General Classification Scheme Research Articles

The relationship between classification research and information retrieval research, 1952 to 1970

PurposeThe purpose of this paper is to present the initial relationship between the Classification Research Group (CRG) and the Center for Documentation and Communication Research (CDCR) and how this relationship changed between 1952 and 1970. The theory of normative behavior and its concepts of worldviews, social norms, social types, and information behavior are used to characterize the relationship between the small worlds of the two groups with the intent of understanding the gap between early classification research and information retrieval (IR) research.Design/methodology/approachThis is a mixed method analysis of two groups as evidenced in published artifacts by and about their work. A thorough review of historical literature about the groups as well as their own published works was employed and an author co-citation analysis was used to characterize the conceptual similarities and differences of the two groups of researchers.FindingsThe CRG focused on fundamental principles to aid classification and retrieval of information. The CDCR were more inclined to develop practical methods of retrieval without benefit of good theoretical foundations. The CRG began it work under the contention that the general classification schemes at the time were inadequate for the developing IR mechanisms. The CDCR rejected the classification schemes of the times and focused on developing punch card mechanisms and processes that were generously funded by both government and corporate funding.Originality/valueThis paper provides a unique historical analysis of two groups of influential researchers in the field of library and information science.

Water-integrated scheduling of batch process plants: Modelling approach and application in technology selection

Efficient water management is becoming increasingly important in production systems, but companies often do not have any concrete strategies to implement. While there are numerous technological options for improving water efficiency in process plants, there is a lack of effective decision support to integrate water aspects in operational decision making. This paper is based on the premise that inclusion of water reuse and related technological decisions during scheduling of production operations is essential for reduction of industrial water consumption. We develop a water-integrated scheduling approach based on mathematical programming to capture the main characteristics of water flows in batch process plants. We model water quality with a practical and generic classification scheme to effectively include water reuse and treatment possibilities. The approach is able to quantify tradeoffs between production efficiency and water efficiency. We also illustrate the use of our approach in the evaluation of water reuse and regeneration technologies for typical process industry settings. Overall, our approach is able to integrate water reuse and regeneration in a relatively efficient manner, and can help reduce industrial water consumption in process industries.

User profiling and behavioral adaptation for HRI: A survey

To effectively collaborate with people, robots are expected to detect and profile the users they are interacting with, but also to modify and adapt their behavior according to the learned models. The goal of this survey is to focus on the perspective of user profiling and behavioral adaptation. On the one hand, human-robot interaction requires a human-oriented perception to model and recognize the human actions and capabilities, the intentions and goals behind such actions, and the parameters characterizing the social interaction. On the other hand, the robot behavior should be adapted in its physical movement within the space, in the actions to be selected to achieve collaboration, and by modulating the parameters characterizing the interaction. In this direction, this survey of the current literature introduces a general classification scheme for both the profiling and the behavioral adaptation research topics in terms of physical, cognitive, and social interaction viewpoints.

Mapping of the Universe of Knowledge in Different Classification Schemes

Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter’s Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider’s International Classification, Bibliothecal Bibliographic Klassification (BBK), and Broad System of Ordering (BSO). We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design. URL: http://ijkcdt.net/xml/10973/10973.pdf

Dendrite growth velocity in the undercooled melt of glass forming Ni50Zr50 compound

Glass-forming Ni50Zr50 intermetallic compound is containerless undercooled and solidified using electrostatic levitation. Large undercoolings up to ∆T = 300 K are achieved. The dendrite growth velocity of the congruently melting alloy is measured as a function of undercooling using a high-speed camera technique. The experimental data is analysed within a sharp interface theory. It is found that the driving force of crystallisation is controlling the growth kinetics at ∆T < 250 K but at larger undercoolings the growth kinetics is progressively controlled by atomic diffusion. This leads to a slowing down of the growth velocity. The maximum velocity and the temperature at which the maximum occurs (Tmax) are inferred from the dendrite growth velocity – undercooling relation. The relation of the temperature Tmax and the glass temperature fits into a general classification scheme for glass-forming systems. The kinetic and thermal undercooling terms are calculated within dendrite growth theory as a function of the total undercooling. At ∆T > 126 K, the kinetic undercooling dominates and increases rapidly with the undercooling ∆T. The maximum prefactor of the kinetic undercooling is plotted vs. the reciprocal temperature. Its temperature dependence is discussed.

