Search

The application of lipid film biosensor devices has created the opportunity to reconstitute a considerable part of their functionality to detect traces of food toxicants. Nanotechnology-enabled sensor miniaturization has extended the range of biological moieties that could be immobilized within a lipid bilayer device. This chapter reviews the recent progress in biosensor technologies for food-quality monitoring. A large number of applications are described herein, placing emphasis on size reduction of novel systems of lipid film devices, new sensing techniques, and nanotechnology-based transduction schemes. The range of analytes that can be currently detected include insecticides, pesticides, herbicides, toxins, hormones, dioxins, and genetically modified foods. Technology limitations and future prospects are discussed, with a focus on the commercialization capabilities of the proposed sensors.

Feedback mechanisms for academic courses have been widely used to measure students opinions and satisfaction towards different components of a course; concurrently, open-text detailed impressions enable professors to continually improve their course. However, the process of reading through hundreds of student feedback responses across multiple subjects, followed by the extraction of important ideas is very time consuming. In this work, we propose an automated feedback summarizer to extract the main ideas expressed by all students on various components for each course, based on a pipeline integrating state-of-the-art Natural Language Processing techniques. Our method involves the usage of BERT language models to extract keywords for each course, identify relevant contexts for recurring keywords, and cluster similar contexts. We validate our tool on 8,201 feedback responses for 168 distinct courses from the Computer Science Department of University Politehnica of Bucharest for the 2019–2020 academic year. Our approach achieves a size reduction of 59% on the overall volume of text, while only increasing the mean average error when predicting course ratings from student open-text feedback by an absolute value of 0.06.

Nanosized particles in the size range 1–100 nm are emerging as an alternative to conventional particles in technological applications. This is due to their small size, which presents them with a great surface area to volume ratio. This unique property of nanomaterials along with the capacity to tune important physicochemical characteristics, such as molecular detection capabilities, based on size and morphology has increased their utilization for novel and improved gas sensor development in various fields of application. Most gases, above their exposure threshold concentration level, can be toxic to humans and the environment.

In this article a compact multi frequency microstrip antenna with enhanced gain has been proposed. This design consists multiple U-shaped slotted modified ground plane of size \( 54 \times 42 \) mm2. The simulation results have been verified with measured results. The effects of slots have been studied and it has been observed that the U-shaped slots lower the resonant frequencies and size reduction of the antenna has been calculated as 94% with respect to the conventional microstrip patch antenna. Simultaneously 7.5 dBi highest gain has also been achieved. The proposed antenna may be used for PCS, LTE 2300, HiperLAN-2 and ITS applications.

Even though densified products have many advantages in terms of storage, handling, transportation, and conversion performance, existing methods to produce dense biomass pellets are currently not considered due to the prohibitive costs to densify them. At present, new preprocessing technologies are developed to address the cost and quality issues associated with conventional methods. This chapter will focus on the advances achieved by industry and national laboratories in terms of biomass size reduction and densification that have a significant impact on energy consumption, cost, and quality. Also, the unit operations and their impact on conventional and advanced preprocessing unit operations are discussed in this chapter.

Formal concept analysis and rough set theory are two of the most important mathematical tools for the treatment of information collected on relational systems. In particular, the idea of reducing the size of a database is widely studied in both theories separately. There are some papers that studied the reduction of a formal context by means of reducts from rough set. In this paper, we are focused in the reduction obtained in an information system considering the FCA reduction mechanism.

Almost all CDCL SAT solvers use the 1-UIP clause learning scheme for learning new clauses from conflicts, and our current understanding of SAT solving provides good reasons for using that scheme. In particular, the 1-UIP scheme yields asserting clauses, and these asserting clauses have minimum LBD among all possible asserting clauses. As a result of these advantages, other clause learning schemes, like i-UIP and all-UIP, that were proposed in early work are not used in modern solvers. In this paper, we propose a new technique for exploiting the all-UIP clause learning scheme. Our technique is to employ all-UIP learning under the constraint that the learnt clause’s LBD does not increase (over the minimum established by the 1-UIP clause). Our method can learn clauses that are significantly smaller than the 1-UIP clause while preserving the minimum LBD. Unlike previous clause minimization methods, our technique is not limited to learning a sub-clause of the 1-UIP clause. We show empirically that our method can improve the performance of state of the art solvers.

This work presents statistical analysis of dried wood biomass using Statistica Neural Networks 8.0. program. The goal of the work was to find similarities and possible difference between convective drying of different types of wood biomass. Wood of five different varieties, i.e. poplar, oak, acacia, willow and rosewood, in three different sizes of size reduction: 29-cm shoots, slices and chips was selected for the analysis using Kohonen networks. The material for experiments was dried in the following temperatures: 50, 60, 70 and 80 °C. The analysis of data related to the process of biomass drying using Kohonen network proved correct in the majority of cases. The interpretation of the topological map, developed as the final effect of the analysis, allowed for the assessment of its correctness at the level of 60%.

