Search results for: credit risk assessment

Authors: Tina Vuko, Marija Maretić, Marko Čular

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The aim of this study is to analyze the role and effectiveness of internal mechanism (audit committee) of corporate governance on credit institutions performance in Croatia. Based on research objective, sample of 78 credit institutions listed on Zagreb Stock Exchange, from 2007 to 2012, has been collected and efficiency index of audit committee (EIAC) has been created. Based on the sample and created EIAC, conclusions are as follows: audit committees of credit institutions have medium efficiency, based on EIAC measurement; there is a significant difference in audit committee effectiveness, in observed period; there is no positive relationship between audit committee effectiveness and credit institution performance; there is a significant difference between level of audit committee effectiveness and audit firm type. Future research should contain increased number of elements in EIAC creation and increased sample, for all obligators who need to establish audit committee.

Keywords: Corporate Governance, Audit Committee, Financial Institutions, Efficiency Index of Audit Committee.

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Authors: Akekaluck Hemtanon, Bunyarit Uyyanonvara

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This research explores on the development of the structure of Carbon Credit Registry System those accords to the need of future events in Thailand. This research also explores the big picture of every connected system by referring to the design of each system, the Data Flow Diagram, and the design in term of the system-s data using DES standard. The purpose of this paper is to show how to design the model of each system. Furthermore, this paper can serve as guideline for designing an appropriate Carbon Credit Registry System.

Keywords: CDM, CDM BE, Annex I County, Non-Annex I country, CERs, Kyoto Protocol.

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Authors: Elena M. Capitanul, Carlos A. Nunes Cosenza, Walid El Moudani, Felix Mora Camino

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The construction of a new airport or the extension of an existing one requires massive investments and many times public private partnerships were considered in order to make feasible such projects. One characteristic of these projects is uncertainty with respect to financial and environmental impacts on the medium to long term. Another one is the multistage nature of these types of projects. While many airport development projects have been a success, some others have turned into a nightmare for their promoters. This communication puts forward a new approach for airport investment risk assessment. The approach takes explicitly into account the degree of uncertainty in activity levels prediction and proposes milestones for the different stages of the project for minimizing risk. Uncertainty is represented through fuzzy dual theory and risk management is performed using dynamic programming. An illustration of the proposed approach is provided.

Keywords: Airports, fuzzy logic, risk, uncertainty.

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Authors: Essam Al Daoud

Abstract:

Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: Gradient boosting, XGBoost, LightGBM, CatBoost, home credit.

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Authors: Nnamdi I. Nwulu, Shola G. Oroja

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It has become crucial over the years for nations to improve their credit scoring methods and techniques in light of the increasing volatility of the global economy. Statistical methods or tools have been the favoured means for this; however artificial intelligence or soft computing based techniques are becoming increasingly preferred due to their proficient and precise nature and relative simplicity. This work presents a comparison between Support Vector Machines and Artificial Neural Networks two popular soft computing models when applied to credit scoring. Amidst the different criteria-s that can be used for comparisons; accuracy, computational complexity and processing times are the selected criteria used to evaluate both models. Furthermore the German credit scoring dataset which is a real world dataset is used to train and test both developed models. Experimental results obtained from our study suggest that although both soft computing models could be used with a high degree of accuracy, Artificial Neural Networks deliver better results than Support Vector Machines.

Keywords: Artificial Neural Networks, Credit Scoring, SoftComputing Models, Support Vector Machines.

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Authors: Bill D. Geis, Frederick Newman

