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Small social entrepreneurs (SSEs) who operate in resource-constrained environments frequently use entrepreneurial bricolage (EB) to overcome such limitations. Research in social entrepreneurship mainly focuses on the outcomes of bricolage, with little knowledge about individual mechanisms that lead SSEs to use this approach. The authors fill this gap by investigating the role of entrepreneurial passion in fostering bricolage and the mediating effect of the sense of community.

To validate the theoretical model, the authors surveyed 279 SSEs operating in 7 African countries. The authors assessed the risk of common method bias, internal reliability and the validity of constructs and tested the hypotheses by performing linear regression analysis.

This study’s results demonstrate that passionate SSEs operating in resource-constrained contexts develop a sense of community by perceiving it as a valuable resource provider and that sense of community moves them to engage with EB.

Within the field of social entrepreneurship, this study examines the importance of a sense of community among SSEs; this evidence opens new avenues for research on drivers of small businesses operating in developing economies.

This study has practical implications for SSEs on implementing bricolage, and guidelines for governments, policymakers and NGOs in better developing their policies and programs considering the role of communities.

This study contributes to the literature by highlighting individual-level drivers of bricolage for SSEs operating in resource constraints, and revealing the relevance of the subjective view of the role of the community.

Differential pressure is an important technological parameter, one urgent task of which is control and measurement. To date, the lion’s share of research in this area has focused on the development and improvement of differential pressure sensors. The purpose of this paper is to develop a smart differential pressure sensor with improved operational and metrological characteristics.

The operating principle of the developed pressure sensor is based on the capacitive measurement principle. The measuring unit of the developed pressure sensor is based on a differential capacitive sensitive element. Programmable system-on-chip (PSoC) technology has been used to develop the electronics unit.

The use of a differential capacitive sensitive element allows the unit to compensate for the influence of interference (for example, temperature) on the measurement result. With the use of PSoC technology, it is also possible to increase the noise immunity of the developed smart differential pressure sensor and provide an unparalleled combination of flexibility and integration of analog and digital functionality.

The use of PSoC technology in the developed smart differential pressure sensor has many indisputable advantages, as the size of the entire circuit can be minimized. As a result, the circuit has improved noise immunity. Accordingly, the procedure for debugging and changing the software of the electronics unit is simplified. These features make development and manufacturing cost effective.

This paper aims to develop and psychometrically assess an individual’s perception of their work unit’s psychological sense of community (PSOCw) scale. This new scale is designed to capture the unique characteristics of a contemporary work unit that might include current practices such as hot-desking and workers located in physically separate locations.

This paper develops and then psychometrically accesses a new scale designed to better capture the psychological sense of community in a contemporary work unit.

The managerial implications for the PSOCw scale that is a psychometrically sound measure of work engagement, civility and collegiality in a work unit allow managers to audit a work unit based on these three dimensions and then take corrective actions to enhance the work unit’s sense of community.

The present study adapts previous work on PSOCw to a contemporary work environment where members of a work unit are often in physically separate locations and largely connect virtually.

The purpose of this study is to describe and explain the relationship between perceived social-organizational climate (PSOC), organizational citizenship behaviors (OCB) of other employees and innovative workplace behaviors (IWB) initiated and performed by employees. The mediating role of person-organization fit (P-O Fit) is tested within the relationship of PSOC, OCB and IWB.

The study was conducted anonymously on a group of 246 employees from 76 companies operating in Poland. Structural equation modeling (SEM) was used in the process of statistical analysis.

The research confirmed a significant statistical relationship between IWB and all studied variables: PSOC, OCB and P-O Fit. On the basis of the analysis, using SEM, it may be concluded that PSOC and OCB of other employees have an indirect influence on IWB, via P-O Fit.

A cross-sectional design and use of self-reported questionnaire data are limitations of this study.

The combination of variables presented in the research model may explain the significance of the chosen determinants of behaviors which are the key ones from the perspective of the company’s effectiveness and competitiveness on the market. The results of this research extend the knowledge in the area of relationships of innovation in the workplace with aspects of social functioning in the organization.