In this paper we apply the philosophy of Rough Set Theory to reduce formal context in the environment of Formal Concept Analysis. Specifically, we propose a reduction mechanism based on the consideration of bireducts and we also study several properties of the reduced contexts.

This chapter explains the aim and importance of size reduction in e-waste recycling. Shredding, crushing, pulverizing, and grinding are general comminution methods used in WPCB recycling. Industrial-size shredders, which are hammer mill pulverizers, are covered in detail. Emerging fractionation and electrodynamic fragmentation with high-voltage pulse technologies are introduced for WPCB recycling. Industrial plant application flowsheets are demonstrated. Industrial-scale material classification methods and equipment are presented. Plant-scale conveyor belts for material transport between equipment and working principles of filtration and dust collection systems for high filtration efficiency are also covered in this chapter.

The Messinian salinity crisis (MSC) has already strongly affected the Mediterranean ecosystems from the beginning of the Messinian. Here, the Tortonian, Messinian, and Zanclean size distributions of the most common mesopelagic fish species are compared in order to test the hypothesis that the MSC impacted the size and hence the biomass of Mediterranean mesopelagic fish in the late Miocene. The results suggest that, with appropriate data, a size reduction can be detected during the Messinian that is possibly connected to the MSC restriction of Mediterranean-Atlantic connection. Indeed, these preliminary data suggest an increase otolith size of Ceratoscopelus in the Zanclean.

The recycling chain for e-waste includes collection and sorting; dismantling and size reduction pretreatment; separation, upgrading, and/or extraction preprocessing; and purification and refining endprocessing steps. This chapter briefly covers selective and simultaneous disassembly techniques; size reduction methods for metal-nonmetal fraction liberation and separation; and upgrading and/or extraction of desired valuable materials/metals/electronic components for purification and refining endprocesses. Electronic component recycling for reuse and material recycling can be achieved by mechanical processing, pyrometallurgy, hydrometallurgy, or combination of both pyrometallurgical and hydrometallurgical techniques. Base and precious metals, plastics, batteries, and some valuable electronic components can be recycled, while the remaining nonrecyclable residues should be disposed of properly.

Providing a reliable and efficient communication infrastructure becomes more important and more demanding for current and future Many-core System-on-Chips. The increased amount of communication partners demands for efficient resource usage. At the same time, an on-going feature size reduction and supply-voltage level reduction renders the SoC vulnerable to bit errors. Our work aims at providing a generalized analysis of network-coded Networks-on-Chip with multicast support and unreliable links. We compare network-coded with dimension-routed NoCs in terms of their hop counts and achievable long-term rates. The results show that for an 8 \(\times \) 8 2D-mesh setup, network-coding yields a 1.7\(\times \) to 8.3\(\times \) better hop count and can achieve a 1.2\(\times \) to 3.7\(\times \) higher rate as dimension-routed 8\(\,\times \,\)8 NoCs for bit error probabilities of \(10^{-12}\) to \(10^{-3}\) and 10% multicast traffic.

Collective computational intelligence can be used in several ways, for example as taking the decision together by some form of a bagging ensemble or as finding the solutions by multi-objective evolutionary algorithms. In this paper we examine and compare the application of the two approaches to instance selection for creating the Pareto front of the selected subsets, where the two objectives are classification accuracy and data size reduction. As the bagging ensemble members we use DROP5 algorithms. The evolutionary algorithm is based on NSGA-II. The findings are that the evolutionary approach is faster (contrary to the popular belief) and usually provides better quality solutions, with some exceptions, were the outcome of the DROP5 ensemble is better.

Lower morbidity, length of hospital stay, and more rapid recovery are considered the hallmark of vaginal surgery. With the adoption of size reduction techniques in the modern era, evidence from skilled gynecologic surgeons has shown that these size reduction techniques for uteri greater than 280 g have been proven to been less traumatic to the patient than abdominal or laparoscopic –type hysterectomies. These techniques were developed in the late nineteenth century when surgery by the abdominal route frequently resulted in significant morbidity and mortality, yet for many reasons that are not completely clear were not readily adopted by most gynecologic surgeons. In the twentieth and twenty first century skilled gynecologic surgeons are employing these techniques with greater frequency, with excellent results that suggest these techniques may be more acceptable in the future to gynecologic surgeons if they wish to provide their patients the optimal surgical care.

In this chapter, a new approach is proposed for the \(H_\infty \) filtering over wireless networks. Firstly, the local measurement is sampled under a nonuniform sampling scheme. Then, one dimension of the measurement, which is selected and quantized for transmission.

This chapter is concerned with the design of energy-efficient and reliable distributed controllers for a class of nonlinear large-scale systems. Techniques such as reducing the packet size and the communication times are used to save the energy consumption of the sensors, and thereby extend the lifetime of the networks.

