A survey on the determinants of entrepreneurial training effectiveness among micro finance institutions of Malaysia

The importance of the training is increasing day by day not only in corporate sector but also in entrepreneurial sector.This study aims to evaluate the influencing factors of entrepreneurial training effectiveness of Malaysian microfinance institutions (hereinafter MFIs).This study use survey research design and involve four listed MFIs of Malaysia that are selected on the base of engagement in entrepreneurship training during last five years.Questionnaires are used to collect data from selected respondents by using stratified random sampling.Results of the study reveal that deteriorating rate of small and micro enterprises is increasing rapidly due to inappropriate training and non-allocation of sufficient funds. Findings confirm the relationship between entrepreneurial training effectiveness and training need analysis. Training contents also found a critical and important factor for training effectiveness.Results also show that there is a need to undertake a comprehensive analysis by MFIs on individual entrepreneurs and the job tasks in order to estimate their training needs.In this way, the need of clients for appropriate and relevant training can be addressed in a better way

Cross-VM Network Channel Attacks and Countermeasures within Cloud Computing Environments

Cloud providers attempt to maintain the highest levels of isolation between Virtual Machines (VMs) and inter-user processes to keep co-located VMs and processes separate. This logical isolation creates an internal virtual network to separate VMs co-residing within a shared physical network. However, as co-residing VMs share their underlying VMM (Virtual Machine Monitor), virtual network, and hardware are susceptible to cross VM attacks. It is possible for a malicious VM to potentially access or control other VMs through network connections, shared memory, other shared resources, or by gaining the privilege level of its non-root machine. This research presents a two novel zero-day cross-VM network channel attacks. In the first attack, a malicious VM can redirect the network traffic of target VMs to a specific destination by impersonating the Virtual Network Interface Controller (VNIC). The malicious VM can extract the decrypted information from target VMs by using open source decryption tools such as Aircrack. The second contribution of this research is a privilege escalation attack in a cross VM cloud environment with Xen hypervisor. An adversary having limited privileges rights may execute Return-Oriented Programming (ROP), establish a connection with the root domain by exploiting the network channel, and acquiring the tool stack (root domain) which it is not authorized to access directly. Countermeasures against this attacks are also presente

Federating cloud systems for collaborative construction and engineering

The construction industry has undergone a transformation in the use of data to drive its processes and outcomes, especially with the use of Building Information Modelling (BIM). In particular, project collaboration in the construction industry can involve multiple stakeholders (architects, engineers, consultants) that exchange data at different project stages. Therefore, the use of Cloud computing in construction projects has continued to increase, primarily due to the ease of access, availability and scalability in data storage and analysis available through such platforms. Federation of cloud systems can provide greater flexibility in choosing a Cloud provider, enabling different members of the construction project to select a provider based on their cost to benefit requirements. When multiple construction disciplines collaborate online, the risk associated with project failure increases as the capability of a provider to deliver on the project cannot be assessed apriori. In such uncontrolled industrial environments, “trust” can be an efficacious mechanism for more informed decision making adaptive to the evolving nature of such multi-organisation dynamic collaborations in construction. This paper presents a trust based Cooperation Value Estimation (CoVE) approach to enable and sustain collaboration among disciplines in construction projects mainly focusing on data privacy, security and performance. The proposed approach is demonstrated with data and processes from a real highway bridge construction project describing the entire selection process of a cloud provider. The selection process uses the audit and assessment process of the Cloud Security Alliance (CSA) and real world performance data from the construction industry workloads. Other application domains can also make use of this proposed approach by adapting it to their respective specifications. Experimental evaluation has shown that the proposed approach ensures on-time completion of projects and enhanced..

Integration of mental health into primary healthcare: Perceptions of stakeholders in Pakistan

Background: In Pakistan, there is high prevalence of mental health disorders, but mental health services to address these are not well developed. To provide effective mental health services, the World Health Organization emphasizes the integration of mental health into primary health care (PHC).Objectives: This study aimed to assess the views of key stakeholders about integration of mental health into PHC in Karachi, Pakistan.Methods: A qualitative, exploratory study was conducted between June and September 2013 among 15 decision-making (from the Department of Health) and implementation-level stakeholders (mental health and public health professionals and primary care staff) from both the public and private sectors. Face-to-face, in-depth interviews were conducted using a semi-structured interview guide. Data were collected until theoretical saturation was achieved and conventional content analysis was carried out.Results: Although there was general support among all the stakeholders for integration of mental health services within PHC, there were also a number of reservations. First was the perceived lack of support within the system in terms of resource allocation and acceptance from the community. Second was the lack of human resources in the field of mental health. In addition, resistance at the PHC level is likely as staff are already burdened with other preventive care services.Conclusions: The study suggests that strong political commitment, adequate human and financial resources, and strong advocacy are needed for the integration of mental health into PHC in Pakistan

EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review

Mental disorders represent critical public health challenges as they are leading contributors to the global burden of disease and intensely influence social and financial welfare of individuals. The present comprehensive review concentrate on the two mental disorders: Major depressive Disorder (MDD) and Bipolar Disorder (BD) with noteworthy publications during the last ten years. There is a big need nowadays for phenotypic characterization of psychiatric disorders with biomarkers. Electroencephalography (EEG) signals could offer a rich signature for MDD and BD and then they could improve understanding of pathophysiological mechanisms underling these mental disorders. In this review, we focus on the literature works adopting neural networks fed by EEG signals. Among those studies using EEG and neural networks, we have discussed a variety of EEG based protocols, biomarkers and public datasets for depression and bipolar disorder detection. We conclude with a discussion and valuable recommendations that will help to improve the reliability of developed models and for more accurate and more deterministic computational intelligence based systems in psychiatry. This review will prove to be a structured and valuable initial point for the researchers working on depression and bipolar disorders recognition by using EEG signals.Comment: 29 pages,2 figures and 18 Table

