Data Link Research Articles

Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Human behaviour is a major driver and determinant of household energy consumption, with routines and practices shaping daily energy profiles. These routines and practices are made up of individual lifestyles and other contextual factors that vary from home to home. Social and psychological theories aim to explain and describe how people consume resources in the home, which has resulted in the development of the home system of practice. This evaluates how occupants live and follow multiple routines which result in varying energy consumption practices. This paper develops a methodology to identify and support the concept of the home system of practice using a data analytical approach and link it to residential energy and distribution network management. This paper utilises k-means cluster analysis to identify these different home systems of practices and routines in energy use by using real-time energy consumption data from July 2019 to March 2021 from a living laboratory in Australia. The results of the analysis show the different daily energy profiles for each of the 39 households, with some homes observing large fluctuations and changes in the way they consume energy during the day. Specific homes were discussed as case studies in this paper focusing on linking the occupants’ contextual factors to their energy profiles. This variation is discussed in terms of the routines of the occupants and associated lifestyles that explain why some energy peaks occurred at different parts of the day and differed during the COVID-19 lockdown period in Australia. The paper conducts a comparison between these case studies to show how people’s lifestyles impact household energy consumption (and variation). These case studies investigated the heating and cooling practices of the occupants to demonstrate how they impact overall consumption. This variation is discussed in relation to energy management and prediction of when homes will consume energy to assist in net-zero energy developments and grid stabilisation operations.

Cross‐organisational data sharing framework based on blockchain‐probes

With the development of information technology, various social fields have gradually realised informatisation and digitisation, and today's society has entered the era of big data. A large amount of data exists in different departments and systems. At present, cross-organisational data sharing is often realised by point-to-point authorisation. However, there are still some threats in the management and control schedule for the whole region. To realise secure and credible data sharing, this paper proposes a cross-organisational data-sharing framework based on Blockchain-Probes using distributed digital identity technology. By using a star data link of the complex network, our system realises the synchronisation of heterogeneous data sources by using a data probe as the inter-central transmission carrier to link different data sources. The proposed framework is applied to the real scenario; compared with the traditional method, the efficiency and accuracy are improved, and the total cost is reduced by 60%. The framework could be employed in multiple complex system application scenarios such as transportation, finance and urban management.

A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale.

Critical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research. To describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care. To demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales. When applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) had an emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission. This methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways.

Trends in Earnings Volatility Using Linked Administrative and Survey Data

We document trends in earnings volatility separately by gender using unique linked survey data from the CPS ASEC and Social Security earnings records for the tax years spanning 1995–2015. The exact data link permits us to focus on differences in measured volatility from earnings nonresponse, survey attrition, and measurement between survey and administrative earnings data reports, while holding constant the sampling frame. Our results for both men and women suggest that the level and trend in volatility is similar in the survey and administrative data, showing substantial business-cycle sensitivity among men but no overall trend among continuous workers, while women demonstrate no change in earnings volatility over the business cycle but a declining trend. A substantive difference emerges with the inclusion of imputed earnings among survey nonrespondents, suggesting that users of the ASEC drop earnings nonrespondents.

Understanding the Use of Heterogenous Data in Tackling Urban Flooding: An Integrative Literature Review

Data-driven approaches to urban flooding management require a comprehensive understanding of how heterogenous data are leveraged in tackling this problem. In this paper, we conduct an integrative review of related studies, and this is structured based on two angles: tasks and data. From the selected 69 articles on this topic, diverse tasks in tackling urban flooding are identified and categorized into eight categories, and heterogeneous data are summarized by their content type and source into eight categories. The links between tasks and data are identified by synthesizing what data are used to support the tasks in the studies. The task–data links are a many-to-many relationship in the sense that one particular data category supports multiple tasks, and one particular task uses data from multiple categories. The future research opportunities are also discussed based on our observations. This paper serves a signpost for researchers who wish to gain an overview of the heterogenous data and their use in this field and lays a foundation for studies that aim to develop a data-driven approach to tackle urban flooding.

2.9 K VCSEL demonstrates 100 Gbps PAM-4 optical data transmission

A cryogenic packaged vertical-cavity-surface-emitting laser (VCSEL) with microwave input and coupled with OM4 fiber for optical output was developed and demonstrated laser operation from 295 to 2.9 K. Record 2.9 K optical data links of 100 Gbps pulsed amplitude modulation 4-level have been demonstrated with an energy per bit ∼153.4 fJ/bit when TDECQ = 3.79 dB. The energy/bit is limited by the link path bandwidth resulted from the input cable loss to 2.9 K VCSEL and can be further improved. Thus, the VCSEL optical data link is proven to be a viable solution for cryogenic communication and computing.

