VLNComm (United States)

VLC (or visible light communication) has grown in popularity in recent years. For next-generation communication system upgrades, dependable data transmission is essential. As the number of VLC system users increases, so does the need for consistent, rapid, and minimally delayed data delivery. However, as more consumers demanded higher speeds, transmission errors also increased. The error correction code minimizes the overall system's data error to mitigate this effect. This study examines a design architecture for a visible light communication (VLC) transmission system that incorporates forward error correction code to improve error performances, suggesting its suitability as access points in 5G technology. The simulation uses version 17 of the Opti system. The proposed architecture employs the Reed Solomon code, a well-known forward error correction (FEC) channel encoding, to safeguard the baseband signal throughout its transmission over an optical channel containing all visible background sounds. An optical filter and equalizer purify an incoming optical signal by eliminating harmonic components introduced by the VLC channel and restoring signal balance. The data transmission has utilized a forward error-correcting channel encoding of RS code with a nonreturn to zero. The simulation modelled the white, spectral, red, yellow, green, and blue light to present various background sounds accessible via the VLC channel. The simulation results indicate that the system model obtains a typical level of zero-bit errors.

Abstract Background: Loneliness is increasingly reported as a growing problem throughout society and is insufficiently addressed through traditional health care systems. Current evidence highlights the physical, emotional, and mental health implications of loneliness. Further, the impact of loneliness as a global public health issue is evidenced by connections to increased obesity, depression, weakened immune systems, and high blood pressure. Interventions aimed at addressing reducing loneliness are being developed and despite their promises, limited evidence of their efficacy exists. In this paper, we look at the cross-sector networks being developed across six cities as a way to develop and implement a specific intervention (Nature Based Social Prescribing) to address social isolation and loneliness. Methods: A network analysis of participating countries was launched with the goal of knowing more about potential networks in partner cities that the RECETAS consortium could draw on when designing and implementing NBSP interventions. We were able to visualize and measure the existing networks and create a place-based understanding of how NBSP can be promoted and sustained locally. Results: The social network analysis reveals similarities and differences across six international cities, and their experiences of establishing networks and collaborating between organizations and their perceptions of and responses to nature-based prescribing and outcomes. These maps are indicative of the number and scope of relational networks that exist in each study site. Our analysis shows that the number of members varies greatly by country, but that quite a few have a large number of relationships and activities. All cities reported an active network in these areas. The membership of these networks was expected, although there are members from unusual sectors that are encouraged to participate in order to diversify the networks. Conclusions: The RECETAS project will use these network data and results to understand how stakeholders across the six cities are working to address mental health, well-being, and loneliness through social prescribing and nature-based activities with the ultimate goal to systematically improve mental health and well-being, reduce loneliness, promote vibrant socially-connected communities, contribute to the sustainability of cities, and reduce health inequities by connecting diverse populations to nature in meaningful ways.

Existing FPGA-based DNN accelerators typically fall into two design paradigms. Either they adopt a generic reusable architecture to support different DNN networks but leave some performance and efficiency on the table because of the sacrifice of design specificity. Or they apply a layer-wise tailor-made architecture to optimize layer-specific demands for computation and resources but loose the scalability of adaptation to a wide range of DNN networks. To overcome these drawbacks, this paper proposes a novel FPGA-based DNN accelerator design paradigm and its automation tool, called DNNExplorer, to enable fast exploration of various accelerator designs under the proposed paradigm and deliver optimized accelerator architectures for existing and emerging DNN networks. Three key techniques are essential for DNNExplorer's improved performance, better specificity, and scalability, including (1) a unique accelerator design paradigm with both high-dimensional design space support and fine-grained adjustability, (2) a dynamic design space to accommodate different combinations of DNN workloads and targeted FPGAs, and (3) a design space exploration (DSE) engine to generate optimized accelerator architectures following the proposed paradigm by simultaneously considering both FPGAs' computation and memory resources and DNN networks' layer-wise characteristics and overall complexity. Experimental results show that, for the same FPGAs, accelerators generated by DNNExplorer can deliver up to 4.2x higher performances (GOP/s) than the state-of-the-art layer-wise pipelined solutions generated by DNNBuilder [1] for VGG-like DNN with 38 CONV layers. Compared to accelerators with generic reusable computation units, DNNExplorer achieves up to 2.0x and 4.4x DSP efficiency improvement than a recently published accelerator design from academia (HybridDNN [2]) and a commercial DNN accelerator IP (Xilinx DPU [3]), respectively.

