Relationship between core self-evaluation and innovative work behavior: mediating effect of affective organizational commitment and moderating effect of organizational learning capacity

Focusing on employees, this study examined the respective mediating and moderating effects of affective organizational commitment and organizational learning capacity in the relationship between core self-evaluation and innovation work behavior. We collected data via an online survey from 330 office workers at midsize and large companies in a metropolitan area of South Korea. The results of analyzing the data using PROCESS macro were as follows: (1) core self-evaluation was positively related to innovative work behavior; (2) the relationship was mediated by affective organizational commitment; (3) the relationship was buffered by organizational learning capacity, such that a higher level of organizational learning capacity diminished the impact of core self-evaluation on innovative wok behavior; and (4) the conditional effect of core self-evaluation on innovative work behavior existed only in the group of a low level of organizational learning capacity. Based on these findings, we suggested implications for theory building, research, and practice

The Design and Optimization of a Compressive-Type Vector Sensor Utilizing a PMN-28PT Piezoelectric Single-Crystal

Underwater sensors that detect the distance and direction of acoustic sources are critical for surveillance monitoring and target detection in the water. Here, we propose an axial vector sensor that utilizes a small (~1 cm3) compressive-type piezoelectric accelerometer using piezoelectric single crystals. Initially, finite element analysis (FEA) was used to optimize the structure that comprised piezoelectric Pb(Mb1/3Nb2/3)O3-28%PbTiO3 single crystals on a tungsten seismic mass. The receiving voltage sensitivity (RVS) was enhanced through geometric optimization of the thickness and sensing area of the piezoelectric material and the seismic mass. The estimated maximum RVS of the optimized vector sensor was −212 dB. FEA simulations and practical measurements were used to verify the directivity of the vector sensor design, which exhibited a dipole pattern. The dipole beam pattern was used to obtain cardioid patterns using the simulated and measured results for comparison. The results clearly showed the feasibility of using the proposed piezoelectric single-crystal accelerometer for a compressive-type vector sensor. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.1

Reversal of the Lattice Structure in SrCoOx Epitaxial Thin Films Studied by Real-Time Optical Spectroscopy and First-Principles Calculations

Using real-time spectroscopic ellipsometry, we directly observed a reversible lattice and electronic structure evolution in SrCoOx (x = 2.5-3) epitaxial thin films. Drastically different electronic ground states, which are extremely susceptible to the oxygen content x, are found in the two topotactic phases: i.e., the brownmillerite SrCoO2.5 and the perovskite SrCoO3. First-principles calculations confirmed substantial differences in the electronic structure, including a metal-insulator transition, which originate from the modification in the Co valence states and crystallographic structures. More interestingly, the two phases can be reversibly controlled by changing the ambient pressure at greatly reduced temperatures. Our finding provides an important pathway to understanding the novel oxygen-content-dependent phase transition uniquely found in multivalent transition metal oxidesclose1

Early Seizure Detection by Applying Frequency-Based Algorithm Derived from the Principal Component Analysis

The use of automatic electrical stimulation in response to early seizure detection has been introduced as a new treatment for intractable epilepsy. For the effective application of this method as a successful treatment, improving the accuracy of the early seizure detection is crucial. In this paper, we proposed the application of a frequency-based algorithm derived from principal component analysis (PCA), and demonstrated improved efficacy for early seizure detection in a pilocarpine-induced epilepsy rat model. A total of 100 ictal electroencephalographs (EEG) during spontaneous recurrent seizures from 11 epileptic rats were finally included for the analysis. PCA was applied to the covariance matrix of a conventional EEG frequency band signal. Two PCA results were compared: one from the initial segment of seizures (5 sec of seizure onset) and the other from the whole segment of seizures. In order to compare the accuracy, we obtained the specific threshold satisfying the target performance from the training set, and compared the False Positive (FP), False Negative (FN), and Latency (Lat) of the PCA based feature derived from the initial segment of seizures to the other six features in the testing set. The PCA based feature derived from the initial segment of seizures performed significantly better than other features with a 1.40% FP, zero FN, and 0.14 s Lat. These results demonstrated that the proposed frequency-based feature from PCA that captures the characteristics of the initial phase of seizure was effective for early detection of seizures. Experiments with rat ictal EEGs showed an improved early seizure detection rate with PCA applied to the covariance of the initial 5 s segment of visual seizure onset instead of using the whole seizure segment or other conventional frequency bands

