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Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement.

In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built.

The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains.

The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

This paper aims to analyze and evaluate the arguments provided in Gema Dari Menara that aim to justify Islamic prohibitions. The first part of this paper will attempt to indicate that the arguments concerning Islam’s prohibition of certain activities are surprisingly secular in their justification, in the sense that their reasoning rests on mundane empirical considerations rather than lofty theological exhortations. For instance, pre-marital sex must be prohibited because it would “ruin one’s personality and community”, Bruneians should not gamble because people who do so “forget their own responsibilities”, and alcohol should not be consumed because it can “ruin a sound mind and one’s personality”. These justifications do not appeal to the divine but instead refer to phenomena that can be observed, measured, and quantified. The second part of this paper will consider the implications of trying to justify absolute religious prohibitions through secular considerations. It will be argued that in doing so the film opens itself to empirical queries that must be addressed for the film to have its desired effect. This paper ultimately draws attention to some of the challenges facing religious apologetics as the social sciences gain prominence.

This study aims to investigate why anti-corruption statutes are not efficient in Nigeria’s upstream petroleum industry.

This study is a doctrinal legal research that embraces a point-by-point comparative methodology with a library research technique.

This study reveals that corruption strives on feeble implementation of anti-corruption legal regime and the absence of political will in offering efficient regulatory intervention. Finally, this study finds that anti-corruption organisations in Nigeria are not efficient due to non-existence of the Federal Government’s political will to fight corruption, insufficient funds and absence of stringent implementation of the anti-corruption legal regime in the country.

Investigations reveal during this study that Nigerian National Petroleum Corporation (NNPC) operations are characterised with poor record-keeping, lack of accountability as well as secrecy in the award of oil contracts, oil licence, leases and other financial transactions due to non-disclosure or confidentiality clauses contained in most of these contracts. Also, an arbitration proceeding limit access to their records and some of these agreements under contentions. This has also limited the success of this research work and generalising its findings.

This study recommends, among other reforms, soft law technique and stringent execution of anti-corruption statutes. This study also recommends increment in financial appropriation to Nigeria’s anti-corruption institutions, taking into consideration the finding that a meagre budget is a drawback.

This study reveals that corruption strives on feeble implementation of anti-corruption legal regime and the absence of political will in offering efficient regulatory intervention. Corruption flourishes due to poor enforcement of anti-corruption laws and the absence of political will in offering efficient regulatory intervention by the government.

The study advocates the need for enhancement of anti-corruption agencies' budgets taking into consideration the finding that meagres budgets are challenge of the agencies.

An increasing demand of agricultural intensification and value addition necessitates the use of improved inputs such as improved seed. Smallholder farmers contribute about 70% of agricultural production in Tanzania. Agriculture sector in Tanzania contributes about 24.1% of the GDP, 30% of exports and 65% of industrial raw materials. Thus, agriculture development, economic growth and industrialization are inseparable. Due to the nature of the product, smallholder farmers cannot judge the overall excellence of seed at the time of buying. This paper assessed quality uncertainty in maize and vegetable seed and its implication for market exchange between farmers and seed sellers in Kilolo district, Iringa Tanzania. The study used a random sample of 130 smallholder farmers and representatives from ten seed companies. Asymmetric information prevails between the two trading sides, i.e. sellers and buyers, leading into quality uncertainty. Moreover, product augmentation is profoundly overlooked whereby most of seed companies have not augmented their products. Because an improved seed is a quintessential example of an experience good, quality uncertainty of some crop varieties under field conditions favored some seed brands to be used more by farmers compared to others. This paper offers a thorough deduction on quality uncertainty under farmers' field condition and its implication on market exchange. It adds information in the body of knowledge on how an improved seed can contribute to sustainable production of food and industrial raw materials, which is a step towards desired industrialization agenda in Tanzania.

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

Violence against women and girls is globally prevalent. Overcoming it is a prerequisite for attaining gender equality and achieving sustainable development. The United Nation's 2030 Agenda for Sustainable Development considers technology as a means to combat violence against women and girls, and there is ample evidence on the positive impact of technology in combating violence. At the same time, however, technology can promote and perpetrate new forms of violence. Research shows that more than 70% of women and girls online are exposed to forms of cyber violence. Most of these cases remain unreported.

This chapter argues that technology contributes to increasing cyber violence against women and girls which in turn leads to severe social and economic implications affecting them. It also argues that legislative and policy reforms can limit this type of violence while enabling women and girls to leverage technology for empowerment. It highlights cases of cyber violence in the Arab region and provides an overview of applicable legislative frameworks. The chapter concludes with recommended policy reforms and measures to strengthen and harmonize efforts to combat cyber violence against women and girls in the Arab region.

This study introduces the concept of audiovisual alerts and warnings as a way to reduce phishing susceptibility on mobile devices.

This study has three phases. The first phase included 32 subject matter experts that provided feedback toward a phishing alert and warning system. The second phase included development and a pilot study to validate a phishing alert and warning system prototype. The third phase included delivery of the Phishing Alert and Warning System (PAWS^TM mobile app) to 205 participants. This study designed, developed, as well as empirically tested the PAWS^TM mobile app that alerted and warned participants to the signs of phishing in emails on mobile devices.

The results of this study indicated audio alerts and visual warnings potentially lower phishing susceptibility in emails. Audiovisual warnings appeared to assist study participants in noticing phishing emails more easily and in less time than without audiovisual warnings.

This study's implications to mitigation of phishing emails are key, as it appears that alerts and warnings added to email applications may play a significant role in the reduction of phishing susceptibility.

This study extends the existing information security body of knowledge on phishing prevention and awareness by using audiovisual alerts and warnings to email recipients tested in real-life applications.