Abstract Today, cross‐sector partners are working together and utilizing a systems approach to solve and tackle complex social problems facing their communities. While building cross‐sector organizational networks has become a best practice in solving complex problems, there is little guidance or evidence on how it can be accomplished without overburdening resource‐stressed systems. Social network analysis (SNA) is one method for evaluating networks using a quantitative approach to measure the strength of connections, how organizations position themselves in a network, leverage resources, and assess the quality and impact of exchanges within the network. The PARTNER Tool (Program to Analyze, Record, and Track Networks to Enhance Relationships) leverages concepts of network science and SNA to provide a validated survey, measures, and analysis tool for network evaluation. The PARTNER methodology assesses the strengths (and gaps) among member relationships, how members perceive trust and value in partnerships, the creation of member relationships and how they have evolved, and identifies needs and gaps based on agreement on outcomes and success at reaching network goals. This chapter provides specific steps to implement the PARTNER Tool Methodology, including customizing the validating survey, administration of the online survey, analyzing the results using the PARTNER evaluation framework, and translating the data to actionable strategies. Real‐world examples are presented to highlight the benefits that can be achieved by leveraging network science with a focus on developing evidence‐based strategies that yield significant results and allow cross‐sector organizations to document their collective progress over time.

Light-emitting diode (LED)-based communications, such as visible light communications and infrared communications, are candidate techniques to provide short-range and high-speed data transmission. In this letter, M-ary pulse amplitude modulation (M-PAM), used as a high bandwidth efficiency scheme, is compared with three well-known optical orthogonal frequency-division multiplexing (OFDM) schemes. Considering the bandwidth limit and constrained peak transmitted power characteristics of LEDs, a bit loading algorithm and a single-tap equalizer with an optimized modulation index are used for the optical OFDM schemes tested. To reduce the inter-symbol interference caused by the bandlimited channel, an optimized pulse shape and a minimum mean squared error equalizer are applied to the M-PAM system. From numerical results, M-PAM can provide a substantially higher data rate than OFDM for bandlimited channels. When the channel bandwidth is ample compared with the symbol rate, optical OFDM outperforms M-PAM.

We consider online multimodal data fusion, where the goal is to combine information from multiple modes to identify an element in a large dictionary. We address this problem in the context of object recognition by focusing on tactile sensing as one of the modes. Using a tactile glove with seven sensors, various individuals grasp different objects to obtain 7-D time series, where each component represents the pressure sequence applied to one sensor. The pressure data of all objects is stored in a dictionary as a reference. The objective is to match a streaming vector time series from grasping an unknown object to a dictionary object. We propose an algorithm that may start with prior knowledge provided by other modes. Receiving pressure data sequentially, the algorithm uses a dissimilarity metric to modify the prior and form a probability distribution over the dictionary. When the dictionary objects are dissimilar in shape, we empirically show that our algorithm recognize the unknown object even with a uniform prior. If there exists a similar object to the unknown object in the dictionary, our algorithm needs the prior from other modes to detect the unknown object. Notably, our algorithm maintains a similar performance to standard offline classification techniques, such as support vector machine, with a significantly lower computational time.

Visible light communication is a candidate technique to provide high-speed data transmissions. This paper proposes a joint optimal waveform design algorithm for visible light communication systems using $M$ -ary pulse amplitude modulation to support multiple users. Transmitted waveforms and minimum mean squared error filters are jointly optimized to minimize the intersymbol and multiple access interferences. Based on different channel conditions, the designed waveforms and modulation constellation sizes can be adaptively adjusted to guarantee the highest bit rates. Channel uncertainty is also considered in this paper. Compared with optical code division multiple access and time division multiple access, the algorithm proposed can provide higher bit rates. In addition, the proposed algorithm can flexibly adjust the illumination level by changing the optimization constraints. An offline waveform design algorithm is then proposed to diminish the optimization computation time. A waveform lookup table can be established offline in advance, and the proper waveforms can be selected from the table based on the actual channel gains in real time. The performance of the offline algorithm can be estimated by using the channel uncertainty model.

Pour l'A., l'interrogation ethique sur l'homme part de la question kantienne Que dois-je faire?. Le christianisme enseigne un type de conduite qui est fonde sur des exigences ethiques bien precises avec notamment ce commandement de l'amour de tous ses prochains comme des freres. Ainsi, la vie morale ne semble pas facile tant au niveau personnel qu'au niveau societal. L'A. affirme que le code de conduite propose par les societes laiques entraine une vie compartimentee de chaque personne. Il conclut qu'un ethos sans Dieu offre un bonheur toujours precaire