted way. The system was developed using the Python and HTML programming languages, the Pycharm IDE and libraries such as Moviepy, Flask and SpeechRecognition. From the practical tests carried out on this web system, it was possible to observe the automatic generation of a reliable summary, the respective video extracted, for example, from a Uniform Resource Locator - URL, as well as a digital sign language interpreter avatar implemented and operating on the same results web page, enabling people with deafblindness to consume the content of a video or a collection of videos. This system also enabled textual translation, local storage and automatic electronic sending of digital files resulting from the summarization, with one file being sent in mp4 format and another in txt format to multiple email addresses, thus contributing to the mass production and dissemination of useful knowledge content and promoting social inclusion and the democratization of knowledge.

This article is dedicated to the features and importance of using multimedia technologies in education and their role in the formation of sociocultural competence via comparative qualitative research methods. As a result, computer technologies increase the efficiency of education, they help to increase student motivation, reveal the potential for learning foreign languages and ultimately contribute to the formation of sociocultural competence. In conclusion, the use of computer technologies in the process of teaching foreign languages, is an indispensable resource for the formation of sociocultural competence.

High efficiency video coding (HEVC) is the newest video codec to increase significantly the coding efficiency of its ancestor H.264/Advance Video Coding. However, the HEVC delivers a highly increased computation complexity. In this paper, a coding unit partitioning pattern optimization method based on particle swarm optimization (PSO) is proposed to reduce the computational complexity of hierarchical quadtree-based coding unit partitioning. The required coding unit partitioning pattern for exhaustive partitioning and the rate distortion cost are efficiently considered as the chromosome and the fitness function of the PSO, respectively. To reduce the computational time, the cellular automata-based (CA) rule based time limit is used in order to find out the best possible modes of operation. Compared to the current state of the art algorithms, this scheme is computationally simple and achieves superior reconstructed video quality (12% increase in PSNR compared to existing methods) at less computational complexity (overall delay by 40%), Increasing the bandwidth and reducing the errors..

Fallstudie zu PORTERS generischen Wettbewerbsstrategien im Kontext nachhaltigen Wirtschaftens I Zusammenfassung PORTERS Konzept der generischen Wettbewerbsstrategien hat den Status eines Managementklassikers und ist vielen Entscheidern in der Unternehmenspraxis bekannt. Aufgrund seines großen Bekanntheitsgrades und seiner Einfachheit eignet sich dieses Konzept als Grundlage für Strategiediskussionen mit Führungskräften. In der Fachliteratur zum strategischen Management ist die Wahl generischer Wettbewerbsstrategien im Kontext nachhaltiger Entwicklung diskutiert worden. In der vorliegenden Fallstudie wird eine Strategieempfehlung für einen Kartoffelchipsproduzenten auf Basis der generischen Wettbewerbsstrategien entwickelt und erörtert, wie sich diese Strategieempfehlung durch flankierende Maßnahmen unterstützen lässt. Zudem werden die Chancen der erfolgreichen Realisierung einer Hybridstrategie diskutiert. In der Fallstudie ist beabsichtigt, die Anwendung von PORTERS Konzept der generischen Wettbewerbsstrategien zu erörtern, jedoch erhebt die Fallstudie nicht den Anspruch, effektives und/oder effizientes Management darzustellen.

Much progress has been made in the field of sentiment analysis in the past years. Researchers relied on textual data for this task, while only recently they have started investigating approaches to predict sentiments from multimedia content. With the increasing amount of data shared on social media, there is also a rapidly growing interest in approaches that work "in the wild", i.e. that are able to deal with uncontrolled conditions. In this work, we faced the challenge of training a visual sentiment classifier starting from a large set of user-generated and unlabeled contents. In particular, we collected more than 3 million tweets containing both text and images, and we leveraged on the sentiment polarity of the textual contents to train a visual sentiment classifier. To the best of our knowledge, this is the first time that a cross-media learning approach is proposed and tested in this context. We assessed the validity of our model by conducting comparative studies and evaluations on a benchmark for visual sentiment analysis. Our empirical study shows that although the text associated to each image is often noisy and weakly correlated with the image content, it can be profitably exploited to train a deep Convolutional Neural Network that effectively predicts the sentiment polarity of previously unseen images.