Coherent Wireless Link at 300 GHz With 160 Gbit/s Enabled by a Photonic Transmitter

The increasing demand for high-capacity wireless communication requires data links at millimeter waves and terahertz frequencies, respectively. At those frequencies, electronic and photonic technologies compete to prove powerful transmitters and receivers. In this work, we demonstrate a wireless link at 300 GHz using a fiber-coupled PIN photodiode as the transmitter. Thus, the whole emitter side is based on components and techniques from standard fiber-optical communication, which inherently enable broadband data channels. We investigated two antenna designs with amplitude modulated and coherent data signals. Despite similar characteristics in terms of output power and carrier bandwidth, the quality of the data signals differed significantly. In addition, we found that the bit-error ratio (BER) scales non-monotonically with the optical input power of the photodiode, which is proportional to the terahertz output power. Depending on the modulation format and the symbol rate, we identified the optimal driving conditions of the photodiode. For amplitude modulation at 5 Gbit/s, we achieved error-free transmission with a BER of 7.5 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−13</sup> . QPSK modulation was error-free up to 64 Gbit/s. The highest line rate of 160 Gbit/s was achieved with 32QAM modulation. This corresponds to 133 Gbit/s net data rate after forward-error correction with 20% overhead. The highest spectral efficiency was achieved with 64QAM at 8 GBaud, i.e., 48 Gbit/s line rate. The presented results highlight the high bandwidth of photonic wireless THz links. Furthermore, the carefully analysis helps to improve the quality of future wireless links in the 300 GHz band.

Outdated Access Point Selection for Mobile Edge Computing With Cochannel Interference

In this paper, we investigate a mobile edge computing (MEC) network, where the user has some computational tasks to be assisted by multiple computational access points (CAPs) through offloading. We consider practical communication scenarios with limited spectrum resources, and the cochannel interference arising from the aggressive reuse of frequency severely degrades the system offloading performance. To enhance the system performance, we provide three CAP selection criteria to choose one best CAP among multiple ones. Specifically, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion I</i> maximizes the computational capability at the CAP, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion II</i> minimizes the interfering power, while <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">criterion III</i> maximizes the instantaneous channel gain of data link. In time-varying channel environments, the CAP selection may be outdated, which deteriorates the system performance. For the three criteria, we evaluate the system outage probability in the outdated channel state information (CSI) by taking into account the latency, energy consumption and data rate, and provide the analytical and asymptotic expressions of outage probability, from which we obtain some critical insights on the system design. Simulation results are finally demonstrated to verify the proposed studies. In particular, criterion III under the perfect CSI can achieve the system whole diversity order coming from multiple CAPs.

Research on intellectual property protection, innovation, and data protection algorithm based on wireless communication network

In today's world, with the developing technologies, data protection has become an absolute requirement, many organizations are focusing on the security of the data and information. Because many unauthorized individuals can hack computer system, putting the confidential files of the organization at danger. Therefore, there is need to employ various data security techniques in order to secure information. Furthermore, to resolve the problem of high energy consumption caused by large amount of data transmission in data protection algorithm, a data protection algorithm based on wireless communication network is proposed. Furthermore, we investigated that nowadays the protection of intellectual property is become significant issue. Because intellectual property security is essential for promoting innovation. Without intellectual property protection, individuals and firms would not gain the full advantages of their creations and would devote less time to development. The communication channel and data transmission link are established. Each node calculates the residual energy when clustering and sends it to the cluster head before the link is generated. The random number of nodes is encrypted and sorted according to the order of data link. Based on the wireless communication network, the privacy data within and between clusters are fused, and the data difference of each node is calculated respectively. Each cluster head uses homomorphic transformation to realize data sharing. The data protection algorithm is designed. The node data is partitioned and encrypted and decrypted by hybrid operation. The fusion results are uploaded to the base station to complete data protection. Apart from this, in this research, we proposed various methodologies in order to secure information as much as possible including text, photography, forms, videos and many more. Experimental results show that compared with CPDA algorithm, CMT algorithm and HRCDA algorithm, the data protection algorithm designed in this paper consumes the least total energy in each round. The algorithm can protect the privacy of data, reduce the consumption of data, and extend the life cycle of the whole network.

Four-Level Micro-Via Technology (4LµV) for ASIC Integration in Active Flexible Sensor Arrays.

