Miracle-dz/UniFAR-FTUs huggingface dataset:
Global shape normalization for handwritten Chinese character recognition: a new method

Nonlinear normalization (NLN) based on line density equalization has been widely used in handwritten Chinese character recognition (HCCR). Our previous results showed that global transformation methods, including moment normalization and a newly proposed bi-moment method, generate smooth normalized shapes at lower computation effort while yielding comparable recognition accuracies. This paper proposes a new global transformation method, named modified centroid-boundary alignment (MCBA) method, for HCCR. The previous CBA method can efficiently correct the skewness of centroid by quadratic curve fitting but fails to adjust the inner density. The MCBA method adds a simple trigonometric (sine) function onto quadratic function to adjust the inner density. The amplitude of the sine wave is estimated from the centroids of half images. Experiments on the ETL9B and JEITA-HP databases show that the MCBA method yields comparably high accuracies to the NLN and bi-moment methods and shows complementariness.
Energy management at municipal parking deck for charging of Plug-in hybrid electric vehicles

In this paper, an algorithm is proposed to optimally manage a large number of Plug-in hybrid electric vehicles (PHEV's) charging at a municipal parking station. Differential Evolution optimization is used to allocate energy efficiently to the PHEV's. Constraints like energy price, remaining battery capacity, and remaining charging time are used. Simulation results are presented and discussed.
Development of College Working Stress Scale

The purpose of this study was to develop a college working stress scale in the assessment of stresses of university staff.Five procedures were conducted including two sub-studies.The total sample consisted of 187 university staff from two universities in Beijing.Results of the study indicated that internal reliability was very satisfactory(Cronbach α=0.92),test-retest reliability was satisfactory(Cronbach α=0.75). The scale possessed high(validity.)
Recent Developments in Multilayer Perceptron Neural Networks

Several neural network architectures have been developed over the past several years. One of the most popular and most powerful architectures is the multilayer perceptron. This architecture will be described in detail and recent advances in training of the multilayer perceptron will be presented. Multilayer perceptrons are trained using various techniques. For years the most used training method was back propagation and various derivatives of this to incorporate gradient information. Recent developments have used output weight optimization-hidden weight optimization (OWO-HWO) and full conjugate gradient methods. OWO-HWO is a very powerful technique in terms of accuracy and rapid convergence. OWO-HWO has been used with a unique “network growing” technique to ensure that the mean square error is monotonically non-increasing as the network size increases (i.e., the number of hidden layer nodes increases). This “network growing” technique was trained using OWO-HWO but is amenable to any training technique. This technique significantly improves training and testing performance of the MLP.
A Mobile Technology for Hazard Management System

The Japan is one of the countries in the world vulnerable to natural hazards because of its geographic location. Due to the advances of Internet and mobile technologies, mobile phones with Internet connection and computation capabilities are widely used now a day. The purpose of this paper is to examine the proposed hazard warning mechanism using the Location Based Service technology and a hazard information management system to rapidly distribute warning message in a short time while hazard sites are near the system users. The disaster management system Android application known as MyDisasterDroid determines the optimum route along different geographical locations that the volunteers and rescuers need to take in order to serve the most number of people and provide maximum coverage of the area in the shortest possible time. Genetic algorithm was applied for optimization and different parameters were varied to determine the most optimum route.
Multi-target Tracking and Observing in Mobile Sensor Networks

Tracking and observing multiple dynamic targets is an important task in mobile sensor networks. This paper presents a novel approach to the problem of sensor splitting/merging for mobile sensor networks to track and observe multiple targets in a dynamic fashion. In this approach, we propose a seed growing graph partition (SGGP) algorithm to solve the splitting/merging problem. Furthermore, during the process of tracking, collision avoidance and velocity matching among mobile sensors are guaranteed. To demonstrate the benefit of the SGGP algorithm in term of the total energy and time consumption when sensors split, we compare the SGGP with a random selection (RS) algorithm. Numerical experimental tests validate our theoretical results.
Consideration on radiation from an unbalanced-mode spiral antenna

This paper describes the radiation from an unbalanced-mode two-arm spiral antenna, where the antenna arms are defined by the Archimedean spiral function. The input impedance, current distribution, radiation pattern, axial ratio, and gain are investigated. The investigation reveals that the unbalanced-mode spiral radiates a circularly polarized wave over a wide frequency range as the balanced-mode spiral.
Send Orders of Reprints at Reprints@benthamscience.org Social Motivation and Residential Style in Prairie and Meadow Voles