Multimedia menurut etimologi atau asal usul bahasanya adalah berasal dari kata  multi  (latin)  “multus”  yang  berarti  banyak  atau  lebih  dari  satu.  Dan  media (latin)  berasal  dari  kata  latin  medius  yang  merupakan  bentuk  jamak  dari  kata “medium”, yang berarti perantara atau pengantar. media adalah segala sesuatu yang “medium”, yang berarti perantara atau pengantar. media adalah segala sesuatu yang pikiran, perhatian, perasaan dan juga minat serta perhatian dari siswa sedemikian rupa, sehingga di dalam proses mengajar dapat berlangsung dengan efektif dan juga efisien sesuai dengan apa yang diharapkan. Sehingga Multimedia adalah gabungan dari beberapa unsur yaitu teks, grafik, suara, video dan animasi yang menghasilkan presentasi yang menakjubkan. Multimedia juga mempunyai komunikasi interaktif yang tinggi. Bagi pengguna komputer multimedia dapat diartikan sebagai informasi komputer yang dapat disajikan melalui audio atau video, teks, grafik dan animasi. Jadi,  multimedia  adalah  suatu  kombinasi  data  atau  media  untuk  menyampaikan suatu informasi sehingga informasi itu tersaji dengan lebih menarik.

Multimedia menurut etimologi atau asal usul bahasanya adalah berasal dari kata  multi  (latin)  “multus”  yang  berarti  banyak  atau  lebih  dari  satu.  Dan  media (latin)  berasal  dari  kata  latin  medius  yang  merupakan  bentuk  jamak  dari  kata “medium”, yang berarti perantara atau pengantar. media adalah segala sesuatu yang digunakan sebagai penyalur pesan dan mengirim pesan, sehingga dapat merangsang pikiran, perhatian, perasaan dan juga minat serta perhatian dari siswa sedemikian rupa, sehingga di dalam proses mengajar dapat berlangsung dengan efektif dan juga efisien sesuai dengan apa yang diharapkan. Sehingga Multimedia adalah gabungan dari beberapa unsur yaitu teks, grafik, suara, video dan animasi yang menghasilkan presentasi yang menakjubkan. Multimedia juga mempunyai komunikasi interaktif yang tinggi. Bagi pengguna komputer multimedia dapat diartikan sebagai informasi komputer yang dapat disajikan melalui audio atau video, teks, grafik dan animasi.

In this paper we are interested in the elaboration of an approached solution to the sum coloring problem (MSCP), which is an NP-hard problem derived from the graphs coloring (GCP). The problem (MSCP) consists in minimizing the sum of colors in a graph. Our resolution approach is based on an hybridization of a genetic algorithm and a local heuristic based on an improvement of the maximal independent set algorithm given by F.Glover [4].

Educational Technology became vital in the teaching and learning process, particularly during the Covid-19 era. However, a host of challenges associated with the integration of ET in the teaching and learning process were unearthed. This study sought to establish the extent to which Educational Technology was integrated into the teaching and learning of Design-based subjects at the diploma level during the COVID-19 pandemic and to explore strategies that can be adopted to improve the quality of teaching and learning in teacher education in times of crises. The study employed a qualitative approach methodology utilising a case study research design. A sample of five lecturers and twenty students was purposively selected. Data were analysed thematically. Results revealed that lecturers have adequate content knowledge about the design-based subjects which they teach but do not have sufficient technological and pedagogical knowledge. The study recommends in-service training of lecturers to effectively use educational technology in teaching processes.

Kebutuhan akan informasi yang cepat, akurat, dan tepat waktu merupakan suatu hal yang mutlak pada era yang serba cepat ini. Keterlambatan dalam menyajikan informasi yang dibutuhkan akan menyebabkan informasi tersebut tidak relevan lagi bagi penggunanya. Sistem Informasi Administrasi Pasien Rawat Jalan dan Rawat Inap Pada Puskesmas Tanjung Raja berangkat dari visi misi dan tujuan dari Puskesmas Tanjung Raja tersebut. Yaitu terwujudnya pelayanan yang baik kepada masyarakat. Sistem Informasi ini akan memudahkan proses-proses tersebut, sehingga pengolahan data-data yang ada akan lebih cepat dan akurat serta meberikan kemudahan staff puskesmas dalam menjalankan tugasnya. metode yang digunakan yaitu RAD (Rapid Application Development (RAD) adalah metode model proses pengembangan perangkat lunak yang bersifat incremental terutama untuk waktu pengerjaan jangka pendek. Desain aplikasi menggunakan sistem UML (Unified Modelling language) yaitu terdiri dari use Case Diagram, Class Diagram, Acti...

