Statistical exploration of dataset examining key indicators influencing housing and urban infrastructure investments in megacities

Lagos, by the UN standards, has attained the megacity status, with the attendant challenges of living up to that titanic position; regrettably it struggles with its present stock of housing and infrastructural facilities to match its new status. Based on a survey of construction professionals’ perception residing within the state, a questionnaire instrument was used to gather the dataset. The statistical exploration contains dataset on the state of housing and urban infrastructural deficit, key indicators spurring the investment by government to upturn the deficit and improvement mechanisms to tackle the infrastructural dearth. Descriptive statistics and inferential statistics were used to present the dataset. The dataset when analyzed can be useful for policy makers, local and international governments, world funding bodies, researchers and infrastructural investor

An Improved Anomalous Intrusion Detection Model

The volume of cyber-attack targeting network resources within the cyberspace is steadily increasing and evolving. Network intrusions compromise the confidentiality, integrity or availability of network resources causing reputational damage and the consequential financial loss. One of the key cyber-defense tools against these attacks is the Intrusion Detection System. Existing anomalous intrusion detection models often misclassified normal network traffics as attacks while minority attacks go undetected due to an extreme imbalance in network traffic data. This leads to a high false positive and low detection rate. This study focused on improving the detection accuracy by addressing the class imbalanced problem which is often associated with network traffic dataset. Live network traffic packets were collected within the test case environment with Wireshark during normal network activities, Syncflood attack, slowhttppost attack and exploitation of known vulnerabilities on a targeted machine. Fifty-two features including forty-two features similar to Knowledge Discovery in Database (KDD ’99) intrusion detection dataset were extracted from the packet meta-data using Spleen tool. The features were normalized with min-max normalization algorithm and Information Gain algorithm was used to select the best discriminatory features from the feature space. An anomalous intrusion detection model was formulated by a cascade of k-means clustering algorithm and random-forest classifier. The proposed model was simulated and its performance was evaluated using detection accuracy, sensitivity, and specificity as metrics. The result of the evaluation showed 10% higher detection accuracy, 29% sensitivity, and 0.2% specificity than the existing model. Keywords— anomalous, cyber-attack, Detection, Intrusio

Genomic characterisation of human monkeypox virus in Nigeria

Monkeypox virus (MPXV) is a large, double-stranded DNA virus belonging to the Orthopox genus in the family Poxviridae. First identified in 1958, MPXV has caused sporadic human outbreaks in central and west Africa, with a mortality rate between 1% and 10%.1 Viral genomes from west Africa and the Congo Basin separate into two clades, the latter being more virulent.2 Recently, MPXV outbreaks have occurred in Sudan (2005), the Republic of the Congo and Democratic Republic of the Congo (2009), and the Central African Republic (2016).3 A suspected outbreak of human MPXV was reported to WHO on Sept 26, 2017, by the Nigeria Centre for Disease Control (NCDC) after a cluster of suspected cases had occurred in Yenagoa Local Government Area, Bayelsa State, Nigeria.4 Since the onset of the outbreak, 155 cases have been reported by the NCDC, of which 56 were confirmed.4 A subset of these samples was sent to the WHO Collaborating Center at the Institut Pasteur de Dakar (IPD) in Senegal for confirmation by PCR

Epidemiology of Injuries at a Tertiary Care Center in Malawi

Injury surveillance is an ongoing process required for primary, secondary, and tertiary injury prevention. In Malawi, hospital-based injury data are not available

Strategic positioning:an integrated decision process for manufacturers

Purpose – This paper describes research that has sought to create a formal and rational process that guides manufacturers through the strategic positioning decision. Design/methodology/approach – The methodology is based on a series of case studies to develop and test the decision process. Findings – A decision process that leads the practitioner through an analytical process to decide which manufacturing activities they should carryout themselves. Practical implications – Strategic positioning is concerned with choosing those production related activities that an organisations should carry out internally, and those that should be external and under the ownership and control of suppliers, partners, distributors and customers. Originality/value – This concept extends traditional decision paradigms, such as those associated with “make versus buy” and “outsourcing”, by looking at the interactions between manufacturing operations and the wider supply chain networks associated with the organisation

How to Exploit the Digitalization Potential of Business Processes

Process improvement is the most value-adding activity in the business process management (BPM) lifecycle. Despite mature knowledge, many approaches have been criticized to lack guidance on how to put process improvement into practice. Given the variety of emerging digital technologies, organizations not only face a process improvement black box, but also high uncertainty regarding digital technologies. This paper thus proposes a method that supports organizations in exploiting the digitalization potential of their business processes. To achieve this, action design research and situational method engineering were adopted. Two design cycles involving practitioners (i.e., managers and BPM experts) and end-users (i.e., process owners and participants) were conducted. In the first cycle, the method’s alpha version was evaluated by interviewing practitioners from five organizations. In the second cycle, the beta version was evaluated via real-world case studies. In this paper, detailed results of one case study, which was conducted at a semiconductor manufacturer, are included

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

Identification, Replication, and Fine-Mapping of Loci Associated with Adult Height in Individuals of African Ancestry

Adult height is a classic polygenic trait of high heritability (h2 ∼0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain ∼10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10−12 and 2p14-rs4315565, P = 1.2×10−8). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10−4 for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits