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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Ioannis Tsilikas Stavros Deligiannidis Aris Tsirigotis Georgios N. Tsigaridas Adonis Bogris Charis Mesaritakis Dept. Physics National Technical University of Athens Zografou Athens Greece Dept. Information and Communication Systems Engineering University of the Aegean Karlovasi Samos Greece Dept. Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9798350345995

In this work we combine a high flow cytometry experimental setup and a 10Kframe/sec capable neuromorphic event-based camera, followed by lightweight machine learning schemes, thus allowing the simultaneous imaging and real-time classification of test particles, moving at a speed of 0.8m/sec with an accuracy of 97.6%. The key advantage of the utilized microscopy system, is the use of an event-based camera, generating spiking events, triggered by pixel's contrast changes. This bio-inspired operation, contrary to conventional CMOS cameras [1], alleviates bandwidth constraints and can significantly boost frame-rate capabilities, thus capturing high speed events. Following this paradigm, medical imaging modalities, where the detection and analysis of fast-moving particles is a necessity, such as high-flow cytometry, can greatly proliferate from the proposed approach.

关键词： Biomedical imaging Cameras CMOS cameras Cytometry Machine learning Real time imaging

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Optimizing Tandem Solar Cell Efficiency: A Perovskite-CIGS Approach

Optimizing Tandem Solar Cell Efficiency: A Perovskite-CIGS A...

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Emerging Trends in Information technology and engineering (ic-ETITE), Conference on

作者： Arpita Chakraborty Aditya Chakraborty Fariba Tasnia Khan Tanjim Mahmud Mohammad Shahadat Hossain Karl Andersson Dept. of CSE Chittagong University of Engineering and Technology Chattogram Bangladesh Dept. of EEE Chittagong University of Engineering and Technology Chattogram Bangladesh Computer Science and Engineering Southern University Bangladesh Chattogram Bangladesh Dept. of CSE Rangamati Science and Technology University Rangamati Bangladesh Dept. of CSE University of Chittagong Chittagong Bangladesh Pervasive and Mobile Computing Laboratory Luleå University of Technology Luleå Sweden

Tandem solar cells combining perovskite and CIGS have rapidly gained prominence as highly efficient photovoltaic devices. Recent advancements in enhancing their efficiency in-volve adjusting the thickness of distinct layers with tunable bandgaps, demonstrating superior performance compared to al-ternative tandem solar cells. The upper cell, employing perovskite material chosen for its excellent light absorption coefficient and optoelectronic properties, collaborates with the bottom CIGS cell, characterized by a tunable bandgap and low thermal requirements, contributing significantly to overall efficiency improvement. Through numerical simulations conducted with wxAMPS software, our proposed model, which incorporates a 3μm thick perovskite absorber layer as the upper cell and a 3.5μm thick CIGS absorber layer as the lower cell, demonstrated outstanding power conversion efficiency of 40.0209%, Voc of 1.8675 V, Jsc of 23.2146 mA/cm 2 , and FF of 92.3152

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QoE-Delay Modeling for Haptic Communications with Stabilizing Control Schemes

QoE-Delay Modeling for Haptic Communications with Stabilizin...

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2021 IEEE Globecom Workshops, GC Wkshps 2021

作者： Chen, Rui Yue, Tong Li, Ming Liu, Qian Dalian University of Technology Dept. of Information and Communication Engineering Dalian116024 China Dalian University of Technology Dept. of Computer Science and Technology Dalian116024 China

