Managerial Perceptions of the Impact of HRIS on Organizational Efficiency

This study evaluates the impact of the HRIS system on HR functions, time management, cost management, managerial satisfaction and organizational efficiency. A sample of 101 managers was drawn from a Municipality in South Africa using cluster sampling. Data was collected using a selfdeveloped, closed-ended questionnaire comprising of 28 items, the psychometric properties (validity, reliability) of which was statistically assessed using Factor Analysis and Cronbach’s Coefficient Alpha respectively. Data was analyzed using descriptive and inferential statistics. The results indicate that managers have a fairly positive view of the impact of the HRIS on organizational effectiveness with the greatest degree of confidence being placed on the impact of HRIS on time management and on HR functions. The results confirm that a well implemented and managed HRIS enables readily available information to be translated into more information sharing, greater knowledge transfer and management. Consequently, the HRIS has the potential to enhance the speed and quality of decision making and the realisation of the HR strategy, thereby enhancing organizational effectiveness

Taking the ‘human’ out of human resources in the fourth industrial revolution?

Doctoral Degree. University of KwaZulu-Natal, Durban.Human resource functions have been revolutionised in recent times because of the emergence of new advanced technologies, including artificial intelligence. However, evidence suggests that artificial intelligence and advanced self-learning machines threaten the global workforce entirely and eliminate human interference. From these perspectives, the current study aimed to examine the impact that AI and technological advancement have on human resource functions. An exploratory research design was adopted to understand the subject matter better. Moreover, mixedmethods research was employed to collect and analyse quantitative and qualitative data. The total population of the study was 46, which included the chief executive officer, senior management, and human resources. Given the small size of the population, the entire population (the consensus) was used as the sample. Multiple data collection instruments (questionnaire, interviews, and focus group interviews) were used to collect the data to enable the triangulation of results. Concerning the quantitative research, 40 questionnaires were sent to the respondents. However, only 29 completed and returned the questionnaires. Moreover, there were 6 participants in the interviews and focus group discussion. The quantitative data was analysed using Statistical Packages for the Social Sciences (version 27.0). The validity and reliability of the questionnaire were determined by computing factor analysis and Cronbach’s alpha coefficient respectively. On the other hand, the qualitative data was analysed manually using thematic analysis. The quantitative results indicated that the various constructs measured in the study were significant. The results of the Pearson’s moment correlation suggested no significant relationship between some of the variables, except human function will be transformed by artificial intelligence and the impact of artificial intelligence on skills set/competencies, and impact of artificial intelligence on skills set/competencies and the impact of artificial intelligence on business. In addition, the results of the analysis of variance suggested no significant difference in employees’ perceptions, varying by age, tenure, and race, respectively, regarding the current status of the use of artificial intelligence, advantages and disadvantages of the use of artificial intelligence, attitudes of human resource practitioners towards artificial intelligence, human resource function will be transformed by artificial intelligence, the impact of artificial intelligence on skills set/competencies. However, a significant difference existed in the employees’ perceptions, varying by race regarding the impact iv PUBLIC of artificial intelligence on business. Additionally, the sample t-test indicated a significant difference in the perceptions of male and female employees regarding all the variables measured in the study. On the other hand, the qualitative findings suggested that the adoption of AI in the HR department had impacted most of the human resource functions, including human case management, recruitment, learning, and chatbots. Furthermore, the qualitative findings revealed that the most significant advantage of using artificial intelligence was removing the mundane work and adding value. The study is unique as it sheds more light on how artificial intelligence has transformed most human resource functions. Therefore, the study recommends that organisations continue to invest in artificial intelligence

Narrowing the municipal funding gap: a metropolitan perspective in South Africa.

