Building a Strong Undergraduate Research Culture in African Universities

Africa had a late start in the race to setting up and obtaining universities with research quality fundamentals. According to Mamdani [5], the first colonial universities were few and far between: Makerere in East Africa, Ibadan and Legon in West Africa. This last place in the race, compared to other continents, has had tremendous implications in the development plans for the continent. For Africa, the race has been difficult from a late start to an insurmountable litany of problems that include difficulty in equipment acquisition, lack of capacity, limited research and development resources and lack of investments in local universities. In fact most of these universities are very recent with many less than 50 years in business except a few. To help reduce the labor costs incurred by the colonial masters of shipping Europeans to Africa to do mere clerical jobs, they started training ―workshops‖ calling them technical or business colleges. According to Mamdani, meeting colonial needs was to be achieved while avoiding the ―Indian disease‖ in Africa -- that is, the development of an educated middle class, a group most likely to carry the virus of nationalism. Upon independence, most of these ―workshops‖ were turned into national ―universities‖, but with no clear role in national development. These national ―universities‖ were catering for children of the new African political elites. Through the seventies and eighties, most African universities were still without development agendas and were still doing business as usual. Meanwhile, governments strapped with lack of money saw no need of putting more scarce resources into big white elephants. By mid-eighties, even the UN and IMF were calling for a limit on funding African universities. In today‘s African university, the traditional curiosity driven research model has been replaced by a market-driven model dominated by a consultancy culture according to Mamdani (Mamdani, Mail and Guardian Online). The prevailing research culture as intellectual life in universities has been reduced to bare-bones classroom activity, seminars and workshops have migrated to hotels and workshop attendance going with transport allowances and per diems (Mamdani, Mail and Guardian Online). There is need to remedy this situation and that is the focus of this paper

HANDLING WORK FROM HOME SECURITY ISSUES IN SALESFORCE

Security is a vital component when it is identified with an endeavor record or our genuine materials. To protect our home or valuable things like gold, cash we use bank storage administrations or underground secret storage spaces at home. Similarly, IT enterprises put tremendous measure of capital in expanding security to its business and the archives. Associations use cryptography procedures to get their information utilizing progressed encryption calculations like SHA-256, SHA-512, RSA-1024, RSA-2048 pieces’ key encryption and Elliptic Curve Cryptography (ECC) calculations. These industry standard calculations are difficult to break. For instance, to break RSA-2048-piece encryption key, an old-style PC needs around 300 trillion years. As indicated by the continuous examination, a quantum PC can break it in 10seconds, yet such a quantum PC doesn\u27t yet exist. Despite the fact that these cryptographic calculations guarantee an awesome degree of safety, there will be dependably a space for breaking the security. Programmers will attempt new techniques to break the security. Thus, the association likewise should continue to utilize new strategies to build the level and nature of the security. Now it is time to check how the security aspect is taken care of when the IT employees are at work from home. The 2020 year has made many professionals work from home because of the Covid-19 pandemic. The Covid-19 has transformed almost all organizations to work from home, this has become standard advice, and technology plays an important role during work from home to monitor the employee works and provide security when the work is being carried away from their respective organization. Employees\u27 information security awareness will become one of the most important parts of safeguarding against nefarious information security practices during this work from home. Most of the workers like the expediency of work from home and the flexibility provided for the employees. But in this situation, workers need guarantees that their privacy is secured when using company laptops and phones. Cyber security plays an important role in maintaining a secured environment when working from home. This work focusses on managing the security break attack in the course of work from home. The focus of the study is on dealing with security breaches that occur when salespeople operate from home. The problem of security isn\u27t new. Security issues existed prior to the lockdown or pandemic, but because the staff was working from the office at the time, the system administrator was available to address them. However, how can an employee\u27s laptop and account be secured when working from home? MFH\u27s salesforce has leveraged a variety of innovative technologies to address security concerns during their tenure. Because the IT behemoth Salesforce has made it possible for all employees, including freshly hired ones, to seek WFH on a permanent basis. To address the security breach difficulties faced by employees, the organization used a number of new approaches, including tracking working hours, raising password difficulty, employing VPN (virtual private network), mandating video during meetings, continuously checking right to use control, and MFA (multi-factor authentication). Improvement of existing multi-factor authentication (MFA) is the focused topic discussed in the thesis. To add an additional step of protection to the login process Blockchain technology is proposed and to identify the employee identification a hybrid recognition model is proposed using face and fingerprint recognition. This leads to the employee going through multiple processes to authenticate his or her identity in numerous ways in order to access the business laptop. This procedure entails connecting his or her laptop to his or her mobile phone or email account. Keywords: MFA, WFH, Cyber Security, Encryption, Decryption