Perceived managerial and leadership effectiveness in a Korean context: An indigenous qualitative study

Multinational corporations (MNCs) across the world have sent an increasing number of managers abroad to leverage unprecedented opportunities in the era of globalization. However, their failure rate has been above 33% for decades, resulting in substantial costs (Puck, Kittler, & Wright, 2008). One of the primary reasons for this failure is a lack of understanding of the national and organizational cultures within the host countries (Festing & Maletzky, 2011). For example, while a number of MNCs have entered the Korean market, several such as Yahoo, Motorola, and Walmart have failed and withdrawn due to the companies’ lack of adjustment to the Korean cultural context (Choe, 2006; Woo, 2013). In spite of the significance of culturally embedded practices, most researchers who have explored management and leadership in Asian countries, whether they were Western or indigenous researchers, have implemented studies using extant Western management and leadership theories derived within the Western cultural context (Leung, 2007; Tsui, 2006). Numerous scholars have claimed that this could be problematic because the findings of such studies may not be applicable to non-Western countries (Li, 2012; Liden & Antonakis, 2009), and may fail to provide insights and understanding of novel contexts or to reveal indigenous aspects of management and leadership (Tsui, 2007). Consequently, there have been increasing calls for indigenous management and leadership research within Asian countries (see Li et al., 2014; Lyles, 2009; Tsui, 2004; Wolfgramm, Spiller, & Voyageur, 2014). Over the past 30 years, managerial effectiveness and leadership effectiveness have been substantially neglected areas of management research (Noordegraaf & Stewart, 2000; Yukl, Gordon, & Taber, 2002). In addition, there has been little agreement on what specific behaviors distinguish effective managers from ineffective ones. Furthermore, more research is needed to examine the managerial and leadership behaviors that are critical for shaping the performance of individuals, groups and organizations (see Borman & Brush, 1993; Cammock, Nilakant & Dakin, 1995; Mumford, 2011; Noordegraaf & Stewart, 2000; Yukl et al., 2002). While most of the research related to managerial and leadership effectiveness has been conducted in the U.S., the few notable non-U.S. studies include that of Cammock et al. (1995) in New Zealand who developed a behavioral lay model of managerial effectiveness using the repertory grid technique. Another notable exception is the cumulative series of perceived managerial and leadership effectiveness studies conducted by Hamlin with various indigenous co-researchers in Western and non-Western countries (see Hamlin & Patel, 2012; Ruiz, Wang, & Hamlin, 2013) using Flanagan’s (1954) critical incident technique (CIT)

Sensing Coverage-Based Cooperative Spectrum Detection in Cognitive Radio Networks

With the advancement of the Internet of Things (IoT), conventional principles of spectrum allocation cannot mitigate spectrum depletion so that a cognitive radio technology is proposed as a solution. The hidden primary user (PU) problem, however, is a critical issue in cognitive radio networks, because spectrum sensing nodes (SNs) can misclassify spectrum occupancy. To cope with this, machine learning-based cooperative spectrum sensing schemes (CSSs) have been proposed. The CSSs without considering the node placement, however, are still faced with the hidden PU problem. In this paper, we present how to place SNs to guarantee the performance of machine learning-based CSSs. We verify that the hidden PU problem makes the overlap of data distribution, which deteriorates the spectrum sensing ability. Based on the Kullback-Leibler divergence, analytical expressions for the spectrum sensing coverage of a single SN are derived. Then, we propose a strategy on how to place a few SNs to cover the whole area of the PU and prove the feasibility of our proposal by the experiment results.1

