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Adoption of enterprise risk management erm practices in the zimbabwean banking sector
Corporate failures that occurred in the mid-1990s as well as the global financial crisis that unfolded in the US in 2007 and subsequent banking crises in many countries underscored the need for banking institutions to develop and implement robust risk management systems and controls to prevent the occurrences of such crises. Enterprise risk management (ERM) has emerged as the best practice approach that provided banks with means for mitigating and controlling risks giving rise to such financial crises. Attempts have been made to find out the factors driving the implementation of ERM and the majority of these studies had conflicting newlineconclusions on the effect of some of these factors. Further, weaknesses were noted in variables used by researchers as proxies for ERM adoption. It was noted that several studies used the appointment of a chief risk officer as a variable representing ERM adoption while a number of other researchers focused on surveys or renowned frameworks such as COSO to ascertain the extent of adoption of ERM. These approaches however, had shortcomings. This study therefore sought to address some of the above gaps in literature. The purpose of this study is to determine the degree of adoption of ERM newlinepractices as well to examine factors (adequacy of risk governance structure, newlinequality of organizational culture, intensity of regulatory environment and size of the bank) influencing the adoption and implementation of ERM by banks in Zimbabwe. A mixed method approach was utilized in this study. The population of the study comprised of 18 commercial banks which have been operating in Zimbabwe since the adoption of the multi-currency system in 2009. Respondents for the study were selected using the purposive sampling approach. This was to ensure the respondents had the right experience and expertise to answer questions on enterprise risk management practices newlinewithin their respective banks. -
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Community Consciousness and The Construction of Social Honour : A Study Among The Kurds in Finland
Research on honour has recently been overshadowed by discussions surrounding honour-related violence (HRV), particularly honour killings. Typically, inquiries into how the concept of honour, often associated with violent acts, is formed, and expressed on personal or communal levels remain unanswered or are only superficially explored. This study aims to uncover the social structures underlying the concept of honour, demonstrate its manifestation through social interactions, and elucidate how individuals respond to threats against their honour. Because of the many tragic instances of HRV within Kurdish diaspora communities, Kurds and Kurdish culture frequently feature in discussions concerning this phenomenon. Therefore, data for current research has been collected from Kurds living in the diaspora, specifically in Finland. The data were elicited through a combination of methods to be as comprehensive as possible. This included 24 semi-structured interviews with individual participants and four Focus Group Discussions involving 16 participants. A closer look at the data shows that the construction of Kurdish honour is based on a complex interaction of social structures. These structures can be broken down into three key elements: institutional, relational, and embodied factors. In this regard, the research has identified six structural components. The study demonstrates that the intensity of honour-related conflicts stems from an intricate interplay of structural factors. However, the relative weight of these factors determines the flashpoints of tension. Through the lens of structuration theory, the study demonstrates the role of everyday practices and dynamic social factors in shaping individuals' discursive consciousness around honour. Individuals' conceptualization of honour may sometimes diverge from its practical application, leading to a space for social negotiation where honour undergoes continuous reshaping into a dynamic equilibrium that impacts daily life. It's essential to recognize that this equilibrium varies among individuals. However, a threat to honour can prompt varying facework procedures, contingent upon individual characteristics and community expectations. Current Inquiry uncovers six distinct behavioural patterns individuals exhibit during a crisis of honour. The investigation of the participants' narratives reveals a diverse Kurdish culture, as evidenced by their different perceptions about the tolerable thresholds of honour violations and contradictory discourses concerning honour. The final significant finding is that the fear of dishonour typically outweighs the desire for honour among the Kurds, as indicated by both daily language use and chronological analysis of conflict cases. This observation holds significant implications, not only for reevaluating normative terminology but also for informing social and political preventive measures. -
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Role of Financial Literacy and Digital Financial Inclusion on Sustainable Development Among The Mao-Naga Tribe of Northeast India
This research empirically analyses the influence of financial literacy and digital financial inclusion on sustainable development. The notion of financial newlineliteracy, adopted from the Organisation for Economic Co-operation and Development, combines financial awareness, attitude, knowledge, and behaviour to achieve financial well-being. Digital financial inclusion is the process by which individuals or households in the underserved or unprivileged section of society have access to formal financial services through innovative digital technologies. The main features of digital financial inclusion include reduction of costs, security, ease of access, usefulness, and actual usage of digital financial services. The current study collected data from the Mao-Naga tribe of Manipur and newlineNagaland, Northeast India using a convenient and purposive sampling method. The research method is quantitative in nature, and primary data were collected from adult individuals who were 18 years old or above. These respondents were eligible and able to manage their own bank accounts independently. The study has a crosssectional time horizon with a deductive approach. The data consisted of 1147 samples of Mao-Naga tribe adults using a structured questionnaire on a seven-point newlineLikert scale. The statistical technique of Statistical Packages of Social Science newline(SPSS) software was utilised to ascertain the descriptive result of the study. The newlinehypothesis testing was conducted using the Partial Least Square Structural Equation newlineModelling (PLS-SEM) statistical model. The SMART-PLS 4.0 software was employed to test the hypotheses of PLS-SEM, explanatory variance, effect size, PLS predict, and importance-performance map analysis (IPMA). Financial literacy and sustainable development were analysed from a reflective-formative approach of higher-order constructs. This research indicates that financial literacy and digital financial inclusion can positively influence sustainable development among the Mao-Naga tribe. -