The purpose of this paper is to design an intelligent ECG classifier using programmable IC technologies to implement many functional blocks of signal acquisition and processing in one compact device. The main microprocessor also simulates the TSK neuro-fuzzy classifier in testing mode to recognize the ECG beats. The design brings various theoretical solutions into practical applications.

The ECG signals are acquired and pre-processed using the Field-Programmable Analog Array (FPAA) IC due to the ability of precise configuration of analog parameters. The R peak of the QRS complexes and a window of 300 ms of ECG signals around the R peak are detected. In this paper we have proposed a method to extract the signal features using the Hermite decomposition algorithm, which requires only a multiplication of two matrices. Based on the features vectors, the ECG beats are classified using a TSK neuro-fuzzy network, whose parameters are trained earlier on PC and downloaded into the device. The device performance was tested with the ECG signals from the MIT-BIH database to prove the correctness of the hardware implementations.

The FPAA and Programmable System on Chip (PSoC) technologies allow us to integrate many signal processing blocks in a compact device. In this paper the device has the same performance in ECG signal processing and classifying as achieved on PC simulators. This confirms the correctness of the implementation.

The device was fully tested with the signals from the MIT-BIH databases. For new patients, we have tested the device in collecting the ECG signals and QRS detections. We have not created a new database of ECG signals, in which the beats are examined by doctors and annotated the type of the rhythm (normal or abnormal, which type of arrhythmia, etc.) so we have not tested the classification mode of the device on real ECG signals.

The compact design of an intelligent ECG classifier offers a portable solution for patients with heart diseases, which can help them to detect the arrhythmia on time when the doctors are not nearby. This type of device not only may help to improve the patients’ safety but also contribute to the smart, inter-networked life style.

The device integrate a number of solutions including software, hardware and algorithms into a single, compact device. Thank to the advance of programmable ICs such as FPAA and PSoC, the designed device can acquire one channel of ECG signals, extract the features and classify the arrhythmia type (if detected) using the neuro-fuzzy TSK network in online mode.

This study aims to analyze the inertial weight factor value in the (PSO) algorithm and propose non‐linear weights with decreasing strategy to implement the improved PSO (IPSO) algorithm. Using various types of sensors, combined with ZigBee wireless sensor networks and the TCP/IP network. The GPRS/SMS long‐range wireless network will sense the measured data analysis and evaluation to create more effective monitoring and observation in a regional environment to achieve an Internet of Things with automated information exchange between persons and things.

This study proposes a wireless sensor network system using ZigBee (PSoC‐1605A) chip, sensor and circuit boards to constitute the IOT system. The IOT system consists of a main coordinator (PSoC‐1605A), smart grid monitoring system, robotic arm detection warning system and temperature and humidity sensor network. The hardware components communicate with each other through wireless transmission. Each node collects data and sends messages to other objects in the network.

This study employed IPSO to perform information fusion in a multi‐sensor network. The paper shows that IPSO improved the measurement preciseness via weight factors estimated via experimental simulations. The experimental results show that the IPSO algorithm optimally integrates the weight factors, information source fusion reliability, information redundancy and hierarchical structure integration in uncertain fusion cases. The sensor data approximates the optimal way to extract useful information from each fusion data and successfully eliminates noise interference, producing excellent fusion results.

Robotic arm to tilt detection warning system: Several geographic areas are susceptible to severe tectonic plate movement, often generating earthquakes. Earthquakes cause great harm to public infrastructure, and a great threat to high‐tech, high‐precision machinery and production lines. To minimize the extent of earthquake disasters and allow managers to deal with power failures, vibration monitoring system construction can enhance manufacturing process quality and stability. Smart grid monitoring system: The greenhouse effect, global energy shortage and rising cost of traditional energy are related energy efficiency topics that have attracted much attention. The aim of this paper is that real‐time data rendering and analysis can be more effective in understanding electrical energy usage, resulting in a reduction in unnecessary consumption and waste. Temperature and humidity sensor network system: Environmental temperature and humidity monitoring and application of a wide range of precision industrial production lines, laboratories, antique works of art that have a higher standard of environmental temperature and humidity requirements. The environment has a considerable influence on biological lifeforms. The relative importance of environmental management and monitoring is acute.