M. Com. University of KwaZulu-Natal, Durban 2014.Metropolitan municipalities play a vital role in service delivery at grassroots level. South Africans suffered from a lack of basic municipal services during the Apartheid era. Accordingly, post-apartheid municipalities underwent a radical transformation to start delivering such basic services as housing, water and electricity to all. Metropolitan governments were established to cover much wider areas to remedy the fragmentation and selective forms of service delivery of the past. However, a concomitant increase in the share of tax revenues has not been forthcoming to metropolitan municipalities to help them provide these services in a financially sustainable and viable manner. Accordingly, this study seeks to find out whether there is a funding gap in metropolitan councils, if so, what the quantum of the gap is, and what can be done to address such a funding gap. This is one of the most important issues facing local government today as it has a direct impact on service delivery, as well as the long-term sustainability and viability of municipalities. The study found that there is a huge funding gap in the three metropolitan councils namely, the City of Cape Town, Ethekwini Municipality, and the City of Tshwane. The key findings arising from the research indicate that: migration and urbanisation are having a huge impact on service delivery in metropolitan councils. The ever- increasing informal households are leading to growing service backlogs. Accordingly, whilst excellent progress has been made in rolling out service delivery, the influx of informal residents undermines the achievements made. This also impacts on the unemployment rate for the three metropolitan councils which is at an average of 24.3 % and is a major cause for concern and will continue to escalate if growth and job creation are not prioritised. Notwithstanding this, metropolitan councils are contributing significantly to the National and Provincial GDP at an average of 10% and 56% respectively. It is apparent that Metropolitan councils are the engines of growth in the economy and there needs to be due support given to them. In addition, there is very little scope to increase the current funding sources, service charges, (electricity, water, refuse and sanitation), rates, and grants as these have been maximised. There is also a major issue of affordability of further tariff increases. In addition the collection rates for all three metropolitan councils are above 95% Therefore, additional or new sources of revenue streams need to be explored, in particular development levies and a local business tax. As regards capital expenditure, a similar challenge of affordability and sustainability exists in meeting the service delivery backlogs and investing in new areas for growth. Whilst borrowings can be increased, this will impact on tariff increases and the affordability by consumers. A further key funding is that not all metropolitan councils are recording backlogs, rehabilitation, replacement and maintenance in a uniform way thus making comparisons difficult. Accordingly a financial model has been developed to ensure appropriate benchmarking using norms set by the World Bank. The model has also assisted in quantifying the funding gap. Accordingly, this study provides a major breakthrough in terms of an enhanced understanding of the funding of metropolitan councils and informing discussions by National Treasury and the Fiscal Finance Commission around the national fiscus, especially with regard to the funding gap and the need to review funding sources including grant funding that goes to metropolitan councils in future. The study found that whilst there is scope for improvement in terms of economies, efficiencies, value for money and productivity and an improvement in collection rates. new sources of revenue need to be identified. However, as recommended by the Fiscal and Finance Commission (FFC) and the South African Local Government Association (SALGA), a local business tax would be the most appropriate funding mechanism to make a meaningful impact on the funding gap as it has good reach and impact. Municipalities should re-look at Public Private Partnerships (PPP’s) as an alternate source of funding and reducing the cost to municipalities, development levies, additional grants, as well as alternate sources of funding as suggested by the FFC. Improved alignment of integrated development plans (IDP’s) to budgets, as well as ‘Smart City’ investments to stimulate growth and investment are also key issues that need to be taken cognisance of to ensure future viability and sustainability of metropolitan councils

CTQScorer: Combining Multiple Features for In-context Example Selection for Machine Translation

Large language models have demonstrated the capability to perform on machine translation when the input is prompted with a few examples (in-context learning). Translation quality depends on various features of the selected examples, such as their quality and relevance, but previous work has predominantly focused on individual features in isolation. In this paper, we propose a general framework for combining different features influencing example selection. We learn a regression model, CTQ Scorer (Contextual Translation Quality), that selects examples based on multiple features in order to maximize the translation quality. On multiple language pairs and language models, we show that CTQ Scorer helps significantly outperform random selection as well as strong single-factor baselines reported in the literature. We also see an improvement of over 2.5 COMET points on average with respect to a strong BM25 retrieval-based baseline.Comment: Accepted to EMNLP 2023 finding

IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

India has a rich linguistic landscape with languages from 4 major language families spoken by over a billion people. 22 of these languages are listed in the Constitution of India (referred to as scheduled languages) are the focus of this work. Given the linguistic diversity, high-quality and accessible Machine Translation (MT) systems are essential in a country like India. Prior to this work, there was (i) no parallel training data spanning all the 22 languages, (ii) no robust benchmarks covering all these languages and containing content relevant to India, and (iii) no existing translation models which support all the 22 scheduled languages of India. In this work, we aim to address this gap by focusing on the missing pieces required for enabling wide, easy, and open access to good machine translation systems for all 22 scheduled Indian languages. We identify four key areas of improvement: curating and creating larger training datasets, creating diverse and high-quality benchmarks, training multilingual models, and releasing models with open access. Our first contribution is the release of the Bharat Parallel Corpus Collection (BPCC), the largest publicly available parallel corpora for Indic languages. BPCC contains a total of 230M bitext pairs, of which a total of 126M were newly added, including 644K manually translated sentence pairs created as part of this work. Our second contribution is the release of the first n-way parallel benchmark covering all 22 Indian languages, featuring diverse domains, Indian-origin content, and source-original test sets. Next, we present IndicTrans2, the first model to support all 22 languages, surpassing existing models on multiple existing and new benchmarks created as a part of this work. Lastly, to promote accessibility and collaboration, we release our models and associated data with permissive licenses at https://github.com/ai4bharat/IndicTrans2

