Mobile applications, solution for sustainable agriculture? - Study of mAgriculture services in Kenya

During the recent years, mobile services have spread to many different sectors, including education, health and agriculture, while changing the practices in those fields. Agriculture sector is under pressure to fill the ever-crowing food demand, while suffering from lack of agriculture resources (such as water and soil) and climate change, as well as figuring how to involve young people in the agriculture sector, in order to replace aging farmers. These issues create a need to bring new sustainable solutions to the agriculture sector. This is the demand, which mobile agriculture, mAgriculture, services are trying to answer. This thesis will examine the mAgriculture services in the Kenyan market. The thesis will provide an overview of the currently available mAgriculture services, their outcome and issues with which they are struggling. The thesis will also present recommendations on how to improve currently existing services and processes behind them. Secondly, thesis will provide four ideas for new services, which would answer for the needs of the farmers. Suitable business models, regarding the new services, are also covered. The thesis focuses with the young farmers as a target group, but findings are also applicable with other potential target groups as well.

A service perspective to digital innovation: exploring the emergence of autonomous shipping

Current research describes digital innovation largely similar to product innovation. Digital innovation is seen as an object of coherent activities, however in reality digital innovation results from convergence of variant technologies and those related actors with versatile business goals. To account for the dynamic nature of digital innovation, this study applies a service perspective to digital innovation. The purpose of the study is to understand how digital innovation emerges within a service ecosystem for autonomous shipping. The sub-objectives of this study are to 1) identify what factors motivate and demotivate actors to integrate resources for autonomous shipping, 2) explore the key technology areas to be integrated to realise the autonomous shipping concept, and 3) suggest how the technology areas are combined for mutual value creation within a service eco-system for autonomous shipping. Insights from autonomous driving were also included. This study draws on literatures on service innovation and service-dominant logic. The research was conducted as a qualitative exploratory case study. The data comprise interviews of 18 marine and automotive industry experts, 4 workshops, 4 seminars, and observations as well as various secondary data sources. The findings revealed that the key actors have versatile motivations regarding autonomous shipping. These varied from opportunities for single applications to occupying a central role in an autonomous technology platform. Thus, autonomous shipping can be seen as an umbrella concept comprising multiple levels. In technical terms, the development of the concept of autonomous shipping is largely based on combining existing technology solutions, which are gradually integrated towards more systemic entities comprising areas of the autonomous shipping concept. This study argues that a service perspective embraces the inherently complex and dynamic nature of digital innovation. This is captured in the developed research framework that describes digital innovation emerging on different levels of interaction: 1. strategic relationships for new solutions, 2. new local networks for technology platforms, and 3. global networks for new markets. The framework shows how the business models and motivations of digital innovation actors feed the emergence of digital innovation in overlapping service ecosystems that together comprise an innovation ecosystem for autonomous technologies. Digital innovation managers will benefit from seeing their businesses as part of a larger ecosystem of value co-creating actors. In orchestrating digital innovation within a service ecosystem, it is suggested that managers consider the resources, roles and institutions within the ecosystem. Finally, as autonomous shipping is at its infancy, the topic provides a number of interesting avenues for future research.

Marketing a Mobile Application in a Highly Competitive Global Marketplace

The purpose of this research was to study the marketing of mobile applications. The main objective was to find out what are the most efficient ways of marketing to increase the sales for a mobile application within a highly competitive marketplace. The marketplaces, app stores, are studied from the perspective of size, ease of entry, competition and customers and their purchasing process. The study also includes research on what are some of the main marketing methods used in mobile app marketing in general. The study consists of two parts, theoretical and empirical research. Theoretical research was done by studying past scientific research on the chosen subjects. As the subject is very new, the research was also extended to other publications from the field of mobile technology. The empirical part was done through interviews and empirical experiments with a case-company, which were used to answer the main objective of this study. These experiments showed that the chosen methods of mobile app marketing, app store optimization, localization and selected social media marketing activities, created the most sales when used together. Positive results were seen also when the activities were conducted by themselves, but together they were able to push the case company to their all time best results. However the key to succeeding and hitting high positions in the app store rankings would most likely require creating a solid marketing strategy, trying out other marketing activities alongside the ones used here, without forgetting to stay on top of mobile technology trends.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Real-time simulation of multibody systems with applications for working mobile vehicles

This dissertation describes an approach for developing a real-time simulation for working mobile vehicles based on multibody modeling. The use of multibody modeling allows comprehensive description of the constrained motion of the mechanical systems involved and permits real-time solving of the equations of motion. By carefully selecting the multibody formulation method to be used, it is possible to increase the accuracy of the multibody model while at the same time solving equations of motion in real-time. In this study, a multibody procedure based on semi-recursive and augmented Lagrangian methods for real-time dynamic simulation application is studied in detail. In the semirecursive approach, a velocity transformation matrix is introduced to describe the dependent coordinates into relative (joint) coordinates, which reduces the size of the generalized coordinates. The augmented Lagrangian method is based on usage of global coordinates and, in that method, constraints are accounted using an iterative process. A multibody system can be modelled as either rigid or flexible bodies. When using flexible bodies, the system can be described using a floating frame of reference formulation. In this method, the deformation mode needed can be obtained from the finite element model. As the finite element model typically involves large number of degrees of freedom, reduced number of deformation modes can be obtained by employing model order reduction method such as Guyan reduction, Craig-Bampton method and Krylov subspace as shown in this study The constrained motion of the working mobile vehicles is actuated by the force from the hydraulic actuator. In this study, the hydraulic system is modeled using lumped fluid theory, in which the hydraulic circuit is divided into volumes. In this approach, the pressure wave propagation in the hoses and pipes is neglected. The contact modeling is divided into two stages: contact detection and contact response. Contact detection determines when and where the contact occurs, and contact response provides the force acting at the collision point. The friction between tire and ground is modelled using the LuGre friction model, which describes the frictional force between two surfaces. Typically, the equations of motion are solved in the full matrices format, where the sparsity of the matrices is not considered. Increasing the number of bodies and constraint equations leads to the system matrices becoming large and sparse in structure. To increase the computational efficiency, a technique for solution of sparse matrices is proposed in this dissertation and its implementation demonstrated. To assess the computing efficiency, augmented Lagrangian and semi-recursive methods are implemented employing a sparse matrix technique. From the numerical example, the results show that the proposed approach is applicable and produced appropriate results within the real-time period.