In this research, a beneficiation process including mechanical scrubbing, screening and milling was applied to the alunitic kaolins of the Ballkesir-Slndlrgl region of Turkey to remove alunite and the other impurities, after size reduction. Chemical and mineralogical analysis of the size groups was made to determine the changes with the composition for SiO2, SO3 and Fe2O3. Afterwards, the use of concentrated kaolins in ceramic tile production was investigated. For this purpose, three different recipes were prepared in order to use the concentrated alunitic kaolins in place of the kaolin being used in a ceramic factory. The properties of the ceramic tiles produced were then compared with those of the factory's own products. It was finally proven that the use of concentrated alunitic kaolin at a ratio of 20% improved the physical properties of ceramic tiles of the factory and that the sulphur within the kaolin was tolerated. © 2017 Australian Ceramic Society.

The filter gain variation and energy constraints are frequently encountered in wireless networked systems. In this chapter, these two issues are discussed in a unified framework. New techniques for the nonuniform sampling and the measurement size reduction are presented. In the filter design, the so-called random filter gain variation problem is discussed.

Due to numerous potential applications of conducting polymers, these materials are now world wide studied since the discovery of first conducting polymer (polyacetylene) in 1977. Particularly for sensing concerned, conducting polymers are very sensitive to environmental conditions. The developments in nanostructure conducting polymers and conducting polymer nanocomposites have large impact on sensor research. Due to large surface-area-to-volume ratio of nanostructure conducting polymers, they show superior performance compared to conducting polymers in bulk form. However, the sensitivity and selectivity of nanostructure conducting polymer-based sensors still leave room for improvement. The conducting polymer nanocomposites have gained tremendous recognition in the field of sensors to improve the sensitivity and selectivity due to synergistic effect of size reduction for nanofiller and high electrical conductivity of conducting polymer in nanocomposites. Therefore, the sensitivity and selectivity of conducting polymer nanocomposites-based sensors have been enhanced compared to that of the classical materials-based sensors. This chapter provides the current research activities of the sensors/biosensors based on conducting polymer nanocomposites. The synthesis of nanostructure conducting polymers and conducting polymer nanocomposites, their application in sensors/biosensors are reviewed and discussed in this chapter.

In this contribution, the prototype of an energy efficient RF front-end combined to a miniaturized highly efficient antenna system is presented. This demonstrator is designed for LTE small cell base station applications and can address both LTE band 7 & 20. It supports carrier aggregation (CA) for capacity network improvement and is compatible with inter-band CA as well as contiguous and non-contiguous intra-band CA. The measurement results show an energy consumption saving of around 30 % and a size reduction factor of 3 for the antenna system compared to regular base station antennas. The proposed design demonstrates the possibility of increasing the energy efficiency as well as the level of integration of a small cell base station despite the use of new technology enablers such as CA technique.

In stylometry, there are two important technical questions: Firstly, does the text size affect the authorship attribution performances? and secondly, what could be the effect of the language on that attribution? To respond to those questions, we have conducted several experiments of authorship attribution applied on multi-size text documents. The text size varies from 100 words to 3000 words per document. For that purpose, a specific Arabic dataset has been conceived (i.e. A4P corpus). The corpus is made available for the scientific community and is suitable for the task of stylometry since the genre and theme are quite similar. Two types of features are investigated: character n-grams and words, in association with several classifiers, namely: SVM, MLP, Linear regression, Stamatatos distance and Manhattan distance. During the experiments, 2 types of scores are proposed: the “Score of Good Attribution” and “Robustness against Size Reduction” ratio. Results are quite interesting, showing that the minimum text size required for performing a fair authorship attribution, depends on the feature and classification method that are employed. For the evaluation task, a specific application of authorship attribution has been conducted on 7 religious books, where the main purpose was to check whether the Quran and Hadith could have the same Author or not. Results have clearly shown that those two books should have 2 different Authors.

Size reduction or enlargement of solid foods can be attained by mechanical methods, without use of heat. Size reduction refers to the production of large or small pieces and several particle sizes. Enlargement includes agglomeration or coating of small food pieces or particles, which may be facilitated by adding small quantities of liquids or steam. In the case of liquids, size reduction of particles is achieved in the homogenization. The following sections, Sects. 4.2 and 4.3 deal with solid foods, while Sect. 4.4 deals with size reduction of liquids. Finally, mixing refers to liquid and solid foods and formation in operations dealing with extrusion and other processes giving the final shape/form of foods.

In this chapter, we study an extended distributed control problem: obtain one local controller for each controllable event. Thus an agent may well acquire several local controllers. In this way, further state size reduction may be achieved, simpler local controllers obtained, and the issue of event sharing among agents easily resolved. Then we illustrate localization by applying it to a number of examples drawn from multi-robot formations, manufacturing cells, and distributed computing; in each case, localization effectively creates a purely distributed control architecture where local controllers operate in parallel and achieve global optimality and nonblockingness.