The residential style of rodents varies across and within species from colonial to solitary and territorial [1]. A mechanism that supports this behavioral distinction might be differential levels of social motivation rather than explicit species-typical social behavior. Accordingly, socially motivated animals learn seeking behavior that leads to a colonial residential pattern and socially unmotivated animals do not learn this behavior and remain solitary. The present experiments test this hypothesis by measuring social motivation in a gregarious social species of vole, the prairie vole, and in a solitary species, the meadow vole. Although their explicit social behavior was similar, Prairie voles readily learned to perform an instrumental response for access to a target vole while meadow voles did not. Neither the estrus status nor the sex of the target affected instrumental responding in either species. In sum, differential social motivation may contribute to distinctive residential patterns in rodents.
The pipeline of ontology building for web-based application

IntroductIon Ontology integration is one of the most important research topics in knowledge integration and knowledge reconciliation. It has been widely applied in knowledge engineering, database and data warehouse, e-commerce as well as semantic Web (Dill, Eiron, Gibson, Gruhl & Guha, 2003; Maedche, 2002). �s more and more organizations in industry, academia and government publish their information (such as services and products) on the Web, how to add semantic annotation for machine-access and thus enhance the interoperability among these autonomous, distributed, and semantically heterogeneous information sources becomes more urgent. Usually, it is feasible to utilize weighted string-matching method to handle the explicit Automatically Integrating Heterogeneous ontologies from structured Web Pages
The research review of entrepreneur social network

As far as the new paradigm of social network was concerned, the paper began with the background and analyzed the definition of the concept from the standpoint of entrepreneurs. Then it outlined the core of the social network theory, summarized indicators and methods of measurement for the social network, reviewed the study of the social network as independent variables from the acquisition of information and resources. Finally the research directions of entrepreneur's social network were discussed. On account of the research purpose, this paper, according to the ability of entrepreneurs to know, to possess, to develop and employ the social network, classified and analyzed the social network theory that came from various fields, which layed a foundation for further research.
Knowledge management enablers, knowledge sharing and research collaboration: a study of knowledge management at research universities in Malaysia

Universities need to be aware of the impact of knowledge management (KM) in order to become world-class academic institutions. This research fills an unexplored gap in regards to the impact of KM enablers (i.e. trust, knowledge self-efficacy, reciprocal benefits, top management support, organizational rewards, organizational culture, KM system infrastructure and KM system quality, openness in communication, and face-to-face (F2F) interactive communication) on knowledge sharing (KS) that supports research collaboration by faculty members. No prior research has focused on the impact of KM enablers that influence research university members to share knowledge. A self-administered questionnaire was employed on members of five research universities in Malaysia to collect data; subsequently, 421 usable responses were analysed using partial least squares path modelling. KS by members was influenced by trust, organizational rewards, organizational culture, KM system quality, openness in communication, and F2F interactive communication; in addition, research collaboration was strongly influenced by KS. The KM–KS–collaboration model shows a KM influence of individual–organizational–technological–communication constructs that encourages KS by members to support research collaboration.
A Distributed Control Approach for Autonomic Performance Management in Cloud Computing Environment

In this paper, a distributed control based performance management approach is developed for a general class of web services deployed in a cloud computing environment. This approach is developed using interaction balance principles that has been applied for optimal control of large scale dynamic systems. The proposed approach can be applied to a general class of distributed computing systems where performance can be tuned by changing a finite set of control inputs. The developed distributed control structure is demonstrated by applying it to manage a distributed web service to minimize power consumption and maximize quality of service.
Aircraft attitude estimation from horizon video

Measurement of aircraft attitude is a necessary step for autonomous control of aircraft. Autonomous aircraft are useful for a range of military and civilian purposes. A method of very low computational complexity is presented that allows the pitch and roll angles of an aircraft to be measured onboard an unmanned aircraft from real-time video of the horizon. This method can be used for maintaining level flight, and provides a degree of automatic terrain avoidance.
The association between cannabis abuse and subsequent schizophrenia: a Swedish national co-relative control study