ISBN: (纸本)9781665423908

In order to quantify the user's experience of haptic interactions in networked teleoperation systems, we design a virtual environment with computer-aid design and conduct extensive subjective tests to explore the relationship among the quality of user's experience, communication delay and control schemes (which maintain the stability of networked teleoperation systems). Four kinds of control schemes are studied in this paper, including (1) Wave Variable (WV) approach;(2) Time Domain Passivity Approach (TDPA);(3) Input-to-State Stable (ISS) approach;and (4) Model Mediated Teleoperation (MMT). These schemes are combined with perceptual dead zone coding to reduce the packet rate of haptic data. Through subjective tests, a QoE-delay model is obtained for haptic interaction in networked teleoperation. This model can be considered as a quality metric to guide the joint optimization of communication and control aiming at achieving the maximal quality of experience (QoE) for haptic interactions. Furthermore, we take the MAC layer multi-stream scheduling as an example to illustrate how to utilize the proposed QoE-delay model as a key metric for the resource allocation in haptic communications. © 2021 IEEE.

关键词： Quality of service

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Living in a Pink Cloud or Fighting a Whack-a-Mole? On the Creation of Recurring Revenue Streams in the Embedded Systems Domain

Living in a Pink Cloud or Fighting a Whack-a-Mole? On the Cr...

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Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Helena Holmström Olsson Jan Bosch Dept. of Computer Science and Media Technology Malmö University Malmö Sweden Dept. of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

For companies in the embedded systems domain, digitalization and digital technologies allow endless opportunities for new business models and continuous value delivery. While physical products still provide the core revenue, these are rapidly being complemented with offerings that allow for recurring revenue and that are based on software, data and artificial intelligence (AI). However, while new digital offerings allow for fundamentally new and recurring revenue streams and continuous value delivery to customers, the creation of these proves to be a challenging endeavour. In this paper, we study how companies explore ways to create new or additional value with the intention to complement their product portfolio with offerings that allow for recurring revenue. Based on multi-case study research, we identify the key challenges that companies in the embedded systems domain experience and we derive four organizational patterns that we see slow down innovation. Second, we present a framework outlining alternative types of offerings to customers. Third, we provide a value taxonomy in which we detail the different types of offerings and the value these provide to customers. For each value offering, we indicate whether this offering is (1) static or evolving, (2) bundled or unbundled, (3) free or monetized, and we provide examples from the case companies we studied.

关键词： Technological innovation Embedded systems Taxonomy Companies Software Artificial intelligence Portfolios

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An Enhanced Smart Intelligent Detecting and Alerting System for Industrial Gas Leakage using IoT in Sensor Network

An Enhanced Smart Intelligent Detecting and Alerting System ...

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International Conference on Smart Systems and Inventive technology (ICSSIT)

作者： G.A Senthil P Suganthi R. Prabha M. Madhumathi S. Prabhu S Sridevi Dept. of Information Technology Agni College of Technology Chennai India Dept. of Electronics and Communication Engineering Sri Sai Ram Institute of Technology Chennai India Dept. of Artificial Intelligence and Data Science Karpaga Vinayaga College of Engineering and Technology Chennai India Dept. of Computer Science and Engineering Sri Ramachandra Engineering and Technology Chennai India

Leakage of any type of gas has emerged as a hazard in recent years, whether in a typical workplace, boiler, a commercial setting, a café, or a canteen, industries natural gas, coal, refinery products, crude oil, cement, electricity, steel, and fertilizers etc. In this article, I proposed a new invention of an IoT-based gas waste monitoring, leak detection, and alerting system. The research extends on the development of such an intelligent system that can intelligently preserve gas, ensure the safety precaution and pre vent accidents. The technique must be connected to the stove. The design incorporates ultrasonic sensors which identify bio gas leakage in circumstance with in square metre is usage area of industries or cooking place. The Proposed work smart intelligence system is cuts off the gas supply using an automated shutting off device. Whenever a gas leak is detected, consumers will be notified through SMS via GSM, location using GPRS, and will be able to resolve the situation as quickly as feasible. The flame sensor in the technology will supervise flame and fire. The buzzer starts to sound when a fire is detected. Aside from that, the system may save data on the cloud. With the help of this cloud storage solution, every user’s daily gas use may be traced. Finally, this approach will aid in recognizing per user natural gas consumption. The system has been examined and is capable of monitoring gas loss, evacuation, and sending an SMS notification and location aid to the user. The precipitate demonstrated its usefulness in conserving a considerable amount of domestically squandered gas.