Strategy formulation and implementation in the zimbabwean food manufacturing sector
This study focused on examining the influence of strategy formulation and implementation on the performance and competitive advantage of the foodmanufacturing companies in Zimbabwe. The study was prompted by the fact that newlinestrategy is essential in every organisation and that competing in the market is like newlinewar, you have injuries and casualties and the best strategy wins . More so, even though the food-manufacturing companies are essential to the Zimbabwean economy, there has been limited research on the area of strategy formulation and implementation. The study applied both quantitative and qualitative approaches because looking at the same problem from several viewpoints is an excellent way to verify data and come up with interpretation and conclusions. It is in view of this fact that the researcher used the triangulation approach, which is a combination of both philosophies, qualitative and quantitative data. The research was a survey because it allowed the research to collect data from a sizeable number of participants in 10 foodmanufacturing companies in Zimbabwe. The researcher used personal judgement in selecting the companies to be part of the study. The data was collected from directors and managerial employees, who are largely involved in the process of strategy formulation and implementation. The researcher used the questionnaires and the indepth interviews as research instruments. SPSS was the quantitative data analysis and qualitative data analysis was using thematic analysis. The study found out that foodmanufacturing companies in Zimbabwe were facing performance related challenges and there were mixed responses on the extent to which they were failing to meet financial, customer, internal business process improvement, and learning and growth targets. The food-manufacturing companies implemented marketing, human resource, financial and operations strategies but were not successful in their endeavours. -
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Respiratory Motion Prediction of Lung Tumor Using Artificial Intelligence
Managing respiratory motion in radiotherapy for lung cancer presents a formidable and newlinepersistent challenge. The inherent dynamic movement triggered by respiration introduces a notable degree of uncertainty in target delineation, impacting the precision of image-guided radiotherapy. Overlooking the impact of respiratory motion can lead to the emergence of artifacts in images during image acquisition, resulting in inaccuracies in tissue delineation. Moreover, the motion between treatment fractions can induce blurriness in the dose distribution within the treatment process, thereby introducing geometric and dosimetric uncertainties. Additionally, inter-fraction motion can result in the displacement of the distribution of administered doses. Given these complexities, the precise prediction of tumor motion holds the utmost importance in newlineelevating the quality of treatment administration and minimizing radiation exposure to healthy tissues neighboring the pertinent organ during radiotherapy. Nonetheless, achieving the desired level of precision in dose administration remains a formidable task due to the inherent variations in internal patient anatomy across varying time scales and magnitudes. While notable advancements have been witnessed in radiotherapy, attributed to innovations like image guidance tools, which have streamlined treatments, the challenge of accommodating lung tumor motion remains critical, particularly in cases related to newlineradiotherapeutic intervention. Substantial limitations endure despite integrating respiratory-gated techniques in radiation oncology to manage lung tumor motion. Moreover, lung cancer prognosis remains low, irrespective of the recent advancements in radiotherapy. The practice of expanding newlinetreatment margins from the Clinical Treatment Volume (CTV) to encompass the Planning newlineTreatment Volume (PTV) has been adopted as a strategy to amplify treatment outcomes. newlineHowever, this strategy necessitates a trade-off, as it inevitably exposes larger volumes of healthy tissues to radiation. -
Analysis of native advertising on buzzfeed and its impact on the brand image of 7 companies /
In today's world, the social web space has become a competitive platform for companies engaged in a plethora of activities to promote and sell their products and, more importantly, create a brand image. In tandem with the rapid development that has been observed in social media, the advertising industry has also evolved to accommodate the needs of the internet. Native advertising has emerged as a viable and lucrative alternative for companies to communicate with their audiences. -
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Computational Methods for Detection and Recognition of Coronary Artery Stenosis in Angiogram Images