Background Although cannabis abuse (CA) is known to be associated with schizophrenia, the causal nature of this association is unclear, with prodromal effects complicating its interpretation. Method From Swedish national registry databases, we used a co-relative case–control design with full-sibling, half-sibling and first-cousin comparisons, alongside a general Swedish population sample. Using ICD codes, 5456 individuals with an initial diagnosis of schizophrenia (2000–2010) were matched with five schizophrenia-free controls. We further identified first-cousin, half-sibling and full-sibling pairs discordant for CA and statistically extrapolated results for discordant monozygotic (MZ) twins. Results Within the general Swedish population, CA was strongly associated with later schizophrenia [odds ratio (OR) 10.44, 95% confidence interval (CI) 8.99–12.11]. This association was substantially attenuated both by increasing temporal delays between CA exposure and schizophrenia diagnosis and by controlling for increasing degrees of familial confounding. Extrapolated discordant MZ pairs suggested that fully controlling for confounding familial factors reduced the association between CA and later schizophrenia to more modest levels (ORs of approximately 3.3 and 1.6 with 3- and 7-year temporal delays respectively). Opiate, sedative, cocaine/stimulant and hallucinogen abuse were also strongly associated with subsequent schizophrenia in the general population. After controlling for familial confounding, only cocaine/stimulant exposure remained associated. Conclusions CA has an appreciable causal impact on future risk for schizophrenia. However, population-based estimates of cannabis–schizophrenia co-morbidity substantially overestimate their causal association. Predictions of the cases of schizophrenia that might be prevented by reduced cannabis consumption based on population associations are therefore likely to be considerably overestimated.
Acute Kidney Injury Risk Factors For ICU Patients Following Cardiac Surgery: The Application of Joint Modeling

Background Admission to the ICU (intensive care unit) is frequently complicated by early AKI (acute kidney injury). The development of AKI following cardiac surgery is particularly associated with increased mortality and morbidity. According to AKIN (acute kidney injury network) criteria, UO (urinary output) is a predictor for AKI. Objectives The goal of this study was to determine the effects of some AKI risk factors on AKI and also to investigate changes in UO as a predictor of AKI using joint modeling. Patients and Methods In a retrospective study, 300 cardiac-operated patients, who had been admitted over a period of three years, were selected according to the consecutive sample selection method, using the ICU at Masih Daneshvari Hospital in Iran as a referral center. The random mixed effect model and the survival model were used to investigate UO changes and estimate the effect of UO and other risk factors on the hazard rate of AKI in a joint analysis. Results AKI occurred in 38.0% of patients. A significant decrease of UO occurred more often in female and infected patients, as well as those with a low DBP (diastolic blood pressure). The survival model showed that the risk of AKI in females, older patients and patients with low DBP, lower UO and with infection was higher (P = 0.001). Using joint modeling, the association parameter between the risk of AKI and UO was estimated (-0.3, P = 0.002). Conclusions Where there is a relationship between two longitudinal and survival responses, joint modeling can estimate it.
Dialogue act recognition for Chinese out-of-domain utterances using hybrid CNN-RF

Due to the short length, diversity, openness and colloquialism characteristic of out-of-domain (OOD) utterances, dialogue act (DA) recognition for OOD utterances in restricted domain spoken dialogue system remains a great challenge. This paper tackles this problem by proposing an effective DA recognition method using hybrid convolutional neural network (CNN) and random forest (RF). CNN acts as a feature extractor using Chinese character embeddings as original features. Then, RF classifier is trained on the learned features to perform DA recognition. The training dataset comes from a corpus of manually annotated Chinese OOD utterances, extracted from approximately 1500 conversations in a dialogue system which serves as a mobile phone recommendation assistant. We performed an evaluation on DA recognition for OOD utterances by logging the interactions of 15 subjects with the system. Experiment results justify the well performance of the proposed method.
A Uni ed Learning Framework Multisets Modeling Learning

Abstract A uni ed learning framework is proposed Its di erent special cases will automatically lead us to current existing major types of neural network learnings e g data clustering various PCA type self organizations and their localized extensions self organizing topological map as well as supervised learning for feedforward network and modular architecture Not only this new framework is useful for a deep understanding of the existing learnings but also it provides new insights that can guide the extensions of the existing learning methods With the new insights we have obtained several new intersting unsupervised learnings and introduced regularization or generalization to unsupervised learnings particularly proposed approaches for solving a classical hard problem how to decide the number of clusters in clustering analysis or competitive learning
Mimir: Bringing CTables into Practice

The present state of the art in analytics requires high upfront investment of human effort and computational resources to curate datasets, even before the first query is posed. So-called pay-as-you-go data curation techniques allow these high costs to be spread out, first by enabling queries over uncertain and incomplete data, and then by assessing the quality of the query results. We describe the design of a system, called Mimir, around a recently introduced class of probabilistic pay-as-you-go data cleaning operators called Lenses. Mimir wraps around any deterministic database engine using JDBC, extending it with support for probabilistic query processing. Queries processed through Mimir produce uncertainty-annotated result cursors that allow client applications to quickly assess result quality and provenance. We also present a GUI that provides analysts with an interactive tool for exploring the uncertainty exposed by the system. Finally, we present optimizations that make Lenses scalable, and validate this claim through experimental evidence.
Ultra low-voltage low-power CMOS 4-2 and 5-2 compressors for fast arithmetic circuits

This paper presents several architectures and designs of low-power 4-2 and 5-2 compressors capable of operating at ultra low supply voltages. These compressor architectures are anatomized into their constituent modules and different static logic styles based on the same deep submicrometer CMOS process model are used to realize them. Different configurations of each architecture, which include a number of novel 4-2 and 5-2 compressor designs, are prototyped and simulated to evaluate their performance in speed, power dissipation and power-delay product. The newly developed circuits are based on various configurations of the novel 5-2 compressor architecture with the new carry generator circuit, or existing architectures configured with the proposed circuit for the exclusive OR (XOR) and exclusive NOR ( XNOR) [XOR-XNOR] module. The proposed new circuit for the XOR-XNOR module eliminates the weak logic on the internal nodes of pass transistors with a pair of feedback PMOS-NMOS transistors. Driving capability has been considered in the design as well as in the simulation setup so that these 4-2 and 5-2 compressor cells can operate reliably in any tree structured parallel multiplier at very low supply voltages. Two new simulation environments are created to ensure that the performances reflect the realistic circuit operation in the system to which these cells are integrated. Simulation results show that the 4-2 compressor with the proposed XOR-XNOR module and the new fast 5-2 compressor architecture are able to function at supply voltage as low as 0.6 V, and outperform many other architectures including the classical CMOS logic compressors and variants of compressors constructed with various combinations of recently reported superior low-power logic cells.
The effect of workplace incivility on service employee creativity: the mediating role of emotional exhaustion and intrinsic motivation

Purpose This study aims to examine how workplace incivility (i.e. coworker and customer incivility) affects service employees’ creativity, specifically the way emotional exhaustion at work decreases their intrinsic motivation, and, in turn, damages service employees’ creativity. The purpose of this study, therefore, is to show the mechanism by which both coworker and customer incivility at work affects service employee creativity. Design/methodology/approach Service employees from a hotel in South Korea were surveyed using a self-administered instrument for data collection. Out of 450 questionnaires, a total of 281 usable questionnaires were obtained after list-wise deletion, for a 62.4 per cent response rate. Structural equation modeling analysis provided support for the hypotheses. Findings The results indicate a serial multiple mediator model in which both coworker and customer incivility increase service employees’ emotional exhaustion, which, in turn, reduces their intrinsic motivation at work and ultimately decreases their creativity. That is, the findings of this study reveal a negative relationship between workplace incivility (i.e. coworker and customer incivility) and service employees’ creativity that is fully and sequentially mediated by the service employees’ emotional exhaustion and intrinsic motivation. Research limitations/implications The use of cross-sectional self-reports potentially raises concerns about common method bias. Caution is recommended in reaching conclusions concerning the causal relationships between the variables, as the current study did not capture causality variation. For instance, it may be that emotional exhaustion from incivility gradually compounds over time, leading to a greater negative impact on service employees. In contrast, employees may develop strategies to cope with uncivil behavior over time, which attenuates the negative effects on service employees as time passes. A longitudinal design might offer an alternative to overcome this limitation in future research. Practical implications Considering the findings about the mediating effect of emotional exhaustion between workplace incivility and employee outcomes (i.e. intrinsic motivation and creativity), firms should consider establishing systematic institutional practices and policies to prevent employees from feeling emotionally exhausted from workplace incivility. Executive and senior management teams would benefit by instituting strict policies and regulations which nurture desirable behaviors among organizational members that protect victims of workplace incivility. Originality/value This study is the first to examine the relationship between workplace incivility and creativity. Moreover, the present study attempts to develop an understanding of the underlying mechanism through which both coworker and customer incivility negatively affect service employees’ creativity.
Install or invoke?: The optimal trade-off between performance and cost in the design of multi-standard reconfigurable radios

We approach the design of multi-standard reconfigurable radio as a choice between two extremes: (a) installing complex self-contained dedicated components that provide high performance at a high cost (“Velcro approach”), versus (b) supporting all targeted standards through primitive lower-level components, which reduces cost but maximises latency. To find the optimal trade-off between performance and cost, we build a mathematical model, in which we represent the design choices through a graph of progressively simpler functional modules. We illustrate our approach through a simple but realistic design example. Additionally, we show that this optimisation can be reformulated as a version of the well-known network design problem, which opens the door to a wealth of results, algorithms, and experience already available in the scientific literature. We identify some specific algorithms that can help us find the optimal design, and discuss limitations, and future directions of our research program.