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Suicide and wrongful death forensic cases are the fastest rising tort in mental health law. Most suicide-related personal injury claims fall into the legal category of “wrongful death.” Though mental health experts may be called on to address a range of forensic questions in wrongful death cases, the central consultation that most experts provide is about the negligence element—specifically, the issue of whether the clinician met the clinical standard of care in assessing, treating, and managing the deceased person’s mental health care. Standards of care, varying from US state to state, are broad and address what a reasonable clinician might do in a similar circumstance. This fact leaves the issue of the suicide standard of care, in each case, up to forensic experts to put forth a reasoned estimate of what the standard of care should have been in the specific case under litigation. Because the general state guidelines for standard of care are broad, forensic experts are readily retained to provide scientific and clinical opinions about whether or not a clinician met the standard of care in their suicide assessment, treatment, and management of the case. In the past and in much of current practice, the assessment of suicide has centered on the elicitation of verbalized suicide ideation. But suicide ideation, in the matter of suicide risk determination, may be a necessary but insufficient target of lethal suicide risk assessment. Assessment of near-term suicide risk—assessment that goes beyond verbalized suicide ideation and relates to acute crisis variables—is likely needed. Specifically, such other or additional suicide risk variable assessment may be required in the context of lethal suicide risk situations, as opposed to the discernment of general, nonlethal suicide behavior as a standard of practice (whether a patient is having suicidal thoughts or exhibiting an ambivalent suicide attempt potential). In the current study, verbalized suicide ideation information was unhelpful in the assessment of lethal risk. The Lethal Suicide Risk Assessment, Acute Model, and other dynamic, near-term risk models (such as the Acute Suicide Affective Disorder Model and the Suicide Crisis Syndrome Model)—going beyond elicited suicide ideation—need to be incorporated into current clinical suicide assessment training and become the legal standard of care for expected clinical behavior. Without this expanded clinical assessment perspective, the standard of care for suicide assessment is out of sync with current knowledge—an emerging dilemma for the forensic evaluation of suicide wrongful death cases.

Keywords: Forensic evaluation, standard of care, suicide, suicide assessment, wrongful death.

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Authors: J. R. Wang, W. Y. Cheng, J. S. Yeh, S. W. Chen, Y. M. Ferng, J. H. Yang, W. S. Hsu, C. Shih

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To understand the risk for dry storage concrete casks in the cask loading, transfer, and storage phase, the purpose of this research is to establish the probabilistic risk assessment (PRA) analysis methodology for dry storage concrete casks by using SAPHIRE 8 code. This analysis methodology is used to perform the study of Taiwan nuclear power plants (NPPs) dry storage system. The process of research has three steps. First, the data of the concrete casks and Taiwan NPPs are collected. Second, the PRA analysis methodology is developed by using SAPHIRE 8. Third, the PRA analysis is performed by using this methodology. According to the analysis results, the maximum risk is the multipurpose canister (MPC) drop case.

Keywords: PRA, Dry storage, concrete cask, SAPHIRE.

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Authors: Isabela Moreira Queiroz

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Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management. 

Keywords: Probabilistic methods, risk assessment, risk management, slope stability.

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Authors: S. A. Nta

Abstract:

Application of health risk assessment methods is important in order to comprehend the risk of human exposure to heavy metals and other dangerous pollutants. Four soil samples were collected at distances of 10, 20, 30 m and the control 100 m away from the dump site at depths of 0.3, 0.6 and 0.9 m. The collected soil samples were examined for Zn, Cu, Pb, Cd and Ni using standard methods. The health risks via the main pathways of human exposure to heavy metal were detected using relevant standard equations. Hazard quotient was calculated to determine non-carcinogenic health risk for each individual heavy metal. Life time cancer risk was calculated to determine the cumulative life cancer rating for each exposure pathway. The estimated health risk values for adults and children were generally lower than the reference dose. The calculated hazard quotient for the ingestion, inhalation and dermal contact pathways were less than unity. This means that there is no detrimental concern to the health on human exposure to heavy metals in contaminated soil. The life time cancer risk 5.4 × 10^-2 was higher than the acceptable threshold value of 1 × 10^-4 which is reflected to have significant health effects on human exposure to heavy metals in contaminated soil. Good hygienic practices are recommended to ease the potential risk to children and adult who are exposed to contaminated soils. Also, the local authorities should be made aware of such health risks for the purpose of planning the management strategy accordingly.

Keywords: Health risk assessment, pollution, heavy metals, soil.

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: credit card fraud detection, user authentication, behavioral biometrics, machine learning, literature survey

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: Risk identification, risk assessment, analytical hierarchical process, multi-criteria decision.

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Authors: Todor Bačkalić, Marinko Maslarić, Milosav Georgijević, Sanja Bojić

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Presented article outlines a rationale, why it is necessary to develop competence about infrastructure risk in water transport. Climate changes are evident and require special attention and global monitoring. Current risk assessment methods for Inland waterway transport just consider some dramatic events. We present a new method for the assessment of risk and vulnerability of inland waterway transport where river depth represents a crucial part. The analysis of water level changes in the lower Danube was done for two significant periods (1965-1979 and 1998-2012).