This paper improves the fixed inertial weight of the original particle swarm optimization (PSO) algorithm. An illustration in the paper indicates that IPSO applies the Internet of Things (IOT) system in monitoring a system via adjusted weight factors better than other existing PSO methods in computing a precise convergence rate for excellent fusion results.

This study examined the effectiveness of the Triple P‐Positive Parenting Program in a government child health service delivery context with Chinese parents in Hong Kong. Specifically, the study sought to identify pre‐intervention variables that might predict programme outcomes such as level of clinical improvement and programme completion. Participants were 661 parents of pre‐school and primary aged children participating in a group version of the Triple P‐Positive Parenting Program. There were significant decreases in disruptive child behaviours, levels of parenting stress, general stress and anxiety and an increase in parenting sense of competence. Greater change in reports of child behaviour problems was related to lower levels of family income, new immigrant family status, and higher pre‐intervention levels of parenting stress. The present study provides a profile of parents who are most likely to benefit from parent training programmes.

Work overload is an important and often singular objective for organizational interventions targeting nurse satisfaction and turnover in hospital settings around the world. The centerpiece of many such interventions involves the reassignment of nursing tasks to lesser licensed or unlicensed staff in order to provide immediate term relief to over extended professional nurses. These “Substitution Interventions” (SI) evolve from the diagnostic assumptions that “lightening the load” of professional nurses with more plentifully available “others” will provide, even in the absence of other changes, immediate relief to over-extended staff, reducing their growing sense of dissatisfaction and, thus, decreasing their desire or perceived need to look for another job. The purpose of this study is to critically examine the prevailing diagnostic assumptions that underlie “Substitution Interventions” (SI) and, propose and test in a sample of hospital care-givers (n=241) an alternative organization diagnostic model that may aid in understanding their propensity to fall short of management expectations.

Intelligent pneumatic actuator (IPA) is a new generation of actuator developed for Research and Development (R&D) purposes in the academic and industrial fields. The purpose of this paper is to show the application of optical encoder and pressure sensor in IPA, to develop a real-time model similar to the existing devices, and to assess the position control performance using a proportional-integrative (PI) controller and a bang-bang controller in real-time.

A micro optical encoder chip is used to detect cylinder rod position by reading constructed laser stripes on a guide rod, whereas a pressure sensor is used to detect the chamber pressure reading. To control the cylinder movements by manipulating pulse-width modulation (PWM) cycles, two unit valves of two ports and two positions were used. A PI controller and a bang-bang controller are used with suitable gain value to drive the valve using PWM to achieve the target actuator position.

The results show the experimental results of the closed-loop position tracking performance of the system using a data acquisition (DAQ) card over MATLAB software.

This paper presents a real-time model used to replace the microcontroller-based system from previous IPA design. The paper proposes two control strategies, PI and bang-bang, to control position using encoder and pressure reading.

This paper aims to address the reasons behind the varying levels of volatile conflict and peace as seen during the Arab Spring of 2011 to 2015. During this time, higher rates of conflict transition occurred than normally observed in previous studies for certain Middle Eastern and North African countries.

Previous prediction models decrease in accuracy during times of volatile conflict transition. Also, proper strategies for handling the Arab Spring have been highly debated. This paper identifies which countries were affected by the Arab Spring and then applies data analysis techniques to predict a country’s tendency to suffer from high-intensity, violent conflict. A large number of open-source variables are incorporated by implementing an imputation methodology useful to conflict prediction studies in the future. The imputed variables are implemented in four model building techniques: purposeful selection of covariates, logical selection of covariates, principal component regression and representative principal component regression resulting in modeling accuracies exceeding 90 per cent.

Analysis of the models produced by the four techniques supports hypotheses which propose political opportunity and quality of life factors as causations for increased instability following the Arab Spring.

Of particular note is that the paper addresses the reasons behind the varying levels of volatile conflict and peace as seen during the Arab Spring of 2011 to 2015 through data analytics. This paper considers various open-source, readily available data for inclusion in multiple models of identified Arab Spring nations in addition to implementing a novel imputation methodology useful to conflict prediction studies in the future.