Systems-in-foil with multi-sensor arrays require extensive wiring with large numbers of data lines. This prevents scalability of the arrays and thus limits the applications. To enable multiplexing and thus reducing the external connections down to few digital data links and a power supply, active circuits in the form of ASICs must be integrated into the foils. However, this requires reliable multilayer wiring of the sensors and contacts for chip integration. As an elegant solution to this, a new manufacturing process for multilayer wiring in polyimide-based sensor foils has been developed that also allows ASIC chips to be soldered. The electrical four-level micro-via connections and the contact pads are generated by galvanic copper deposition after all other process steps, including stacking and curing of polyimide layers, are completed. Compared to layer by layer via technology, the processing time is considerably reduced. Because copper plating of vias and solderable copper contact pads happens as the final step, the risk of copper oxidation during polyimide curing is completely eliminated. The entire fabrication process is demonstrated for six strain sensor nodes connected to a surface-mounted ASIC as a detecting unit for sensing spatially resolved bending states. Each sensor node is a full-bridge configuration consisting of four strain gauges distributed across interconnected layers. The sensor foil allows bending of +/−120° without damage. This technology can be used in future for all kinds of complex flexible systems-in-foil, in particular for large arrays of sensors.

Nearly 70 Gbit/s NRZ-OOK encoding of a dual-mode 850 nm VCSEL with a highly In-doped and small Zn-diffused emission area

By pre-emphasized encoding of a dual-mode 850 nm vertical-cavity surface-emitting laser (VCSEL), the nearly 70 Gbit/s on–off keying (OOK) transmission performance is performed for the ultrafast data link. This VCSEL is designed with a new structural configuration, including 6 μm oxidized aperture and 4 μm Zn-diffused emission aperture, which exhibits dual-mode lasing with a threshold current of 0.75 mA, a nonsaturated power of 2.2 mW at 8 mA, and a differential quantum efficiency of 0.38 under a lensed OM4 multimode fiber (MMF) coupling scheme. In particular, the high indium (In) dopant density in the quantum well increases its differential gain coefficient to upshift the relaxation oscillation frequency, which effectively broadens the modulation bandwidth to high-speed data transmission. For the back-to-back transmission, the VCSEL coupled with a lensed OM4-MMF (1 m) for short-reach link reveals an NRZ-OOK transmission at 66 and 69 Gbit/s with a corresponding bit-error ratio (BER) of 5.9 × 10 − 10 and 10 − 5 for error-free decoding after forward-error correction. When employing graded-index single-mode fiber (GI-SMF) with 100 m length as the transmission segment, the VCSEL linked to the GI-SMF connected with a lensed OM4-MMF (1 m) collimator can provide the pre-emphasized NRZ-OOK transmission at 51 Gbit/s with a BER of 4.5 × 10 − 10 and SNR of 14.1 dB.

Multi Gigabit Wireless Data Transfer in Detectors at Future Colliders

The WADAPT (Wireless Allowing Data And Power Transmission) consortium has been formed to identify the specific needs of different projects that might benefit from wireless communication technologies with the objective of providing a common platform for research and development in order to optimize effectiveness and cost. Wireless technologies have developed extremely fast over the last decade and are now mature enough to be a promising alternative to cables and optical links, with a possibility of revolutionizing detector design. Although wireless readout has the qualities and properties to be used in many collider detectors, this article focuses on the transmission of large amount of data from vertex detectors at high rate, low power budget and in potential high radiation environment. For vertex detectors, the 60 GHz band has proven to be adequate and commercial products are already available, providing 6 Gbps data links. This technology allows efficient partitioning of detectors in topological regions of interest, with the possibility of adding intelligence on the detector to perform four-dimensional reconstruction of the tracks and vertices online, in order to attach the tracks to their vertex with great efficiency even in difficult experimental conditions, and conveniently substitutes a mass of materials (cables and connectors). Early transceiver module products have been successfully tested for signal confinement, crosstalk, electromagnetic immunity and resistance to radiation. In the long run, emerging 140 GHz bands could also be used for higher data rates (&amp;gt;100 Gbps) at future high energy and luminosity hadron colliders.

Multivariate fuzzy logic‐based ad hoc on‐demand distance vector protocol under the impact of node mobility in wireless ad hoc networks