Enzalutamide induced non-ischemic cardiomyopathy. A case report and review of literature on anti-androgen therapy-related cardiovascular events

Prostate cancer has a very high prevalence among elder men, and this could potentially increase as longevity in many parts of the world is increasing. Early stages of prostate cancer can have surgical options, but the more advanced stages require some form of anti-androgen therapy. There are novel anti-androgen agents that were recently approved. Cardiovascular toxicity has been reported with some of these drugs. This is a novel report of likely cardiovascular toxicity due to Enzalutamide, which typically has a safer cardiovascular profile than Abiraterone.We describe a 72-year-old male with repeated recurrence of prostate cancer with metastasis. The second time it recurred was within 2 years of the 1st recurrence and was treated with Enzalutamide.However, within 2 weeks he developed systolic congestive heart failure that improved with stopping the drug and medical optimization.Literature review shows that Abiraterone has more cardiovascular side effects than Enzalutamide which more commonly causes hypertension. The timeline in our case suggests Enzalutamide causing congestive heart failure which is a novel finding. This finding warrants further research regarding the safety profile of novel anti-androgen therapy. This includes risk stratification for potential cardiovascular adverse events and risk/benefit analysis prior to initiating therapy. Data on cumulative dose accumulation and risks can also be an area of future research

A Case of HER2 Mutated Colorectal Cancer Treated Successfully With Fam-Trastuzumab Deruxtecan

Colorectal cancer is a malignant tumor arising from the inner lining of the colon or rectum and is the third most common cancer and the third leading cause of cancer-related deaths in the United States. Human epidermal growth factor receptor 2 (HER2) gene overexpressed or amplified colorectal cancer has shown treatment responses with HER2-directed therapies. We present a 78-year-old woman with metastatic colorectal cancer with a HER2 L726I mutation identified in tumor sequencing with amplification or overexpression of HER2. She had an excellent response to fam-trastuzumab deruxtecan. Our case is the first and most noteworthy case of a patient with metastatic colorectal cancer and a HER2 L726I mutation who achieved a remarkable clinical response to fam-trastuzumab deruxtecan

A case report of abscopal toxicity in a patient with lung adenocarcinoma

The abscopal effect describes tumor responses outside the irradiated field. The literature shows increased overall survival and response rates in patients receiving immunotherapy and radiation, likely from exaggerated abscopal effects. We present a 57-year-old woman with stage 4 lung adenocarcinoma who received treatment with a combination of chemotherapy and immunotherapy. She had disease progression on maintenance immunotherapy, confirming resistance. Palliative radiation to the sternal bone lesion resulted in a significant response to all areas of cancer, confirming the abscopal effect. Unfortunately, she developed severe pneumonitis; to our knowledge, this is the first case of abscopal lung toxicity

An unusual cause of chronic diarrhea in a Middle‐Aged adult: A diagnostic challenge

Key Clinical Message Diarrhea is a common symptom in medical practice that often gets overlooked. This article is intended to increase the awareness of physicians and other providers on a subtle but important cause of chronic diarrhea

High-performance computing for static security assessment of large power systems

Contingency analysis (CA) is one of the essential tools for the optimal design and security assessment of a reliable power system. However, its computational requirements rise with the growth of distributed generations in the interconnected power system. As CA is a complex and computationally intensive problem, it requires a fast and accurate calculation to ensure the secure operation. Therefore, efficient mathematical modelling and parallel programming are key to efficient static security analysis. This paper proposes a parallel algorithm for static CA that uses both central processing units (CPUs) and graphical processing units (GPUs). To enhance the accuracy, AC load flow is used, and parallel computation of load flow is done simultaneously, with efficient screening and ranking of the critical contingencies. We perform extensive experiments to evaluate the efficacy of the proposed algorithm. As a result, we establish that the proposed parallel algorithm with high-performance computing (HPC) computing is much faster than the traditional algorithms. Furthermore, the HPC experiments were conducted using the national supercomputing facility, which demonstrates the proposed algorithm in the context of N−1 and N−2 static CA with immense power systems, such as the Indian northern regional power grid (NRPG) 246-bus and the polish 2383-bus networks