Keywords: Container ship, draught, probability, the Danube.

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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Hazard assessment and risks quantification are key components for estimating the impact of existing regulations. But since regulatory compliance cannot cover all risks in aviation, the authors point out that by studying causal factors and eliminating uncertainty, an accurate analysis can be outlined. The research debuts by making delimitations on notions, as confusion on the terms over time has reflected in less rigorous analysis. Throughout this paper, it will be emphasized the fact that the variation in human performance and organizational factors represent the biggest threat from an operational perspective. Therefore, advanced risk assessment methods analyzed by the authors aim to understand vulnerabilities of the system given by a nonlinear behavior. Ultimately, the mathematical modeling of existing hazards and risks by eliminating uncertainty implies establishing an optimal solution (i.e. risk minimization).

Keywords: Control, human factor, optimization, risk management, uncertainty.

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Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deals with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: Credit network, case portfolio, binary tree, priority queue, stack.

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Authors: Yu-Chen Lin, Tzong-Yeang Lee

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This study aims to assess the vulnerability and risk of the coastal areas of Taijiang to abnormal oceanographic phenomena. In addition, this study aims to investigate and collect data regarding the disaster losses, land utilization, and other social, economic, and environmental issues in these coastal areas to construct a coastal vulnerability and risk map based on the obtained climate-change risk assessment results. Considering the indexes of the three coastal vulnerability dimensions, namely, man-made facilities, environmental geography, and social economy, this study adopted the equal weighting process and Analytic Hierarchy Process to analyze the vulnerability of these coastal areas to disasters caused by climatic changes. Among the areas with high coastal vulnerability to climatic changes, three towns had the highest coastal vulnerability and four had the highest relative vulnerability. Areas with lower disaster risks were found to be increasingly vulnerable to disasters caused by climatic changes as time progresses.

Keywords: Climate change, coastal disaster, risk, vulnerability

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Authors: Jerry Szatko, Edan L. Jorgensen, Stacia Jorgensen

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A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.

Keywords: Behavior based advising, behavioral finance, financial advising, financial advisor tools, financial risk tolerance.

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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Authors: Tomohiro Ando, Satoshi Yamashita

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The objective of this study is to propose a statistical modeling method which enables simultaneous term structure estimation of the risk-free interest rate, hazard and loss given default, incorporating the characteristics of the bond issuing company such as credit rating and financial information. A reduced form model is used for this purpose. Statistical techniques such as spline estimation and Bayesian information criterion are employed for parameter estimation and model selection. An empirical analysis is conducted using the information on the Japanese bond market data. Results of the empirical analysis confirm the usefulness of the proposed method.

Keywords: Empirical Bayes, Hazard term structure, Loss given default.

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Authors: Moosa Haji Abbasi, Emad Benhelal, Arshad Ahmad

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Storage tank farms are essential industrial facilities to accumulate oil, petrochemicals and gaseous products. Since tank farms contain huge mass of fuel and hazardous materials, they are always targets of serious accidents such as fire, explosion, spill and toxic release which may cause severe impacts on human health, environmental and properties.

Although having a safe layout is not able to prevent initiating accidents, however it effectively controls and reduces the adverse impact of such accidents.

The aim of this paper is to determine the optimal layout for a storage tank contains different type of hydrocarbon fuels. A quantitative risk assessment is carried out on a selected tank farm in Jaipur, India, with particular attention given to both the consequence modeling and the overall risk assessment using PHAST Software. Various designs of tank layouts are examined taking into consideration several issues of plant operations and maintenance. In all stages of the work, standard guidelines specified by the industry are considered and recommendations are substantiated with simulation results and risk quantification.

Keywords: Tank farm, safe distance, safe layout, risk assessment, PHAST.