A Target-Less Vision-Based Displacement Sensor Based on Image Convex Hull Optimization for Measuring the Dynamic Response of Building Structures

Existing vision-based displacement sensors (VDSs) extract displacement data through changes in the movement of a target that is identified within the image using natural or artificial structure markers. A target-less vision-based displacement sensor (hereafter called “TVDS”) is proposed. It can extract displacement data without targets, which then serve as feature points in the image of the structure. The TVDS can extract and track the feature points without the target in the image through image convex hull optimization, which is done to adjust the threshold values and to optimize them so that they can have the same convex hull in every image frame and so that the center of the convex hull is the feature point. In addition, the pixel coordinates of the feature point can be converted to physical coordinates through a scaling factor map calculated based on the distance, angle, and focal length between the camera and target. The accuracy of the proposed scaling factor map was verified through an experiment in which the diameter of a circular marker was estimated. A white-noise excitation test was conducted, and the reliability of the displacement data obtained from the TVDS was analyzed by comparing the displacement data of the structure measured with a laser displacement sensor (LDS). The dynamic characteristics of the structure, such as the mode shape and natural frequency, were extracted using the obtained displacement data, and were compared with the numerical analysis results. TVDS yielded highly reliable displacement data and highly accurate dynamic characteristics, such as the natural frequency and mode shape of the structure. As the proposed TVDS can easily extract the displacement data even without artificial or natural markers, it has the advantage of extracting displacement data from any portion of the structure in the image

Non-Iterative Optimal Design Method Based on LM Index for Steel Double-Beam Floor Systems Reinforced with Concrete Panels

Steel double-beam floor systems reinforced with concrete panels can improve the structural and environmental performance of buildings by reducing moment demands and embodied CO2 emissions. However, for steel double-beam floor systems, a time-consuming iterative analysis is required to derive an optimal design proposal owing to the rotational constraints in the composite joints between the concrete panel and steel beams. In this study, a non-iterative optimal design method using the LM index is proposed to minimize the embodied CO2 emissions of steel double-beam floor systems. The LM index is a measure that can be used to select the optimal cross-section of the steel beams considering the decreased moment capacity according to the unbraced length. The structural feasibility of the proposed design method was verified by investigating whether safety-related constraints were satisfied by the LM index with respect to the design variables under various gravity loads. The applicability of the proposed optimal design method is verified by comparing the embodied CO2 emissions derived from the proposed and code-based design methods. Applicable design conditions were presented based on the LM index to aid engineers. The proposed design method can provide environmentally-optimized design proposals to ensure structural safety by directly selecting the LM index of steel beams

Development of Marker-Free Night-Vision Displacement Sensor System by Using Image Convex Hull Optimization

Vision-based displacement sensors (VDSs) have the potential to be widely used in the structural health monitoring field, because the VDSs are generally easier to install and have higher applicability to the existing structures compared to the other conventional displacement sensors. However, the VDS also has disadvantages, in that ancillary markers are needed for extracting displacement data and data reliability is significantly lowered at night. In this study, a night vision displacement sensor (NVDS) was proposed to overcome the aforementioned two limitations. First, a non-contact NVDS system is developed with the installation of the infrared (IR) pass filter. Since it utilizes the wavelength of the infrared region and it is not sensitive to the change of a visible ray, it can precisely extract the shape information of the structure even at night. Second, a technique to extract the feature points from the images without any ancillary marker was formulated through an image convex hull optimization. Finally, the experimental tests of a three-story scaled model were performed to investigate the effectiveness of proposed NVDS at night. The results demonstrate that the NVDS has sufficiently high accuracy even at night and it can precisely measure the dynamic characteristics such as mode shapes and natural frequencies of the structure. The proposed system and formulation would extend the applicability of vision sensor not only into night-time measure but also marker-free measure