Quality monitoring of spot welding with advanced signal processing and data-driven techniques

As resistance spot welding is a crucial and widely used metal joining technique nowadays, a cheap and highly accurate online quality monitoring scheme is strongly demanded in industry. In this paper, a novel framework for welding quality examination is proposed by using advanced signal processing and artificial intelligence techniques. Our proposed framework consists of two objective schemes, a general welding quality classification scheme and a more detailed and advanced welding quality estimation scheme. To achieve a fast, convenient and cheap monitoring strategy, only the easily obtained electrical signals are monitored for data acquisition. For the welding quality classification, a self-organizing map under a windowed feature extraction is applied. Results of the spot welding experiment from a portable welding machine show that the classification accuracy can be 92.9%. For welding quality estimation, variation of the welding time and detailed aspects of welding quality are introduced. In particular, a modified recurrent neural network is utilized for the size estimation of the heat affected zone, while a novel self-organizing map type classifier is used to detect the expulsion condition along with its occurrence time. During the spot welding experiments, the average error percentage of the heat affected zone size estimation is around 6.7% and the accuracy on expulsion detection reaches 93.3%.

Dark matter, light mediators, and the neutrino floor

We analyze future direct data matter detection experiments using Effective Field Theory (EFT) operators with light, $\lesssim 100$ MeV mass mediators. We compare the nuclear recoil energy spectra from these operators to the predicted high energy solar neutrino spectrum. A set of operators that generate spectra similar to the neutrino background is identified, however this set is distinct from those that mimic the neutrino background for heavy, $\gtrsim 100$ MeV mass mediators. We outline a general classification scheme based on momentum dependence of the dark matter-nucleus interaction to determine how strong the discovery limit for a given operator saturates in the presence of the neutrino background. Our results highlight the benefit of considering a general theoretical framework regarding dark matter, and motivate continued experimental progress towards lower nuclear recoil energy thresholds.

Classifying and modeling setups and cleanings in lot sizing and scheduling

Much attention in the lot sizing and scheduling literature has been focused on reducing the number and size of setups. Cleanings, in contrast, remain a key cost driver in large parts of the process industries such as the food and pharmaceutical sectors. Here, quality and safety considerations lead to a diversity of cleaning requirements. A prerequisite for an efficient use of resources is an accurate representation of the constraints imposed by the different setups and cleanings. In this paper, we therefore first develop a general classification scheme for setups and cleanings. Three different classes are identified: batch-, time-, and volume-dependent setups and cleanings. The classes are further differentiated based on their separability, substitutability, reference point, flexibility, product dependency, and batch-size dependency. Secondly, we develop a generic optimization model for lot sizing and scheduling in the typical process-industry setting of flowshops, accurately representing all setup and cleaning classes. Thirdly, we apply the model to the case of cheese production in no-wait flowshops, demonstrating the adaptability of the generic model to industry-specific settings as well as the computational efficiency of the approach. The results show that significant reductions in machine downtime and makespan are achieved. Finally, our numerical tests provide insights into the extent to which a misidentification of cleaning classes may decrease scheduling flexibility and impair solution quality. Our results also show the benefits of considering the heterogeneity in processing times, which can be used to compensate for setup- and cleaning-time differences during successive production stages.