Coronary Artery Disease (CAD) is caused by stenosis of the coronary artery's lumen. This heart disease is one of the reasons for the highest mortality worldwide. This illness manifests as stenosis or plaque in the coronary arteries and causes atherosclerosis. It damages or clogs the heart arteries, causing a lack of blood flow to the heart muscles and leading to a heart attack. There are different medical modalities to diagnose the heart artery disease. A standard method used by the cardiologist to diagnose the severity of this disease is coronary angiography. An X-ray machine is used to capture the angiogram image at various angles during cardiac catheterization. Experts examine the data and offers different opinions. owever, most of the angiogram videos consist of unclear images with artifacts, and because of the complex structure of the arteries, medical experts fail to get accurate information about the damages and blockages in arteries. Based on the cardiologist's suggestions, a computational model is proposed as a secondary method to detect and recognize the stenosis level from the coronary angiogram images. The proposed model is Coronary Artery Stenosis Detection Using Digital Image Processing (CASDDIP). The proposed research model/framework can identify the stenosis in the cardiogram image with good accuracy of 98.06% precision. This proposed research experimentation can be compared with existing literature methods which outperforms compared to other methods using real time dataset. A dataset, such as angiogram videos and images of patients under varying age groups, is used to train the model. These videos are acquired from the healthcare center with due consent. The proposed CASDDIP model consists of four modules: Keyframe extraction and preprocessing Coronary Artery Segmentation Feature extraction and stenosis detection Initially, a novel keyframe extraction method is proposed to find the keyframe from the angiogram video. Followed by a hybrid segmentation method is presented in this research to extract the coronary artery region from the image. Further a method is proposed to detect the stenosis by extracting and fusing different features. Detected stenosis is categorized using the proposed stenosis level classification method. This CASDDIP model is a supporting tool to help the cardiologist during diagnosis. -
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Activity recognition using machine learning techniques for smart home assisted living
The statistical survey by United Nations Department of Economic and Social Affairs/Population Division says, quotglobally the number of persons aged 60 and above is expected to be more than double by 2050 newlineand more than triple by 2100quot. Especially in India, 9.5 percent of the population comprises of elders above 60 years. This may reach 22.2 percent in 2050 and 44.4 percent in 2100. On one side, the population of newlineelders are gradually increasing and on the other side there is a challenge to take care of the wellbeing of the elders when they are living alone. Smart home assisted living system can address these problems. Smart newlineHome Assisted living System is one among the growing research areas in smart computing. Advances in sensing, communication and ambientintelligence technologies created tremendous change in smart living newlineenvironment. The development in technology made smart home to support elders, disabled persons and the needy person. newlineActivity recognition is a growing technology in recent research and it plays a vital role in smart home assisted living system. Activity Recognition is a more dynamic, interesting, and challenging research newlinetopic in different areas like Ubiquitous Computing, Smart Home Assisted Living, Human Computer Interaction (HIC) etc. It provides solution to various real-time, human-oriented problems like elder care and health newlinecare. newlineIn order to address the issue on providing support on elder care this research proposes a machine learning based activity recognition model and an enhanced communication protocol for a smart home system, which are collaborated for designing the architecture of a smart home assisted living system. This system consists of three sub phases viz., data acquisition, monitoring system, and tracking system. -
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Clonning and Characterization of An Exported Protein Present in the RD7 Region of Clinical Isolates of Mycobacterium Tuberculosis
The bacterium Mycobacterium tuberculosis is responsible for causing the disease newlinetuberculosis in mammals, which is regarded as one of the oldest diseases haunting the human race. The only available tuberculosis vaccine Bacillus Calmette-Guerine (BCG), is effective against childhood tuberculosis but is regarded as having low efficacy in conferring protection in the case of tuberculosis in adults. A comparison of the M. tuberculosis H37Rv strain and clinical isolates from Kerala had earlier revealed that the clinical strains have a distinctive 4.5 kb genomic sequence that is lacking from the H37Rv strain in the RD7 region. The RD7 is a distinctive genomic region that is absent in M. tuberculosis H37Rv and Mycobacterium bovis BCG strain. The 4.5 kb genomic sequence is projected to include 6 potential ORFs by newlineNCBI ORF prediction tool, one of which Novel Hypothetical Protein (NHP2) is anticipated to encode an exported protein with a length of 268 amino acids. Studies demonstrate that Mycobacterium tuberculosis secretory proteins such as the Ag85 complex, the ESAT-6 family protein, and the PE-PPE family proteins were newlineeffective vaccine candidates because they trigger T cells. Here, we present an indepth analysis of the exported protein, which is 268 amino acids long. The putative exported protein with a gene 807 bp long was PCR amplified and cloned in the expression vector pET-32a for expression. The protein was over expressed using Isopropyl D-1-thiogalactopyranoside (IPTG) and was isolated and purified using column chromatography. Bioinformatics studies were conducted to study the characteristics of the expressed protein. A novel putative mycobacterial protein discovered by subtractive hybridization was studied for its potential as a vaccine candidate using cutting-edge computer technologies. -
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A study on the perception of MOOC (Massive Open Online Course) amongst the students of Christ University, Bengaluru /
Massive open online courses (MOOC) are a recent innovation in the field of online learning. Several top-tier universities around the world have started offering MOOC programmes in a wide array of professional, technical as well as creative fields. Top MOOC providers such as Coursera, Udacity and edX have a student fellowship from all across the world, pursuing one or more from the thousands of courses offered by these MOOC giants.