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Microsign Products was established in 1979 by Mr. Nisheeth Mehta in the quiet town of Bhavnagar in Gujarat. The company commenced its operations to produce plastic fasteners, clips, clamps closures mainly used in electronic industries. In 2015, it had become the market leader in Western India and the whole and sole seller of many products such as adhesive clips and cables for large companies such as Honda, the Tatas, Siemens etc. Over the years Microsign diversified to meet the requirements of the automobile, defence, telecommunication, and packaging industries. Exhibit 1 shows the product list of Microsign. Operating from a single three storied building over the last 35 years, Microsign served clients from far and wide. The liaison office in Mumbai helped in the procurement of material and in marketing its products. In May 2015, Microsign moved to a 2000 square yard building on the outskirts of Bhavnagar. There was ample room for manufacturing, warehousing, shipping, and administration in the new premises of Microsign.

Present day organizations are considering workforce diversity as one of the main challenges in the human resource management. This study aims to find out the relationship between diversity management (DM) in the context of strategic human resource management (SHRM) and organizational performance (OP). An attempt is made to find out the mediation effect of cognitive diversity (CD) and affective diversity (AD) in the relationship between DM and OP.

The constructs investigated in the present study include DM, OP, CD and AD. Structural equation modeling has been used to test the model fit. The data was collected from 50 human resource professionals working in different organizations in the information technology (IT) sector in Bangalore, India. Confirmatory factor analysis has been used for establishing the reliability.

The results show that there exists a significant relationship between DM and OP. This significant positive relationship can be attributed to the mediating role of CD and significant negative relationship is because of the AD.

This study has several limitations. In this study, only three DM practices have been considered. The generalization of the results is another limitation as the study has been conducted in the IT sector in Bangalore, India. Similarly, sample size also affects the implications of an empirical study and sample size in this study is small. This study has investigated only the impact of two aspects of diversity, cognitive and affective, while neglecting the effect of communicational and symbolic processes.

The results indicate that organizations must consider that by providing intercultural trainings (ICTs), work–life balance (WLB) and work-time flexibility options, the negative aspects of diversity can be minimized. Moreover, organizations should encourage the task conflict which leads to better decision-making as well as creates a sense of group identification, which may help in the avoidance of negative consequences of AD.

This study is undertaken to find out the effect of certain diversity-oriented SHRM practices such as flexible working times, WLB, ICT and its impact on the OP in the Indian IT industry. This study has investigated the mediating role of CD and AD on the relationship between diversity-oriented SHRM practices and OP, which is the novelty of this study. Third, the study has been undertaken considering that there is a dearth of research on the impact of AD and CD on OP in the Indian context.

There is a paucity of comparative literature on pathway to care among patients with co-occurring disorders and those with only substance use disorders. This paper aims to compare the pathways to care among patients with co-occurring disorder and those with only substance use disorders.

A cross-sectional observational study was carried out on male treatment seekers at a tertiary care substance use disorder treatment center in India. Participants were recruited in two groups, those with co-occurring psychiatric and substance use disorders and those with only substance use disorders. The two groups were matched for age and socio-economic status.

A total of 189 subjects with co-occurring psychiatric and substance use disorders and 197 subjects with substance use disorders only were recruited. Psychiatric services were the most common first point of care. However, a larger proportion of the subjects in the co-occurring disorder group received the first care from faith healers, while a greater proportion received first care from the therapeutic communities in substance use disorder only group. Initial care was sought mostly following suggestion from the family members in both the groups. The time to treatment for substance use disorders did not differ between the two groups, though the treatment seeking for substance use disorder was more delayed than that of psychiatric disorder in the co-occurring disorder group.

The findings shed light on the pathway of care followed in India and is a matter of further research.

Expansion of services and dissemination of information about psychiatric disorders and substance use disorders can provide timely care to patients with substance use disorders and co-occurring disorders.

The findings have a social implication as well. More awareness is needed currently in India for timely treatment of dual disorders.

The paper is an original research by the authors. The data were collected from the participants who reported to the dual diagnosis clinic. The findings are important as they tell us about the current understanding of dual diagnosis by the general public.

The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.

Classical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.

The two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.

The present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.

The idea is to exploit the natural stability and performance of the human arm during movement, execution and manipulation. The purpose of this paper is to remotely control a handling robot with a low cost but effective solution.

The developed approach is based on three different techniques to be able to ensure movement and pattern recognition of the operator’s arm as well as an effective control of the object manipulation task. In the first, the methodology works on the kinect-based gesture recognition of the operator’s arm. However, using only the vision-based approach for hand posture recognition cannot be the suitable solution mainly when the hand is occluded in such situations. The proposed approach supports the vision-based system by an electromyography (EMG)-based biofeedback system for posture recognition. Moreover, the novel approach appends to the vision system-based gesture control and the EMG-based posture recognition a force feedback to inform operator of the real grasping state.

The main finding is to have a robust method able to gesture-based control a robot manipulator during movement, manipulation and grasp. The proposed approach uses a real-time gesture control technique based on a kinect camera that can provide the exact position of each joint of the operator’s arm. The developed solution integrates also an EMG biofeedback and a force feedback in its control loop. In addition, the authors propose a high-friendly human-machine-interface (HMI) which allows user to control in real time a robotic arm. Robust trajectory tracking challenge has been solved by the implementation of the sliding mode controller. A fuzzy logic controller has been implemented to manage the grasping task based on the EMG signal. Experimental results have shown a high efficiency of the proposed approach.

There are some constraints when applying the proposed method, such as the sensibility of the desired trajectory generated by the human arm even in case of random and unwanted movements. This can damage the manipulated object during the teleoperation process. In this case, such operator skills are highly required.

The developed control approach can be used in all applications, which require real-time human robot cooperation.

The main advantage of the developed approach is that it benefits at the same time of three various techniques: EMG biofeedback, vision-based system and haptic feedback. In such situation, using only vision-based approaches mainly for the hand postures recognition is not effective. Therefore, the recognition should be based on the biofeedback naturally generated by the muscles responsible of each posture. Moreover, the use of force sensor in closed-loop control scheme without operator intervention is ineffective in the special cases in which the manipulated objects vary in a wide range with different metallic characteristics. Therefore, the use of human-in-the-loop technique can imitate the natural human postures in the grasping task.

This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.