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The purpose of this paper is to explore the possibility that several workplace initiatives could stem the biases of recruiters against people who disclose or demonstrate diagnosed mental disorders. Specifically, in many nations, the level of unemployment in people who experience mental disorders is rife. Arguably, employers exhibit various biases that disadvantage people who disclose or demonstrate mental disorders; for example, recruiters tend to orient attention to the limitations, instead of the strengths, of job candidates. Because of these various biases, employers may reject applicants who acknowledge or manifest a mental disorder, even if these candidates would have been suitable.

To substantiate these premises, the authors analyzed established taxonomies of cognitive biases to identify which of these biases are likely to deter the employment of people with mental disorders. In addition, the authors applied several theories, such as the future self-continuity hypothesis, to uncover a variety of initiatives that could redress these biases in the future.

The authors uncovered five constellations of biases in recruiters that could disadvantage individuals who disclose or demonstrate mental disorders. Fortunately, consistent with the meaning maintenance model and cognate theories, when the vision and strategy of organizations is stable and enduring, these biases diminish, and people who report mental disorders are more likely to be employed.

This paper shows that initiatives that promote equality and stability in organizations could diminish stigma against individuals who experience mental disorders.

The purpose of this study is to investigate factors that influence the application of governance mechanism in family small and medium-sized enterprises (SMEs) in Indonesia.

This study used multiple regression analysis to examine the hypothesis. For data collection, questionnaires were distributed to 337 owners and managers of SMEs around 7 districts in Java Island in Indonesia.

The result indicates that uncertainty influences the application of formal governance in family SMEs in Indonesia. Meanwhile, asset specificity has impact on both formal and relational governance in the context of firms. Financial and non-financial objectives did not impact both formal and relational governance.

Though this research was carried out in a particular cultural context, this study was not specifically designed to examine the interaction between cultural variables and family corporate governance variables. In the future, there is need for a study that examines how culture can influence the practice of formal and relational governance in family business.

The study will give guidance to owners or managers of family business in terms of governance mechanism when uncertainty increases. This evidence suggests that family firms need to adopt formal governance within family firms when uncertainty exists.

The research finding indicated that uncertainty influenced the application of formal governance in family SMEs in Indonesia. This research finding suggests that family firms need to adopt formal governance when uncertainty exists. The adoption of formal governance, however, may implicate to some others organizational areas in family firms such as leadership, recruitment and selection and corporate culture.

This study is one of the few on family SMEs, which applied the transaction cost theory. Most of the studies use agency theory for investigating governance mechanism in the family business. This study is one of the few on family SMEs, which applied the transaction cost. This study provides an explanation about a factor that influences a family firm to choose formal and relational governance within the firm.

This paper discusses a new similarity measure for the anomaly‐based intrusion detection scheme using sequences of system calls. With the increasing frequency of new attacks, it is getting difficult to update the signatures database for misuse‐based intrusion detection system (IDS). While anomaly‐based IDS has a very important role to play, the high rate of false positives remains a cause for concern. Defines a similarity measure that considers the number of similar system calls, frequencies of system calls and ordering‐of‐system calls made by the processes to calculate the similarity between the processes. Proposes the use of Kendall Tau distance to calculate the similarity in terms of ordering of system calls in the process. The k nearest neighbor (kNN) classifier is used to categorize a process as either normal or abnormal. The experimental results, performed on 1998 DARPA data, are very promising and show that the proposed scheme results in a high detection rate and low rate of false positives.

The purpose of this paper is to study the way in which family ties influence the entrepreneurial preparedness of the diaspora family business owner.

In-depth interviews were carried out with 15 Cypriot family business owners hosted in various countries. The paper draws on social capital theory and uses an abductive analytical approach.

The findings of this paper illustrate that family ties coming from the family across borders play a significant role for diaspora family business owners’ entrepreneurial preparedness. Hidden values deriving from the interpersonal relationships within the family across borders drive the diaspora family business owners to learn upon self-reflection and become entrepreneurially prepared, led by both urgency and esteem.

This study provides practical implications for the entrepreneurial preparedness of diaspora family business owners and those who wish to become family business owners in a diaspora context.

This study contributes theoretically through the conceptualization of “family across borders social capital” and “diaspora entrepreneurial preparedness”. It also contributes empirically to the fields of diaspora family business, entrepreneurial learning and diaspora entrepreneurship through new knowledge regarding the role of family across borders social capital in the entrepreneurial preparedness of the diaspora family business owner.

The classical Preisach model and its modifications are one of the most generally applied simulations to model the behavior of magnetic materials, to describe hysteresis phenomena and different properties, as noncongruent minor loops, frequency dependence, temperature dependence, accommodation, and so on. Artificial neural networks (NNs) are widely used in fields of research where the solution of problems with conventional methods on traditional computers is very difficult to work out, for example system identification, modeling and function approximation. NNs can be considered as universal approximation for functions based on the theorem of Kolmogorov‐Arnold. In this paper a new NN model of scalar hysteresis characteristics is introduced. The examined method is built on the function approximation and continuous interpolation capability of NNs. The anhysteretic magnetization curve and a set of the ascending and a set of the descending first order reversal branches can be stored in a system of three neural networks. Different properties of magnetic materials can be simulated by a simple knowledge‐based algorithm. Value of differential susceptibility can be expressed in analytical form. Finally hysteresis characteristics predicted by the introduced model are compared with the results of the Preisach simulation.