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Authors: Manu Krishnan, Phil Jacoby

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In this paper, we discuss the paradigm shift in bank capital from the “gone concern" to the “going concern" mindset. We then propose a methodology for pricing a product of this shift called Contingent Capital Notes (“CoCos"). The Merton Model can determine a price for credit risk by using the firm-s equity value as a call option on those assets. Our pricing methodology for CoCos also uses the credit spread implied by the Merton Model in a subsequent derivative form created by John Hull et al . Here, a market implied asset volatility is calculated by using observed market CDS spreads. This implied asset volatility is then used to estimate the probability of triggering a predetermined “contingency event" given the distanceto- trigger (DTT). The paper then investigates the effect of varying DTTs and recovery assumptions on the CoCo yield. We conclude with an investment rationale.

Keywords: CoCo, Contingent capital, Bank Capital, Tier1 Capital

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: Corporate credit rating prediction, feature selection, genetic algorithms, instance selection, multiclass support vector machines.

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Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

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Well organized digitalization and information systems have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are to be identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, with a focus on information system risks.

Keywords: information system risk, operational risk, microfinance performance, DR Congo

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Authors: Dragan Kljajic, Nikola Djuric, Karolina Kasas-Lazetic, Danka Antic

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Wireless communications have been expanded very fast in recent decades. This technology relies on an extensive network of base stations and antennas, using radio frequency signals to transmit information. Devices that use wireless communication, while offering various services, basically act as sources of non-ionizing electromagnetic fields (EMF). Such devices are permanently present in human vicinity and almost constantly radiate, causing EMF pollution of the environment. This fact has initiated development of modern systems for observation of the EMF pollution, as well as for risk assessment. This paper presents the Serbian electromagnetic field monitoring network – SEMONT, designed for automated, remote and continuous broadband monitoring of EMF in the environment. Measurement results of the SEMONT monitoring at one of the test locations, within the main campus of the University of Novi Sad, are presented and discussed, along with corresponding exposure assessment of the general population, regarding the Serbian legislation.

Keywords: EMF monitoring, exposure assessment, sensor nodes, wireless network.

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Authors: Saima Ayaz, Zakir Hussain, Maqbool Hussain Sial

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The study identified the sources of production inefficiency of the farming sector in district Faisalabad in the Punjab province of Pakistan. Data Envelopment Analysis (DEA) technique was utilized at farm level survey data of 300 farmers for the year 2009. The overall mean efficiency score was 0.78 indicating 22 percent inefficiency of the sample farmers. Computed efficiency scores were then regressed on farm specific variables using Tobit regression analysis. Farming experience, education, access to farming credit, herd size and number of cultivation practices showed constructive and significant effect on the farmer-s technical efficiency.

Keywords: Agricultural credit, DEA, Technical efficiency, Tobit analysis

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Authors: Phayong Thepaksorn

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The objective of this study was to assess whether living in proximity to a roofing fiber cement factory in southern Thailand was associated with physical, mental, social, and spiritual health domains measured in a self-reported health risk assessment (HRA) questionnaire. A cross-sectional study was conducted among community members divided into two groups: near population (living within 0-2km of factory) and far population (living within 2-5km of factory) (N=198). A greater proportion of those living far from the factory (65.34%) reported physical health problems than the near group (51.04%) (p =0.032). This study has demonstrated that the near population group had higher proportion of participants with positive ratings on mental assessment (30.34%) and social health impacts (28.42%) than far population group (10.59% and 16.67%, respectively) (p <0.001). The near population group (29.79%) had similar proportion of participants with positive ratings in spiritual health impacts compared with far population group (27.08%). Among females, but not males, this study demonstrated that a higher proportion of the near population had a positive summative score for the self-HRA, which included all four health domain, compared to the far population (p<0.001 for females; p = 0.154 for males). In conclusion, this self-HRA of physical, mental, social, and spiritual health domains reflected the risk perceptions of populations living in the vicinity of the roofing fiber cement factory. This type of tool can bring attention to population concerns and complaints in the factory’s surrounding community. Our findings may contribute to future development of self-HRA for HIA development procedure in Thailand.

Keywords: Cement dust, health impact assessment, risk assessment, walk-though survey.