关键词： Industries GSM Cloud computing Vents Fires Sensor systems Intelligent sensors

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Crime Prediction using Machine Learning with a Novel Crime Dataset

arXiv

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arXiv 2022年

作者： Shohan, Faisal Tareque Akash, Abu Ubaida Ibrahim, Muhammad Alam, Mohammad Shafiul Dept. of Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh Dept. of Computer Science and Engineering Univeristy of Dhaka Dhaka Bangladesh

Crime is an unlawful act that carries legal repercussions. Bangladesh has a high crime rate due to poverty, population growth, and many other socio-economic issues. For law enforcement agencies, understanding crime patterns is essential for preventing future criminal activity. For this purpose, these agencies need structured crime database. This paper introduces a novel crime dataset that contains temporal, geographic, weather, and demographic data about 6574 crime incidents of Bangladesh. We manually gather crime news articles of a seven year time span from a daily newspaper archive. We extract basic features from these raw text. Using these basic features, we then consult standard service-providers of geo-location and weather data in order to garner these information related to the collected crime incidents. Furthermore, we collect demographic information from Bangladesh National Census data. All these information are combined that results in a standard machine learning dataset. Together, 36 features are engineered for the crime prediction task. Five supervised machine learning classification algorithms are then evaluated on this newly built dataset and satisfactory results are achieved. We also conduct exploratory analysis on various aspects the dataset. This dataset is expected to serve as the foundation for crime incidence prediction systems for Bangladesh and other countries. The findings of this study will help law enforcement agencies to forecast and contain crime as well as to ensure optimal resource allocation for crime patrol and prevention. © 2022, CC BY-NC-ND.

关键词： Adaptive boosting

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Improving ATSC 3.0 Channel Estimation using AI Techniques

Improving ATSC 3.0 Channel Estimation using AI Techniques

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： E. Iradier I. Bilbao J. Montalban P. Angueira S-I. Park S. Kwon N. Hur Dept. Computer Languages and Systems UPV/EHU Bilbao Spain Dept. of Communications Engineering UPV/EHU Bilbao Spain Dept. Electronics Technology UPV/EHU Bilbao Spain ETRI Daejeon South Korea

ISBN: (数字)9798350364262

ISBN: (纸本)9798350364279

Over the past several years, ATSC has continued to develop new technologies that can be integrated into the standard, making it a leading innovator in the broadcasting industry. The spectrum efficiency of the waveforms and coding, combined with new infrastructure based on the integration of a core network, has proposed ATSC 3.0 as a strong candidate for implementing new multimedia-related use cases. However, the requirements for certain use cases (e.g., AR/VR, 360-degree video) are very harsh, for instance, regarding the signal quality needed at the receiver end. A set of ATSC 3.0 physical layer configurations cannot be implemented with the current channel estimation and equalization solutions. Consequently, Artificial Intelligence (AI) is presented as the necessary enabler for these cases. Specifically, AI has demonstrated better use of the knowledge of the propagation channel than traditional processing methods. Therefore, this paper aims to propose AI-based channel estimation techniques for ATSC. Specifically, two solutions are proposed. The first is a super-resolution estimation enhancer, whereas the second performs the interpolation process within the AI. The results show that both techniques improve the performance of current processing techniques by around one order of magnitude.

关键词： Interpolation Superresolution Channel estimation Estimation Broadcasting Proposals Multimedia communication

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Solution of k-Fractional Integral Via Fixed Point Using Complex Valued Double Controlled Dislocated Metric Spaces

Solution of k-Fractional Integral Via Fixed Point Using Comp...