FACIAL IDENTIFICATION FOR DIGITAL FORENSIC

Forensic facial recognition has become an essential requirement in criminal investigations as a result of the emergence of electronic devices, such as mobile phones and computers, and the huge volume of existing content. Forensic facial recognition goes beyond facial recognition in that it deals with facial images under unconstrained and non-ideal conditions, such as low image resolution, varying facial orientation, poor illumination, a wide range of facial expressions, and the presence of accessories. In addition, digital forensic challenges do not only concern identifying an individual but also include understanding the context, acknowledging the relationships between individuals, tracking, and numbers of advanced questions that help reduce the cognitive load placed on the investigator. This thesis proposes a multi-algorithmic fusion approach by using multiple commercial facial recognition systems to overcome particular weaknesses in singular approaches to obtain improved facial identification accuracy. The advantage of focusing on commercial systems is that they release the forensic team from developing and managing their own solutions and, subsequently, also benefit from state-of-the-art updates in underlying recognition performance. A set of experiments was conducted to evaluate these commercial facial recognition systems (Neurotechnology, Microsoft, and Amazon Rekognition) to determine their individual performance using facial images with varied conditions and to determine the benefits of fusion. Two challenging facial datasets were identified for the evaluation; they represent a challenging yet realistic set of digital forensics scenarios collected from publicly available photographs. The experimental results have proven that using the developed fusion approach achieves a better facial vi identification rate as the best evaluated commercial system has achieved an accuracy of 67.23% while the multi-algorithmic fusion system has achieved an accuracy of 71.6%. Building on these results, a novel architecture is proposed to support the forensic investigation concerning the automatic facial recognition called Facial-Forensic Analysis System (F-FAS). The F-FAS is an efficient design that analyses the content of photo evidence to identify a criminal individual. Further, the F-FAS architecture provides a wide range of capabilities that will allow investigators to perform in-depth analysis that can lead to a case solution. Also, it allows investigators to find answers about different questions, such as individual identification, and identify associations between artefacts (facial social network) and presents them in a usable and visual form (geolocation) to draw a wider picture of a crime. This tool has also been designed based on a case management concept that helps to manage the overall system and provide robust authentication, authorisation, and chain of custody. Several experts in the forensic area evaluated the contributions of theses and a novel approach idea and it was unanimously agreed that the selected research problem was one of great validity. In addition, all experts have demonstrated support for experiments’ results and they were impressed by the suggested F-FAS based on the context of its functions.Republic of Iraq / Ministry of Higher Education and Scientific Research – Baghdad Universit

KB - WOT Fisheries Research; programme for 2010

LNV programme WOT 5 covers the execution of statutory tasks (WOT) in fisheries carried out by DLO. Part of the KB programme, presented in this report, contains resources earmarked to maintain and develop the expertise needed to carry out the WOT programme. As well as maintaining expertise, innovation is an important part of the programme. The programme is also part of the Wageningen UR Kennisbasis and comes under the theme KB01: “Groene en blauwe ruimte”. This report describes the allocation and utilisation of the Kennisbasis budget in 2010. The available budget in 2010 is €621 000. The structure of the KBWOT programme is similar to that in 2009. The money is spent through projects, each of which is described in this report. The projects are split up into four priority research areas: A) Influence of changes in the environment on marine ecosystems, B) impact of fisheries on ecosystems, C) changing fishery management, D) maintenance and international exchange of key WOT expertise. These priority research areas have been developed with the agreement of LNV. All of these areas fall under the wider WUR kennisbasis themes

Envisioning technology through discourse: a case study of biometrics in the National Identity Scheme in the United Kingdom