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Authors: E. Fosch-Villaronga

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This paper pioneers Care Robot Impact Assessment (CRIA), a methodology used to identify, analyze, mitigate and eliminate the risks posed by the insertion of non-medical personal care robots (PCR) in medical care facilities. Its precedent instruments [Privacy and Surveillance Impact Assessment (PIA and SIA)] fall behind in coping with robots. Indeed, personal care robots change dramatically how care is delivered. The paper presents a specific risk-sector methodology, identifies which robots are under its scope and presents some of the challenges introduced by these robots.

Keywords: Ethics, Impact Assessment, Law, Personal Care Robots.

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Authors: Okolo Chimaobi Valentine

Abstract:

This paper seeks to assess the implications of bank consolidation on the performance of small and medium scale enterprises in the Nigerian economy. Multiple linear regression technique and correlation matrix test were employed to measure the extent to which small and medium scale enterprises asset size, survival and access to credit were influenced. The result showed that bank deposit (BD) and bank credit (L or BC) impacted on asset size and survival of small and medium scale enterprises. None of the variables had significant impact on SMEs access to credit. There is a shift of focus by commercial banks away from small and medium scale enterprises (small customers), which is evidenced by the significant negative influence of bank credit to both the survival and asset size of small and medium enterprises. While micro finance banks work hard at providing funds to small and medium scale entrepreneurs, their capacity to meet the needs of these entrepreneurs is constrained. CBN should make policies that will boost micro finance bank’s capital and also monitor closely the management of the banks to ensure prudent financing of small and medium scale investments.

Keywords: Bank consolidation, small and medium enterprises.

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Authors: Hossam Shalabi, George Hadjisophocleous

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The Canadian Nuclear Power Plants (NPPs) use some portions of NUREG/CR-6850 in carrying out Fire Probabilistic Risk Assessment (PRA). An assessment for the applicability of NUREG/CR-6850 to CANDU reactors was performed and a CANDU Fire PRA was introduced. There are 19 operating CANDU reactors in Canada at five sites (Bruce A, Bruce B, Darlington, Pickering and Point Lepreau). A fire load density survey was done for all Fire Safe Shutdown Analysis (FSSA) fire zones in all CANDU sites in Canada. National Fire Protection Association (NFPA) Standard 557 proposes that a fire load survey must be conducted by either the weighing method or the inventory method or a combination of both. The combination method results in the most accurate values for fire loads. An updated CANDU Fire PRA model is demonstrated in this paper that includes the fuel survey in all Canadian CANDU stations. A qualitative screening step for the CANDU fire PRA is illustrated in this paper to include any fire events that can damage any part of the emergency power supply in addition to FSSA cables.

Keywords: Fire safety, CANDU, nuclear, fuel densities, FDS, qualitative analysis, fire probabilistic risk assessment.

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Authors: Chin-Ming Hong, Chin-Teng Lin, Chao-Yen Huang, Yi-Ming Lin

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In this article, we propose an Intelligent Medical Diagnostic System (IMDS) accessible through common web-based interface, to on-line perform initial screening for osteoporosis. The fundamental approaches which construct the proposed system are mainly based on the fuzzy-neural theory, which can exhibit superiority over other conventional technologies in many fields. In diagnosis process, users simply answer a series of directed questions to the system, and then they will immediately receive a list of results which represents the risk degrees of osteoporosis. According to clinical testing results, it is shown that the proposed system can provide the general public or even health care providers with a convenient, reliable, inexpensive approach to osteoporosis risk assessment.

Keywords: BMD, osteoporosis, IMDS, fuzzy-neural theory, web interface.

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Authors: B. Ferdousi

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This study examines the adoption of digital technology in academic assessment or e-assessment in higher education. The main focus of this research is to determine the impact of advanced digital technology on different assessment techniques such as formative assessment and summative assessment. The goal of this study is to critically evaluate the selection of different assessment methods using digital technology to enhance assessment for more effective learning. Given the increasing use of digital technology in the assessment of students' achievement in the learning process, this research is significant. Based on a literature review of different assessment techniques using technology, this study focuses on the formative and summative techniques of e-assessment. The paper offers an in-depth analysis of the innovative and creative use of digital technology in assessment. The findings of this research will enhance knowledge and in-depth understanding of using technology in assessment, especially in active learning environments, in higher academic institutions.

Keywords: E-assessment techniques, assessment for learning, assessment of learning, digital technology.

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