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2021 IEEE International Conference on technology, Research, and Innovation for Betterment of Society, TRIBES 2021

作者： Yadav, Gopal Sharma, Rajesh Kumar Lal Prajapati, Gend Indore Institute of Science and Technology Dept. of Engineering Science and Humanities Indore India Holkar Science College Dept. of Mathematics Indore India Institute of Engineering and Technology Dept. of Computer Science Engineering Indore India

ISBN: (纸本)9781665433426

In this paper, we have presented an extended and generalized version of dislocated metric in the frame of complex valued metric space, which has been introduced as complex valued double controlled dislocated metric space. Under the suitable assumptions, common fixed point theorems have been proven in this structure. In addition to this, we provided the unique solution of k-fractional integral as an application. © 2021 IEEE.

关键词： Topology

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CDP: Selective Influential Nodes Based on Cliques in the Diffusion Process in Social Networks

CDP: Selective Influential Nodes Based on Cliques in the Dif...

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International Conference on Web Research (ICWR)

作者： Fatemeh Yazdanifar Hamid Ahmadi Beni Nikoo Salimi Asgarali Bouyer Dept. of Mathematics and Computer Science Amirkabir University of Technology Tehran Iran Dept. Software Engineering Azarbijan Shahid Madani University Tabriz Iran Dept. of the Electrical Electronics Electronics and Telecommunication Engineering and Naval Architecture University of Genoa Genoa Italy Dept. of Computer Engineering Azarbaijan Shahid Madani University Tabriz Iran

Influence maximization techniques emphasize selecting a set of influential nodes in order to maximize influence. Because the algorithms presented in this field ignore the topology of cliques for diffusion, there are two major challenges in influence maximization algorithms: optimal diffusion and computational overhead reduction. As a result, the CDP algorithm is presented in this article to address these issues. This algorithm first selects suitable cliques for diffusion based on their position and strategy in social networks. Furthermore, for each clique, a score is calculated based on the topological criteria of the clique, and suitable cliques are selected for diffusion by applying a threshold limit. The seed nodes are chosen from the cliques in the second step. To avoid the rich club phenomenon, only a few nodes from each clique are chosen as seed candidate nodes. Finally, the seed nodes are chosen based on the node’s topology and the strength of the node’s level one neighbor. In the experiment section, the CDP algorithm significantly outperforms the best algorithms presented in recent years in terms of influence spread rate and execution time.

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Navigating the Privacy and Cybersecurity Risks of Smart Homes

Navigating the Privacy and Cybersecurity Risks of Smart Home...

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Information technology (ACIT)

作者： Fatimah Abdulrahman Alghamdi Abdulrahman Abdullah Alghamdi dept. Computer Science and Engineering College of Computing and Artificial Intelligence Jeddah University Jeddah Saudi Arabia dept. Computer Science College of Computing and Information Technology Shaqra University Shaqra Saudi Arabia

The increasing popularity of smart home devices has led to a growing concern over cyberthreats to these devices. This study aims to investigate the perceived cyberthreats to smart home devices and identify ways to protect privacy and countermeasure against these threats. Five experts in the field of smart home technology were selected for this study. Semi-structured interviews were conducted with the selected experts over the telephone. The transcripts of the interviews were analyzed using thematic analysis. The main findings of the study indicate that the most significant cyberthreats to smart home devices are: Voice recordings (35.5 % ), Camera and microphone access (30.1 %), Location tracking (24.9 % ). Personal information (20.1%), Data breaches (15.1 %), Third-party access (7.4 %), Privacy invasion (7.4%), Lack of control over personal information (5.0 % ), Cyber-attacks (4.8%), Security vulnerabilities in smart devices (4.8 % ) were also identified as potential threats. The study suggests that protecting personal data and ensuring device security are key considerations for safeguarding smart home devices and that it is important to take the necessary precautions to protect smart home devices from cyber threats, and to be aware of the potential risks that these devices pose to personal privacy and security.

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