SummaryEfficient routing of generated packets through the network with minimal overhead in path discovery and subsequent route maintenance is the fundamental objective required in the modern wireless network operation. Recently, the application of autonomic computational learning techniques for design and optimization of routing protocols in ad hoc networks is substantially gaining the research interest. The commonly deployed soft computing methodology of fuzzy inference system is capable of handling uncertain and imprecise networking information related to the frequently changing states of generic mobile technologies. In this paper, we propose a novel fuzzy logic‐based ad hoc on‐demand distance vector (FL‐AODV) routing protocol employing the multivariate cross‐layer design architecture to optimize the multiple performance parameters in wireless ad hoc networks. This fuzzy optimization framework essentially applies the header length from data link and physical layers, route timeout from network layer, and node mobility speed from application layer as inputs to the fuzzification interface. Besides, bit rate for application layer and communication range parameter for data link layer are scrutinized as the fuzzy outputs derived from the defuzzifier. The designed adaptive routing protocol is extensively assessed through simulation experimental analysis under the varying effects of node mobility conditions. Various network performance attributes including the reception cache hit, packet delivery ratio, packet errors, ping loss rate, mean throughput, and delay are computed and analyzed for comprehensive comparison between the presented fuzzy‐based FL‐AODV and classical AODV routing mechanisms. Finally, we compare our fuzzy routing model with previous algorithms to demonstrate its efficacy in terms of key performance metrics of throughput and delay.

Towards Data Analysis Environment for Multi-Partner Clinical Research Project - SMART-CARE.

A Systems Medicine Approach to Stratification of Cancer Recurrence (SMART-CARE) establishes mass spectrometry-based systems medicine technologies and data analysis pipelines employing expertise of the multiple partners from Heidelberg biomedical campus. We have established a central linked data repository that links clinical, mass spectrometry, and data analysis teams to enable a full cycle of data management. Other questions of setting up the data analysis environment for the multi-partner clinical research project are addressed in this work, too.

Cross-Layer Design Based N-ary Huffman Coding for Performance Analysis of DSDV Routing Protocol in MANETs

The implementation of the optimal Huffman coding technique for achieving proficient data compression, lower information redundancy and minimal utilization of the scarce bandwidth is essential to handle the effective processing of massive network data. In this paper, we employ cross-layer design technique among the data link, network and presentation layers of the traditional protocol stack to develop the improved DSDV routing protocol based on n-ary Huffman coding procedure. The entropy-based adaptive prefix codewords with variable length are assigned to the probability of packet successful delivery across the ad-hoc wireless network. Several coding and network efficiency parameters are deployed to assess the performance of the proposed routing scheme under three distinctive IPv4 network scenarios. These investigated network protocols include the default IPv4, multi IPv4 and dynamic IPv4 routing methodologies. Diversified simulation settings are employed with deviating network size to measure the multitude of essential wireless network characteristics incorporating the average delay, packet error rate, packet delivery fraction, data rate, ping loss rate, entropy rate, and reception cache hit. In addition, the set of key data compression/coding indicators are examined through comprehensive numerical analysis such as codeword length, source information rate, mean redundancy, and coding efficiency. Beyond, we significantly compare the performance of our developed cross-layer coded mobile routing model with several previous algorithms to validate its enhanced feasibility and superiority in terms of crucial network operation metrics such as throughput, packet drop rate, mean delay and packet delivery ratio.

Estimating the Costs of Alternative Large-Scale Food Fortification Programs in Burkina Faso: A MINIMOD Tool for Informing Policy Discussions

ObjectivesDecisions regarding the types and amounts of micronutrients to include in large-scale food fortification (LSFF) programs should consider costs. The Micronutrient Intervention Modeling (MINIMOD) cost tool estimates the costs of alternative LSFF programs, with focus on stakeholders’ cost burdens.MethodsAn activity-based cost model was developed and adapted to the context of Burkina Faso. Key national characteristics (e.g., population size), and information on existing and hypothetical LSFF programs (e.g., adherence to standards) establish the model's platform. Private- and public-sector costs (as relevant) of designing, implementing, and managing LSFF are included. The model contains a micronutrient premix cost calculator. LSFF-vehicle-specific consumption patterns (e.g., g/day of fortifiable wheat flour consumed, based on household survey data) link costs to program reach. A ten-year planning time horizon is adopted.ResultsThe premix required to fortify wheat flour with iron and folic acid (60 mg/kg of ferrous fumarate, 2.5 mg/kg of folic acid – the current standard) is estimated to cost ∼$2.11 (2020 USD) per MT of fortified flour, with overall 10-year program costs of ∼$2.4m; ∼25% faced by industry (e.g., internal quality control), ∼23% by government (e.g., external monitoring), and 52% by stakeholders who would cover premix costs (generally assumed to be industry, with some pass-through to consumers). Cost per person and cost per person reached are ∼$0.010 and ∼$0.023, respectively. Including zinc in this premix (95 mg/kg of zinc oxide) would increase the cost per MT of fortified flour to ∼$3.02, total 10-year program costs to ∼$3.3m, and cost per person and per person reached to ∼$0.014 and ∼$0.032, respectively. The premix's share of costs increased to ∼54%.ConclusionsThe levels and compositions of the costs should be considered when designing and managing LSFF, in part because different stakeholder groups, including consumers, will be called upon to pay them. Premix costs are one main cost driver; increasing the number and/or amounts of fortificants will increase overall program costs and shift the burden of costs among stakeholders.Funding SourcesResearch was supported by a grant to UC Davis from Helen Keller International through their support from the Bill & Melinda Gates Foundation.