Sachet is a Network based Intrusion Detection System developed at IIT Kanpur. It monitors the network traffic to detect any unwanted attempts to compromise the security of the network by malicious users. Recently an Intrusion Prevention functionality was also added to it. IPS monitors network traffic inline and prevent intrusions by dropping the malicious packets before they reach the actual host. In this thesis, we are adding two functionalities needed to enhance the utility of the system. One of major technique to prevent an IDS/IPS from detecting an attack is through splitting the signature into two packets of a TCP Connection. As the IDS/IPS checks for signature in each packet individually it would not be able to detect this attack. However, on the host machine these packets would be reassembled and a stream of data is available to the application. Hence, it would get compromised. We are adding a TCP Reassembly module to our IPS so that it can detect those attacks which would have went though undetected. We are also adding a Web based Graphical User Interface to the system so that a network administrator can monitor the IDS from a remote machine. Currently, the information about the alerts (and the status of network and nodes) can be monitored only from the server machine. I take this opportunity to express my sincere gratitude towards my thesis supervisor, Dr. Dheeraj Sanghi, for his continuous support and guidance. He provided me with many valuable ideas throughout the thesis period. I also thank Prabhu Goel Research Center and Army Technology Board for partially supporting my thesis. I would also like to thank all the faculty members of Department of Computer Science for imparting invaluable knowledge on me. I would also like to thank my project partner, Chinmay Asarawala, for his cooperation and innovative suggestions. I would also like to thank my colleagues, Vinaya Natarajan, Devendar Bureddy, Satyam Sharma and Dungara Ram Choudhary for their suggestions. I would like to thank all my classmates too for making my stay at IITK enjoyable. Finally, I would like to thank my parents for their constant support and encouragement in all my endeavours.

Le travail réalisé tout au long de cette thèse n'a été possible qu'avec l'aide et le soutien de nombreuses personnes. Je profite de l'occasion qui m'est donnée ici pour leur exprimer toute ma gratitude. Je tenais en premier lieu à remercier vivement Jean-Jacques Pansiot, mon directeur de thèse, pour son encadrement et sa disponibilité. Merci Jean-Jacques de m'avoir fait partager tes connaissances, ton expérience et ta bonne humeur. Ce fut un réel plaisir de travailler pendant ces années sous ta direction. Je souhaite remercier chaleureusement Dominique Grad et Benoît Hilt, mes coencadrants de thèse, pour m'avoir prodigué de précieux conseils et pour m'avoir apporté de nombreuses idées au cours de ce travail. Je remercie Messieurs Guy Leduc, Thomas Noël, Vincent Roca et François Spies pour l'intérêt qu'ils ont porté à mes travaux en acceptant de faire partie de mon jury de thèse. Je tiens également à remercier toute l'équipe Réseaux et Protocoles du LSIIT. En particulier les doctorants présents et passés, avec qui j'ai beaucoup appris, partagé et apprécié travailler. Merci à Alexander, Damien, Émil, Julien, Julien, Mickaël, Pascal et Romain, pour votre disponibilité et votre gentillesse. Enfin, je remercie également ma famille et mes amis qui m'ont toujours soutenu, encouragé et sans qui je n'écrirais pas ces lignes. i vi independently of the reception rate. To deal with these problems, we propose a sequencer and its API, which assure that the more important the data is, the lower its sending rate is. And thus acquired by the majority of receivers. Experiments have shown the sequencer optimal performances insuring that a receiver subscribed to N% of the source rate obtains the most important N% of the applicative data. Moreover, applications can use this API without knowing anything about the dynamic layering used by M2C. Therefore, this API is easy to use, which makes it suitable for various kind of applications. Indeed, we have demonstrated the usefulness of the API and the underlying congestion control protocol by implementing two experimental applications : a file transfer [MU-TUAL] and a video streaming software [MUST].