The purpose of this study was to solve the problem of pose measurement of various parts for a precision assembly system.

A novel alignment method which can achieve high-precision pose measurement of microparts based on monocular microvision system was developed. To obtain the precise pose of parts, an area-based contour point set extraction algorithm and a point set registration algorithm were developed. First, the part positioning problem was transformed into a probability-based two-dimensional point set rigid registration problem. Then, a Gaussian mixture model was fitted to the template point set, and the contour point set is represented by hierarchical data. The maximum likelihood estimate and expectation-maximization algorithm were used to estimate the transformation parameters of the two point sets.

The method has been validated for accelerometer assembly on a customized assembly platform through experiments. The results reveal that the proposed method can complete letter-pedestal assembly and the swing piece-basal part assembly with a minimum gap of 10 µm. In addition, the experiments reveal that the proposed method has better robustness to noise and disturbance.

Owing to its good accuracy and robustness for the pose measurement of complex parts, this method can be easily deployed to assembly system.

The purpose of this paper is to explore and encapsulate the enablers that can facilitate education for sustainable development in higher education (HE). The study also aims to understand the interdependence between the enablers.

The study adopts the total interpretive structural modelling approach to comprehend the interaction and transitivity between the enablers. Cross-impact multiplication matrix analysis was applied to rank the enablers and classify them on the basis of the driving and dependence power into dependent, autonomous, independent and linkage enablers.

An extensive literature review and expert opinion helped in identifying 10 enablers that can promote sustainability in higher education. The structural model revealed government policies, media, accreditation/sustainability audit, sustainability leadership and institutional commitment as the crucial enablers that can drive sustainability and activate the enablers with high dependence and low driving power.

The results of this study will assist the policymakers and management of universities and colleges in understanding important factors that can facilitate sustainability in higher education. Universities and colleges to incorporate sustainability in their system need to transform not only the core higher education activities of learning and teaching, research and engagement, also the way the colleges operate its culture, governance, structure and how it supports the staff and students.

So far, research on sustainability in higher education has looked into each factor in isolation. This research provides a comprehensive view of the factors and has attempted to establish a multidirectional interplay between factors facilitating sustainability in higher education (SHE).

Surface curvature is needed to analyze the range data of real objects and is widely applied in object recognition and segmentation, robotics, and computer vision. Therefore, it is not easy to estimate the curvature of the scanned data. In recent years, machine learning classification methods have gained importance in various fields such as finance, health, engineering, etc. The purpose of this study is to classify surface points based on principal curvatures to find the best method for determining surface point types.

A feature selection method is presented to find the best feature vector that achieves the highest accuracy. For this reason, ten different feature selections are used and six sample datasets of different sizes are classified using these feature vectors.

The author examined the surface examples based on the feature vector using the machine learning classification methods. Also, the author compared the results for each experiment.

To the best of the author's knowledge, this is the first study to examine surface points according to principal curvatures using machine learning classification methods.

Online knowledge integration has been an important concern of the online knowledge community as it can lead to various positive outcomes of online knowledge coproduction. This paper identifies online knowledge integration factors by considering group heterogeneity and group interaction process.

Based on the categorization-elaboration model (CEM) and interactive team cognition (ITC) theory, a research model that reflects the antecedent's factors and mediating factors of online knowledge integration was developed and empirically examined based on data collected from 2,339,836 data extracted from Wikipedia.

Group interaction process plays an essential mediator role in online knowledge integration. Group knowledge heterogeneity negatively influences online knowledge integration and group experience heterogeneity positively, and they both positively promote online knowledge integration through group interaction process with different paths.

Our research concerns the OKC context in one setting (Wikipedia). We expect that the results will generalize to other OKC platforms.

The findings of the study could assist the online knowledge community's organizers to understand the motivational mechanisms of online knowledge integration. Group interaction process could be regarded as the key role to promote group wisdom and maintain group independence.

We advance the understanding of the online knowledge integration and gain a richer understanding of the importance of group interaction independence for online knowledge integration based on the agreement of group wisdom. It suggested keeping group interaction independence is an important aspect for highly online knowledge integration among heterogeneity groups.

This study extends CEM and ITC theory to the domain of knowledge integration context and finds the mechanism between group heterogeneity and online knowledge integration by introducing the group interaction process.

The purpose of this paper is to longitudinally test the propositions of the Electronic Market Hypothesis (EMH) within the context of the US home mortgage industry.

The paper uses a deductive, positivist case study, through a systematic examination of “texts” in the trade press over three time periods: 1995‐1999, 2000‐2002, and 2003‐2007.

EMH propositions, while generally not found to be valid in the early years, were more consistent with evidence in the home mortgage industry in the later period.

Throws fresh light on the debate between the appropriateness and the inappropriateness of the EMH as a core theory explaining the influence of Information Technology on market and industry structures.

Designing of corporate strategies to foster efficient market mechanisms.

Using a relatively uncommon (analysis of primary data from trade press articles) qualitative research methodology which could serve as a guideline for future research. This approach offers opportunities to use various trade press sources to perform studies on the effects of IT on people, such as analyzing how IT departments are adapting their governance practices as workers increasingly use personal computing devices to access organizational assets (e.g., networks, applications, and data).