Analysis of group composition in multimember multigroup data

AbstractData from groups often have a multimember multigroup (MMMG) structure. Examples are two‐parent families with a female or male child (three members, two groups), two same‐gender and opposite‐gender peers of different status (two members, four groups), or gay, lesbian, and heterosexual couples (two members, three groups). To analyze such data, a framework called MMMG actor–partner interdependence model (MMMG APIM) is presented considering group composition. Three models are discussed in detail: the three‐member two‐group APIM, the two‐member four‐group APIM, and the two‐member three‐group APIM. Structural equation modeling and cross‐sectional and longitudinal data are used to illustrate the approach. To ease the interpretation of APIM findings, a proposal of a general classification scheme is made.

중장년층 일자리 요구사항 분석 및 인력 고용 매칭 시스템 개발

중장년층 일자리 요구사항 분석 및 인력 고용 매칭 시스템 개발

MYOELECTRIC ACTIVATION DIFFERENCES IN TRANSFEMORAL AMPUTEES DURING LOCOMOTOR STATE TRANSITIONS

Locomotor state transitions are challenging for transfemoral (TF) amputees due to the lack of active knee control even in the current powered prosthetic devices. Myoelectric activation has been used successfully to classify steady-state locomotion states, but classification of transitions between locomotion states remains a challenge, especially for TF amputees. The purpose of this study was to determine if lower-extremity muscle activation differences between pre-transition and transition gait cycles occur in the involved or uninvolved limb of TF amputees during locomotion state transitions. Surface electromyography (EMG) was collected from residual muscles on the involved limb and from the uninvolved limb from five TF amputees as they transitioned between different locomotion states (level ground, ramp ascent/descent, stair ascent/descent). Statistical parametric mapping (SPM) was used to assess differences in activation. When analyzed as a group, the only significant differences were observed in the vastus lateralis of the uninvolved limb. High inter-subject variation reduced the significance of other pattern differences. Further inspection revealed that the individual subjects expressed three different recruitment patterns. These recruitment patterns may indicate compensatory strategies adopted by the subjects over the years since amputation. Furthermore, the separate recruitment patterns suggest the need for individualized locomotion transition classification algorithms rather than a general classification scheme.

Pseudospin anisotropy of trilayer semiconductor quantum Hall ferromagnets

When two Landau levels are brought to a close coincidence between them and with the chemical potential in the Integer Quantum Hall regime, the two Landau levels can just cross or collapse while the external or pseudospin field that induces the alignment changes. In this work, all possible crossings are analyzed theoretically for the particular case of semiconductor trilayer systems, using a variational Hartree-Fock approximation. The model includes tunneling between neighboring layers, bias, intra-layer and inter-layer Coulomb interaction among the electrons. We have found that the general pseudospin anisotropy classification scheme used in bilayers applies also to the trilayer situation, with the simple crossing corresponding to an easy-axis ferromagnetic anisotropy analogy, and the collapse case corresponding to an easy-plane ferromagnetic analogy. An isotropic case is also possible, with the levels just crossing or collapsing depending on the filling factor and the quantum numbers of the two nearby levels. While our results are valid for any integer filling factor $\nu$ (=1,2,3,...), we have analyzed in detail the crossings at $\nu=3$ and $4$, and we have given clear predictions that will help in their experimental search. In particular, the present calculations suggest that by increasing the bias, the trilayer system at these two filling factors can be driven from an easy-plane anisotropy regime to an easy-axis regime, and then can be driven back to the easy-plane regime. This kind of reentrant behavior is an unique feature of the trilayers, compared with the bilayers.