We present an interactive application that enables users to improve the visual aesthetics of their digital photographs using spatial recomposition. Unlike earlier work that focuses either on photo quality assessment or interactive tools for photo editing, we enable the user to make informed decisions about improving the composition of a photograph and to implement them in a single framework. Specifically, the user interactively selects a foreground object and the system presents recommendations for where it can be moved in a manner that optimizes a learned aesthetic metric while obeying semantic constraints. For photographic compositions that lack a distinct foreground object, our tool provides the user with cropping or expanding recommendations that improve its aesthetic quality. We learn a support vector regression model for capturing image aesthetics from user data and seek to optimize this metric during recomposition. Rather than prescribing a fully-automated solution, we allow user-guided object segmentation and inpainting to ensure that the final photograph matches the user's criteria. Our approach achieves 86% accuracy in predicting the attractiveness of unrated images, when compared to their respective human rankings. Additionally, 73% of the images recomposited using our tool are ranked more attractive than their original counterparts by human raters.

This work is overview in field of dynamic and static QR-coding. The main attention is paid to peculiarities of using dynamic and static QR codes. The paper proposes classification of QR-codes. Key code characteristics that you should pay attention to when selecting and writing code have also been identified. A comparison of dynamic and static QR-coding is given.

Pemakaian VR dalam desain interior berpotensi membawa perubahan bagaimana para profesional merancang ruang. Kemajuan ini memungkinkan desainer untuk menggali lebih dalam detail ruang interior, bahkan sebelum kontruksi dimulai. Artikel ini membahas bagaimana VR memungkinkan visualisasi yang lebih baik dan kolaborasi yang lebih efektif. Melalui artikel ini diharapkan dapat memberikan pemahaman yang lebih dalam tentang dampak positif dan potensi penggunaan teknologi VR dalam desain interior bangunan di era modern, serta menginspirasi para professional industry dan pemilik property untuk menjelajahi dan mengadopsi inovasi ini dalam upaya menciptakan ruang interior yang lebih fungsional, menarik dan efisien.

Recent advances in deep learning have expanded possibilities to generate music, but generating a customizable full piece of music with consistent long-term structure remains a challenge. This paper introduces MusicFrameworks, a hierarchical music structure representation and a multi-step generative process to create a full-length melody guided by long-term repetitive structure, chord, melodic contour, and rhythm constraints. We first organize the full melody with section and phrase-level structure. To generate melody in each phrase, we generate rhythm and basic melody using two separate transformer-based networks, and then generate the melody conditioned on the basic melody, rhythm and chords in an auto-regressive manner. By factoring music generation into sub-problems, our approach allows simpler models and requires less data. To customize or add variety, one can alter chords, basic melody, and rhythm structure in the music frameworks, letting our networks generate the melody accordingly. Additionally, we introduce new features to encode musical positional information, rhythm patterns, and melodic contours based on musical domain knowledge. A listening test reveals that melodies generated by our method are rated as good as or better than human-composed music in the POP909 dataset about half the time.

Stališča učiteljev do uporabe sodobne tehnologije pri pouku matematike Povzetek: Raba sodobne tehnologije pri pouku matematike prinaša številne prednosti tako za učitelje kot za učence. Te morajo spoznati in prepoznati učitelji, saj je uspešna raba tehnologije pri pouku odvisna predvsem od njih. V okviru reformiranja sistema vzgoje in izobraževanja ter s tem prenove učnih načrtov je treba upoštevati novosti in mednarodne trende, med katerimi je tudi digitalizacija družbe. Učitelji bodo morali slediti spremembam v procesu izobraževanja ter v poučevanje vključevati sodobno tehnologijo na tak način, da bo njena raba pedagoško in didaktično premišljena. Zato bi bilo treba zagotoviti strokovna izobraževanja, s katerimi bodo učitelji bolj kompetentni in samozavestni pri vključevanju sodobne tehnologije v pouk. Toda ali so učitelji pripravljeni na tovrstne spremembe? Z raziskavo, ki jo predstavljamo v prispevku, smo poskušali ugotoviti stališča učiteljev glede rabe dinamične geometrije pri pouku matematike ter raziskati dejavnike, ki vplivajo na oblikovanje njihovih stališč. Anketirali smo 117 osnovnošolskih učiteljev, ki so v šolskem letu 2022/2023 poučevali matematiko v 2. ali 3. vzgojno-izobraževalnem obdobju osnovne šole. Ugotovili smo, da je pripravljenost za vključevanje sodobne tehnologije v pouk pri bolj izkušenih učiteljih manjša v primerjavi z manj izkušenimi učitelji ter da se učitelji zavedajo, da je slovenski učni načrt za matematiko treba spremeniti v smislu, da bo podpiral rabo računalniško podprte tehnologije pri pouku.