Evaluation of antibiotic use in pediatric intensive care unit of a developing country

Background: Pediatric Intensive Care Unit (PICU) patients are often prescribed antibiotics with a low threshold in comparison to patients elsewhere. Irrational antibiotics use can lead to rapid emergence of drug resistance, so surveillance of their use is important.Objectives: To evaluate the use of antibiotics in relation to bacteriological findings in PICU of a Tertiary Hospital.Methods: Retrospective review of medical records of all children (age 1 month-16 years) admitted in our closed multidisciplinary-cardiothoracic PICU from January to June 2013 was performed, after approval from Ethical Review Committee. For each antibiotic, indication (prophylactic, empiric, therapeutic) and duration of use were recorded. All diagnoses of infections were recorded according to diagnostic criteria of IPSCC 2005. Results are presented as frequency and percentages and median with inter quartile range using SPSS version 19.Results: All of the total 240 patients admitted in PICU during the study period received antibiotics: 43% (n = 104) prophylactically, 42% (n = 102) empirically, and 15% (n = 15) therapeutically. Median number of antibiotic use per patient in PICU was 3, with range of 1-7. 25% received 1 antibiotic, 23% received 2 antibiotics, 29% received 3 antibiotics, and rest received ≥4 antibiotics. Most commonly used antibiotics were cefazolin, meropenem, vancomycin and ceftriaxone, and most frequently used combination was meropenem and vancomycin. In majority of the cases, (70%) empiric antibiotic combinations were stopped in 72 h.Conclusion: This is the first report of antibiotics use in PICU from our country, which shows that antibiotics are prescribed universally in our PICU. Strategies to assess the need for antibiotic use are needed

Aggregated capability assessment (AgCA) for CAIQ enabled Cross-Cloud Federation

Cross-Cloud Federation (CCF) enables resource exchange among multiple, heterogeneous Cloud Service Providers (CSPs) to support the composition of services (workflow) hosted by different providers. CCF participation can either be fixed, or the types of services that can be used are limited to reduce the potential risk of service failure or secure access. Although many service selection approaches have been proposed in literature for cloud computing, their applicability to CCF i.e. cloud-to-cloud interaction, has not been adequately investigated. A key component of this cloud-to-cloud paradigm involves assessing the combined capability of contributing participants within a federation and their connectivity. A novel Aggregated Capability Assessment (AgCA) approach based on using the Consensus Assessment Initiative Questionnaire from Cloud Security Alliance is proposed for CCF. The proposed mechanism is implemented as a component of a centralized broker to enhance the quality of the selection process for participants within a federation. Our experimental results show that AgCA is a useful tool for partner selection in a dynamic, heterogeneous and multilevel cloud federation

Optimizing diamond-like carbon coatings - From experimental era to artificial intelligence

Diamond-like carbon (DLC) coatings are widely used for numerous engineering applications due to their superior multi-functional properties. Deposition of good quality DLC is governed by energy per unit carbon atom or ion and plasma kinetics, which are independent parameters. Translating independent parameters to dependent parameters to produce a best DLC is subjected to deposition method, technology, and system configurations which may involve above 50 combinations of bias voltage, chamber pressure, deposition temperature, gas flow rate, etc. Hence DLC coatings are optimized to identify the best parameters which yield superior properties. This article covers DLC introduction, the role of independent parameters, translation of independent parameters to dependent parameters, and discussion of four generations of DLC optimization. The first-generation of DLC optimization experimentally optimizes the parameter-to-property relationship, and the second-generation describes multi-parameter optimization with a hybrid of experimental and statistical-based analytical methods. The third generation covers the optimization of DLC deposition parameters with a hybrid of statistical methods and artificial intelligence (AI) tools. The ongoing fourth generation not only performs multi-parameter and multi-property optimization but also use AI tools to predict DLC properties and performance with higher accuracy. It is expected that AI-driven DLC optimizations and progress in virtual synthesis of DLC will not only assist in resolving DLC challenges specific to emerging markets and complex environments, but will also become a pathway for DLC to enter a digital-twin era

Risk-based service selection in federated clouds

The Cloud Service Provider (CSP) marketplace has continued to expand in recent years. Although a few major providers dominate (e.g. AWS, Google Cloud, Microsoft Azure), there are also a number of specialist providers offering hosting services and computing platforms. A single Cloud provider can also offer a marketplace for their own offerings - e.g. the AWS Marketplace, which enables third party libraries to be deployed as services within AWS instances. In order to determine whether a particular CSP should be used, clients need to apply preliminary assessment and evaluation when provisioning services on such a provider. Service selection can be realised based on different decision-making criteria, to enable a more informed selection process for clients. Trust can be utilised as a mechanism to inform such selection decisions. Trust can have different representations and utilise parameters derived from past interactions. Trust therefore represents an expression of risk associated with a service exchange between clients and providers. We present a trust-based risk evaluation for CSP selection in federated clouds, with a particular focus on security & data privacy. We use a scenario from an Architecture, Engineering & Construction (AEC) project to demonstrate how such a selection can be made, and is of benefit in developing the federated system. A methodology for the selection process is outlined, making use of metrics and certification processes from the Cloud Security Alliance. The proposed approach can also be generalised to other application domains with similar requirements