Unification of [FeFe]-hydrogenases into three structural and functional groups

Background[FeFe]-hydrogenases (Hyd) are structurally diverse enzymes that catalyze the reversible oxidation of hydrogen (H2). Recent biochemical data demonstrate new functional roles for these enzymes, including those that function in electron bifurcation where an exergonic reaction is coupled with an endergonic reaction to drive the reversible oxidation/production of H2. MethodsTo identify the structural determinants that underpin differences in enzyme functionality, a total of 714 homologous sequences of the catalytic subunit, HydA, were compiled. Bioinformatics approaches informed by biochemical data were then used to characterize differences in inferred quaternary structure, HydA active site protein environment, accessory iron-sulfur clusters in HydA, and regulatory proteins encoded in HydA gene neighborhoods. ResultsHydA homologs were clustered into one of three classification groups, Group 1 (G1), Group 2 (G2), and Group 3 (G3). G1 enzymes were predicted to be monomeric while those in G2 and G3 were predicted to be multimeric and include HydB, HydC (G2/G3) and HydD (G3) subunits. Variation in the HydA active site and accessory iron-sulfur clusters did not vary by group type. Group-specific regulatory genes were identified in the gene neighborhoods of both G2 and G3 Hyd. Analyses of purified G2 and G3 enzymes by mass spectrometry strongly suggest that they are post-translationally modified by phosphorylation. ConclusionsThese results suggest that bifurcation capability is dictated primarily by the presence of both HydB and HydC in Hyd complexes, rather than by variation in HydA. General significanceThis classification scheme provides a framework for future biochemical and mutagenesis studies to elucidate the functional role of Hyd enzymes.

Wireless Communication in Data Centers: A Survey

Data centers (DCs) is becoming increasingly an integral part of the computing infrastructures of most enterprises. Therefore, the concept of DC networks (DCNs) is receiving an increased attention in the network research community. Most DCNs deployed today can be classified as wired DCNs as copper and optical fiber cables are used for intra- and inter-rack connections in the network. Despite recent advances, wired DCNs face two inevitable problems; cabling complexity and hotspots. To address these problems, recent research works suggest the incorporation of wireless communication technology into DCNs. Wireless links can be used to either augment conventional wired DCNs, or to realize a pure wireless DCN. As the design spectrum of DCs broadens, so does the need for a clear classification to differentiate various design options. In this paper, we analyze the free space optical (FSO) communication and the 60 GHz radio frequency (RF), the two key candidate technologies for implementing wireless links in DCNs. We present a generic classification scheme that can be used to classify current and future DCNs based on the communication technology used in the network. The proposed classification is then used to review and summarize major research in this area. We also discuss open questions and future research directions in the area of wireless DCs.

Ethics in Entrepreneurial Finance: Exploring Problems in Venture Partner Entry and Exit

This research advances our understanding of the manifestation of tensions and ethical issues in entrepreneurial finance. In doing so, we offer an overview of ethics in entrepreneurship and finance, delineating the curious paucity of research at their intersection. Using twelve vignettes, we put forward the asymmetries between entrepreneurs and investors and discuss a set of ethical problems that arise among key actors centring on the dynamics of venture partner entry and exit, applying the multiple-lens ethical perspective to analyse these issues. This analysis culminates in the introduction of a general classification scheme for ethical problems across venture partners. Our analysis highlights the moral dimension inherent in the entry and exit of venture partners and the importance of considering moral judgement, as well as intention in future analysis of any decision-making. Our study also points to the moral responsibility in finance, especially to the mutual moral responsibilities of investors and entrepreneurs. By integrating ethics into finance, this research also demonstrates that in the case of venture partner exit, an ethical approach and decent governance go beyond compliance to the law. We conclude with implications for practitioners, specifically with some proposals for a solution to the problem of blocked and forced exit. Together, we make several contributions to the literature by integrating ethics, finance and entrepreneurship, and we call for future research to stimulate a growing body of research within this presently overlooked area.