Around the globe, governments are pursuing policies that depend on information technology (IT). The United Kingdom’s National Identity Scheme was a government proposal for a national identity system, based on biometrics. These proposals for biometrics provide us with an opportunity to explore the diverse and shifting discourses that accompany the attempted diffusion of a controversial IT innovation. This thesis offers a longitudinal case study of these visionary discourses. I begin with a critical review of the literature on biometrics, drawing attention to the lack of in-depth studies that explore the discursive and organizational dynamics accompanying their implementation on a national scale. I then devise a theoretical framework to study these speculative and future-directed discourses based on concepts and ideas from organizing visions theory, the sociology of expectations, and critical approaches to studying the public’s understanding of technology. A methodological discussion ensues in which I explain my research approach and methods for data collection and analysis, including techniques for critical discourse analysis. After briefly introducing the case study, I proceed to the two-part analysis. First is an analysis of government actors’ discourses on biometrics, revolving around formal policy communications; second is an analysis of media discourses and parliamentary debates around certain critical moments for biometrics in the Scheme. The analysis reveals how the uncertain concept of biometrics provided a strategic rhetorical device whereby government spokespeople were able to offer a flexible yet incomplete vision for the technology. I contend that, despite being distinctive and offering some practical value to the proposals for national identity cards, the government’s discourses on biometrics remained insufficiently intelligible, uninformative, and implausible. The concluding discussion explains the unraveling visions for biometrics in the case, offers a theoretical contribution based on the case analysis, and provides insights about discourses on the ‘publics’ of new technology such as biometrics

Analysis Of Data Stratification In A Multi-Sensor Fingerprint Dataset Using Match Score Statistics

Biometric data is an essential feature employed in testing the performance of any real time biometric recognition system prior to its usage. The variations introduced in the match performance critically determine the authenticity of the biometric data to be able to be used in an everyday scenario for the testing of biometric verification systems. This study in totality aims at understanding the impact of data stratification of a such a biometric test dataset on the match performance of each of its stratum. In order to achieve this goal, the fingerprint dataset of the West Virginia University\u27s 2012 BioCOP has been employed which is a part of the many multimodal biometric data collection projects that the University has accomplished. This test dataset has been initially segmented based on the scanners employed in the process of data acquisition to check for the variations in match performance with reference to the acquisition device. The secondary stage of data stratification included the creation of stratum based on the demographic features of the subjects in the dataset.;The main objectives this study aims to achieve are:;• Developing a framework to assess the match score distributions of each stratum..;• Assessing the match performance of demographic strata in comparison to the total dataset..;• Statistical match performance evaluation using match score statistics..;Following the generation of genuine and imposter match score distributions , Receiver Operating Characteristic Curves (ROC) were plotted to compare the match performance of each demographic stratum with respect to the total dataset. The divergence measures KLD and JSD have been calculated which signify the amount of variation between the match score distributions of each stratum. With the help of these procedures, the task of estimating the effect of data stratification on the match performance has been accomplished which serves as a measure of understanding the impact of this fingerprint dataset when used for biometric testing purposes

Smart aging : utilisation of machine learning and the Internet of Things for independent living

Smart aging utilises innovative approaches and technology to improve older adults’ quality of life, increasing their prospects of living independently. One of the major concerns the older adults to live independently is “serious fall”, as almost a third of people aged over 65 having a fall each year. Dementia, affecting nearly 9% of the same age group, poses another significant issue that needs to be identified as early as possible. Existing fall detection systems from the wearable sensors generate many false alarms; hence, a more accurate and secure system is necessary. Furthermore, there is a considerable gap to identify the onset of cognitive impairment using remote monitoring for self-assisted seniors living in their residences. Applying biometric security improves older adults’ confidence in using IoT and makes it easier for them to benefit from smart aging. Several publicly available datasets are pre-processed to extract distinctive features to address fall detection shortcomings, identify the onset of dementia system, and enable biometric security to wearable sensors. These key features are used with novel machine learning algorithms to train models for the fall detection system, identifying the onset of dementia system, and biometric authentication system. Applying a quantitative approach, these models are tested and analysed from the test dataset. The fall detection approach proposed in this work, in multimodal mode, can achieve an accuracy of 99% to detect a fall. Additionally, using 13 selected features, a system for detecting early signs of dementia is developed. This system has achieved an accuracy rate of 93% to identify a cognitive decline in the older adult, using only some selected aspects of their daily activities. Furthermore, the ML-based biometric authentication system uses physiological signals, such as ECG and Photoplethysmogram, in a fusion mode to identify and authenticate a person, resulting in enhancement of their privacy and security in a smart aging environment. The benefits offered by the fall detection system, early detection and identifying the signs of dementia, and the biometric authentication system, can improve the quality of life for the seniors who prefer to live independently or by themselves