The interaction of artificial intelligence and design thinking In the development of HR and decision-making trends

This paper is a qualitative exploratory study, and a suggestive theory that aims to explore contemporary trends in HR policies in relation to technology. More precisely, the paper is a content-analysis research, aimed to explore the relationship between decision-making and data-driven business environment, and the extent to which AI and DT augment decision-making, if at all. Artificial intelligence is a physical concept which is used to describe and examine the impact that technology has on HRM practices. Design thinking is an abstract concept used to describe and examine the evolution of best leadership practices in terms of HRM processes. Before I started conducting this research, my focus was on AI, as a concept bound to change the face of traditional decision-making. Copious amount of data that is produced, extracted and stored daily, requires respective analysis. As such, I approached my respondents with the knowledge I gathered through personal research and during the creation of theoretical framework. As the research were advancing, I began to realise the extent to which these concepts provide insights into the relationship between the culture of design (thinking) and notion of artificial (intelligence) in decision-making. These two concepts were used to test the extent to which decision-making can be augmented with their use, and how they influence organisational hierarchy. From the side of the technology, AI is looking into the nature of Big Data and how it is used to exploit information for competitive HRM. DT is used to exploit the extent to which Big Data is used to broaden decision-making solutions. Together, this paper is examining the potential of these relationships, and if it in fact renders greater decision-making advantage, by accelerating the process with AI and disrupting traditional decision-making with DT. The paper used the Big Data Maturity Model (BDMM) to filter the findings and study this relationship accordingly. The model is comprised of five interconnected stages which test big data maturity of companies, as well as of their employees. Stages were divided according to goals of the paper and the two concepts. Moreover, the codes that were used to filter the findings served as additional differentiating points in the stages. The research provides insights into the synthesis of AI and DT and how they are perceived by decision-makers. The conclusions give an overview of advantages and challenges faced by HR managers when implementing AI and DT in decision-making and the subsequent room for research of this relationship

A BRIEF OVERVIEW OF STOCHASTIC INSTRUMENTS FOR MEASURING FLOWS OF ELECTRICAL POWER AND ENERGY

This paper gives a brief overview of three instruments suitable for measuring the flow of electrical power and energy. The first instrument is a single-phase power analyzer, while the other two instruments are double and quadruple three-phase power analyzers. In addition to overviewing these instruments, the paper presents a possible improvement of a quadruple three-phase power analyzer. The implementation of this improvement would make it possible to use a quadruple three-phase power analyzer as support for the phasor measurement unit

SERUM LEVELS OF INTERLEUKIN-6 AND TUMOR NECROSIS FACTOR-ALPHA IN EXACERBATION AND REMISSION PHASE OF SCHIZOPHRENIA

Background: The variations in proinflamatory cytokine levels have been associated with schizophrenia (SCH), duration of illness, psychopathology and treatment. The aim of the study was to investigate serum levels of interleukin-6 (IL-6) and tumor necrosis factoralpha (TNF-α) in schizophrenic patients during exacerbation and remission, and its association with course of illness and therapy. Subjects and methods: We measured serum levels of IL-6 and TNF-α in 43 schizophrenic patients in exacerbation and remission and compared them to 29 healthy controls, matched by sex, age, body mass index (BMI) and smoking habits. The severity of psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). Results: There was no difference in levels of IL-6 and TNF-α in exacerbation compared to remission in schizophrenic patients. IL-6 was higher and TNF-α was lower in schizophrenic patients in both exacerbation and remission in comparison with healthy controls. TNF-α in exacerbation was in negative correlation with IL-6 in remission. No statistical significance was found between levels of cytokines and sex, age, BMI, smoking habits, antipsychotic medication, duration of treatment and duration of illness. IL-6 levels were in positive correlation with the age of onset and the duration of untreated psychosis. In schizophrenic patients on adjunctive treatment with mood stabilizers, TNF-α levels increased in remission. Conclusion: Our results suggest that the connection between schizophrenia, cytokines and medication is multifaceted, and not necessarily linear. Adjunct mood stabilizers not only ameliorate psychopathology, but might convey immunomodulatory effects as well. Further longitudinal studies could elucidate potential beneficial effect of combined therapy in treatment of SCH

Integer codes correcting single asymmetric errors

This paper presents a class of integer codes capable of correcting single asymmetric errors. The presented codes are defined over the ring of integers modulo 2b– 1 and are constructed with the help of a computer. The results of an exhaustive search have shown that, for practical lengths up to 4096 bits, the proposed codes use the same number of check bits as the best systematic single asymmetric error-correcting codes (SAECCs). Besides this, it is found that for some lengths the presented codes are perfect. Finally, the paper shows that the encoding/decoding complexity of the proposed codes is notably lower than that of the best systematic SAECCs.Peer-reviewed manuscript: [https://hdl.handle.net/21.15107/rcub_dais_11654

Integer codes capable of correcting burst asymmetric errors

In this paper, we present a class of integer codes capable of correcting burst asymmetric errors. The presented codes are constructed with the help of a computer and have the potential to be used in various practical systems, such as optical networks and VLSI memories. In order to evaluate the performance of the proposed codes, the paper analyzes the probability of erroneous decoding for different bit error rates. The presented codes are also analyzed from a rate-efficiency point of view. The obtained results show that for many data lengths they require less check-bits than optimal burst error correcting codes