Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customized services. A fundamental requirement of these services is person identification. Although a variety of person-identification approaches has been proposed, they suffer from several limitations in practical applications, such as low energy efficiency, accuracy degradation, and privacy issue. This article proposes an energy-harvesting-based privacy-preserving gait recognition scheme for smart space, which is named PrivGait. In PrivGait, we extract discriminative features from 1-D gait signal and design an attention-based long short-term memory (LSTM) network to classify different people. Moreover, we leverage a novel Bloom filter-based privacy-preserving technique to address the privacy leakage problem. To demonstrate the feasibility of PrivGait, we design a proof-of-concept prototype using off-the-shelf energy-harvesting hardware. Extensive evaluation results show that the proposed scheme outperforms state of the art by 6%-10% and incurs low system cost while preserving user's privacy.

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Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

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Big data these days is big business. Big data implies a combination of databases too large and/or too diverse to maintain by regular database management systems. Big data plays an ever-increasing role these days. This is caused by that fact that not only society started to collect more and more data via for example Facebook but also because more and more technical systems and components started to collect and store data; the so-called Internet of Things (IoT). The IoT enables that more information from sensor systems becomes available that was not available in the past. Theoretically this means that monitoring technical systems 24/7 should become reality and downtime and unexpected maintenance a thing of the past. This paper discusses the utilization of big data and the application of the IoT in bulk solid handling and transportation systems. It discusses recent developments and a case study.@en

The Asymmetric information among different entities can contribute to the imbalance between supply and demand in agricultural supply chain. Negotiation is an effective method to address information symmetry. Many researchers can be found in the literature on agent-based negotiation in industrial supply chain, but very few in agricultural supply chain, primarily because of the interior instability. This paper presents an agent-based negotiation framework for agricultural supply chain to address the information symmetry by introducing the third party logistics. The third party logistics, with more functions than a traditional broker, integrates logistics services and intermediary services to guarantee the relative stability in dynamic agricultural environments. A negotiation interaction process is also designed to facilitate the interaction among these agents. Finally, a case is used to validate the proposed framework.@en

Agricultural supply chain is in general open and dynamic attributed and negotiation is a key strategy to realize collaboration among different entities involved. However, traditional static and offline negotiation strategy may not function well, an agricultural supply chain centered on third party logistics will provide a new collaborative relationship among agricultural materials suppliers, agricultural cooperatives, farmers, agricultural products demanders and third party logistics providers. This paper proposes a novel adaptive negotiation strategy for agricultural supply chain centered on third party logistics. The negotiation strategy consists of an evaluation function in terms of integrity and risk preferences, a concession function in terms of concession preference, time and resources, and a generation function in terms of opponent’s behaviors. Afterwards, an procedure was proposed to solve the negotiation strategy. Finally, a simulation experiment was employed to verify the effectiveness of the negotiation strategy. @en

The Internet of Things and Big data these days means big business. Monitoring Belt Conveyor Systems used to be performed by means of inspectors and off line. These days the developments are towards fully automated inspection systems. The IoT enables that more information from sensor systems becomes available that was not available in the past. Theoretically this means that monitoring Belt Conveyor systems 24/7 should become reality and down-time and unexpected maintenance a thing of the past. All these sensor systems produce a vast amount of information. Big data implies a combination of databases too large and/or too diverse to maintain by regular database management systems. Big data plays an ever-increasing role these days. This paper discusses an application of the IoT in bulk solid handling and transportation systems and the utilization of big data. It discusses recent developments and a case study.@en

The concept of PPP-RTK is to achieve integer ambiguity resolution (IAR) at a single GNSS user by providing network-derived satellite phase biases (SPBs) in addition to the standard precise point positioning (PPP) corrections. These corrections enable recovering integerness of user ambiguities, thereby recovering the full capability of the precise carrier-phase observations. This contribution analyzes the capability of single-receiver positioning with IAR using new L5/E5a-frequency observations from GPS, the European Galileo, the Japanese quasi-zenith satellite system (QZSS) and the Indian regional navigation satellite system (IRNSS). In the absence of network products for new systems, especially for IRNSS, we use a small array of multi-GNSS stations to provide a batch of network-derived corrections. These array-aided corrections, comprising estimable combinations of the satellite clocks, first-order slant ionospheric delays as well as the satellite phase biases, are applied to the multi-system single-frequency L5/E5a-observations of the user station. Results from real-data experiments demonstrate that even though standalone PPP-RTK using current L5/E5a-enabled satellite sets of each single system is not possible yet, they effectively contribute to the tightly integrated multi-system PPR-RTK.@en