Metallurgical Data Science for Steel Industry: A Case Study on Basic Oxygen Furnace

The steel industry has developed sensorization to generate data, monitoring systems, and steelmaking process control. The remaining challenges are data storage issues, lack of cross‐production data links, and erroneous datasets, which significantly increase the quality control complexity. The development of a data‐driven approach through artificial intelligence (AI) techniques enables machine learning techniques to big datasets aiming to provide process–property optimization and identify challenges and gaps in the data. Recently, computational capabilities and algorithmic developments have significantly grown in power and complexity, accelerating process optimization. Addressing large‐scale industrial data process–property optimization strategies involve numerous influencing possessing factors but limited data. As one of the largest production chains in the world, the steel industry faces an ever‐increasing demand for larger components, high levels of functionality, and quality of the final product. Herein, an integrated data‐driven steelmaking case study is built with the aim of predicting and optimizing the final product composition and quality. Machine learning is used collaboratively with fundamental knowledge, first‐principal calculation, and feedback into a backpropagation neural network (NN) model. Integrating data mining and machine learning generates reasonable predictions and addresses process efficiencies within the steelmaking furnaces. The ultimate goal is to enhance the digitalization of the steel industry.

Microcomb-driven silicon photonic systems

Microcombs have sparked a surge of applications over the past decade, ranging from optical communications to metrology1–4. Despite their diverse deployment, most microcomb-based systems rely on a large amount of bulky elements and equipment to fulfil their desired functions, which is complicated, expensive and power consuming. By contrast, foundry-based silicon photonics (SiPh) has had remarkable success in providing versatile functionality in a scalable and low-cost manner5–7, but its available chip-based light sources lack the capacity for parallelization, which limits the scope of SiPh applications. Here we combine these two technologies by using a power-efficient and operationally simple aluminium-gallium-arsenide-on-insulator microcomb source to drive complementary metal–oxide–semiconductor SiPh engines. We present two important chip-scale photonic systems for optical data transmission and microwave photonics, respectively. A microcomb-based integrated photonic data link is demonstrated, based on a pulse-amplitude four-level modulation scheme with a two-terabit-per-second aggregate rate, and a highly reconfigurable microwave photonic filter with a high level of integration is constructed using a time-stretch approach. Such synergy of a microcomb and SiPh integrated components is an essential step towards the next generation of fully integrated photonic systems.

Multi-sector discrete-time channel model for data link layer evaluation of CubeSat communications

Innovation in the space sector is going through a fruitful period. Among other factors, this has been a consequence of the CubeSat paradigm and its acceptance in the educational, scientific, and commercial sectors, as well as its relevant role in the integration of terrestrial and satellite communication systems. Nevertheless, there is no standardized communication protocol for CubeSat technology. One of the reasons for this lack of standardization is the nonexistence of a widely accepted communication channel model for fast development and simulation of CubeSat technology at the data link layer level. Aiming at filling this gap, we propose a communication channel model that captures both the dynamics of the CubeSat in the low earth orbit and the propagation environment where the terrestrial devices are located, taking into account the elevation angle. For this purpose, finite state Markov chains are used to model the time evolution of the channel fading through the satellite trajectory when it passes by the ground point target. Then, CCSDS recommendations are used as a study case for the data link layer of a CubeSat, while an adaptive automatic repeat request mechanism, according to the elevation angle, is simulated and optimized, showing the usefulness of the proposed channel model.

A Distributed Formation Joint Network Navigation and Positioning Algorithm

In view of the problem that the leader-follower joint navigation scheme relies too much on the absolute navigation and positioning accuracy of the leader node, under the conditions of distributed network-centric warfare (NCW) and to meet the location service accuracy, reliability, and synergy efficiency of the future integrated communication, navigation (ICN), we built a joint navigation and positioning system with low Earth orbit (LEO), airborne data link, and inertial navigation system (INS) as the core; designed a ranging and time-synchronization scheme of the joint navigation and positioning system; and established a joint navigation and positioning method for formation and networking based on mutual ranging and velocity measurement information between aircrafts. Finally, based on the designed LEO constellation, the universality, effectiveness, superiority, and potential superiority of algorithm are verified, respectively. The simulation results show that the scheme can meet the requirements of joint location services in challenging environments, and could be used as a reference scheme for future ICN integration.