A general modeling approach to online optimization with lookahead

A vast number of real world problems are coined by an information release over time and the related need for repetitive decision making over time. Optimization problems arising in this context are called online since decisions have to be made although not all data is known. Due to technological advances, algorithms may also resort to a limited preview (lookahead) on future events. We first embed the paradigm of online optimization with lookahead into the theory of optimization and develop a concise understanding of lookahead. We further find that the effect of lookahead can be decomposed into an informational and a processual component. Based on analogies to discrete event systems, we then formulate a generic modeling framework for online optimization with lookahead and derive a classification scheme which facilitates a thorough categorization of different lookahead concepts. After an assessment of performance measurement approaches with relevance to practical needs, we conduct a series of computational experiments which illustrate how the general concept of lookahead applies to specific instantiations and how a knowledge pool on lookahead effects in applications can be built up using the general classification scheme.

Banking and Insurance Recapitalization During the 2007-2009 Credit Crisis

This paper explores the feedback loop between the intensity of financial intermediary recapitalization and a number of measures of credit and liquidity risk. We cover the entire 2007–2009 subprime crisis with a sample that includes the 97 largest banks and insurance companies on both sides of the Atlantic. We model the intensity of recapitalization by implementing a scale measure inspired by the Corrective Action system used by U.S. banking regulators. The proposed ordering starts with inaction, followed by dividend cuts, to issues of new equity, to bailouts. Our risk measures include toxic asset exposures, credit default swap spreads, and Merton-style probabilities of default. We show that there is a monotone relationship between the intensity of risk and the intensity of recapitalization across all firms and jurisdictions in the sample. We are able to simplify the large heterogeneity of regulations and business models across sectors and countries within a fairly simple and general classification scheme. This scheme distinguishes between individual bailouts, targeted at bankruptcy prevention, and more nuanced collective bailouts, which were more related to the prevention of systemic risk arising from potentially solvent institutions.

A transition function for the solid particle erosion of rocks

A simple two-parameter model K1=1−exp[−(λ⋅χ)b] is derived, which can describe the response of rock materials during the erosion through rounded solid particles at normal incidence. A procedure for estimating the distribution parameters λ and b is proposed, and the procedure is applied to four rock materials (rhyolite, granite, limestone, and schist). Erosion experiments with quartz particles are performed in order to estimate K1 numbers for the rock materials. It is shown that the model covers different types of material response. The parameter K1 can be linked to general rock classification schemes.

A Replication of “Meta-Analysis of the Effect of Fiscal Policies on Long-run Growth” (European Journal of Political Economy 2004)

This study replicates the article by Nijkamp and Poot (2004), henceforth N&amp;P, and performs a variety of robustness checks. Using a sample of fiscal policy studies published between 1983 and 1998, N&amp;P concluded that certain types of studies on fiscal policies were more likely to confirm prior beliefs about their impact on economic growth than others. N&amp;P also identified study attributes that impacted the likelihood of confirmation. We are able to exactly replicate their findings. We then attempt an alternative replication, returning to the original studies and independently categorizing them using N&amp;P’s general classification scheme. We also investigate the implications of a number of methodological improvements on their analysis. Our analysis produces results that are qualitatively similar to N&amp;P, though few of our results are statistically significant. The full-length version of this study suggests directions for future meta-analysis studies on the subject of fiscal policy and economic growth.

Classification of nematic order in 2 + 1 dimensions: Dislocation melting andO(2)/ZNlattice gauge theory

Nematic phases, breaking spontaneously rotational symmetry, provide for ubiquitously observed states of matter in both classical and quantum systems. These nematic states may be further classified by their $N$--fold rotational invariance described by cyclic groups $C_N$ in 2+1D. Starting from the space groups of underlying $2d$ crystals, we present a general classification scheme incorporating $C_N$ nematic phases that arise from dislocation-mediated melting and discuss the conventional tensor order parameters. By coupling the $O(2)$ matter fields to the $Z_N$ lattice gauge theory, an unified $O(2)/Z_N$ lattice gauge theory is constructed in order to describe all these nematic phases. This lattice gauge theory is shown to reproduce the $C_N$ nematic-isotropic liquid phase transitions and contains an additional deconfined phase. Finally, using our $O(2)/Z_N$ gauge theory framework, we discuss phase transitions between different $C_N$ nematics.