Exploring knowledge worker motivation in autonomous and interdependent problem solving tasks on virtual platforms

The objective of this study is to understand why virtual knowledge workers conduct autonomous tasks and interdependent problem solving tasks on virtual platforms. The study is qualitative case study including three case organizations that tap the knowledge of expert networks, and utilize virtual platforms in the work processes. Research data includes 15 interviews, that is, five experts from each case company. According to the findings there are some specific characteristics in motivation to work on tasks on online platforms. Autonomy, self-improvement, meaningful tasks, knowledge sharing, time management, variety of contacts, and variety of tasks, and projects motivate virtual knowledge workers. Factors that may enhance individuals’ engagement to work on tasks are trust, security of continuous task flow and income, feedback, meaningful tasks and tasks that contribute to self-improvement, flexibility and effectiveness in time management, and virtual tools that support social interaction. The results also indicate that there are some differences in individuals’ motivation based on the tasks’ nature. That is, knowledge sharing and variety of contacts motivated experts who worked on interdependent problem solving tasks. Then again, autonomy and variety of tasks motivated experts who worked on autonomous tasks.

Robots, intencionalidade e inteligência artificial

O artigo aborda problemas filosóficos relativos à natureza da intencionalidade e da representação mental. A primeira parte apresenta um breve histórico dos problemas, percorrendo rapidamente alguns episódios da filosofia clássica e da filosofia contemporânea. A segunda parte examina o Chinese Room Argument (Argumento do Quarto do Chinês) formulado por J. Searle. A terceira parte desenvolve alguns argumentos visando mostrar a inadequação do modelo funcionalista de mente na construção de robots. A conclusão (quarta parte) aponta algumas alternativas ao modelo funcionalista tradicional, como, por exemplo, o conexionismo.

Adherence to Treatment in Psychotic Disorders - Development of user-centered mobile health intervention

The aim of this study was to explore adherence to treatment among people with psychotic disorders through the development of user-centered mobile technology (mHealth) intervention. More specifically, this study investigates treatment adherence as well as mHealth intervention and the factors related to its possible usability. The data were collected from 2010 to 2013. First, patients’ and professionals’ perceptions of adherence management and restrictive factors of adherence were described (n = 61). Second, objectives and methods of the intervention were defined based on focus group interviews and previously used methods. Third, views of patients and professionals about barriers and requirements of the intervention were described (n = 61). Fourth, mHealth intervention was evaluated based on a literature review (n = 2) and patients preferences regarding the intervention (n = 562). Adherence management required support in everyday activities, social networks and maintaining a positive outlook. The factors restricting adherence were related to illness, behavior and the environment. The objective of the intervention was to support the intention to follow the treatment guidelines and recommendations with mHealth technology. The barriers and requirements for the use of the mHealth were related to technology, organizational issues and the users themselves. During the course of the intervention, 33 (6%) out of 562 participants wanted to edit the content, timing or amount of the mHealth tool, and 23 (4%) quit the intervention or study before its conclusion. According to the review, mHealth interventions were ineffective in promoting adherence. Prior to the intervention, participants perceived that adherence could be supported, and the use of mHealth as a part of treatment was seen as an acceptable and efficient method for doing so. In conclusion, the use of mHealth may be feasible among people with psychotic disorders. However, clear evidence for its effectiveness in regards to adherence is still currently inconclusive.

Examining human-centered design practice in the mobile apps era

Human-Centered Design (HCD) is a well-recognized approach to the design of interactive computing systems that supports everyday and professional lives of people. To that end, the HCD approach put central emphasis on the explicit understanding of users and context of use by involving users throughout the entire design and development process. With mobile computing, the diversity of users as well as the variety in the spatial, temporal, and social settings of the context of use has notably expanded, which affect the effort of interaction designers to understand users and context of use. The emergence of the mobile apps era in 2008 as a result of structural changes in the mobile industry and the profound enhanced capabilities of mobile devices, further intensify the embeddedness of technology in the daily life of people and the challenges that interaction designers face to cost-efficiently understand users and context of use. Supporting interaction designers in this challenge requires understanding of their existing practice, rationality, and work environment. The main objective of this dissertation is to contribute to interaction design theories by generating understanding on the HCD practice of mobile systems in the mobile apps era, as well as to explain the rationality of interaction designers in attending to users and context of use. To achieve that, a literature study is carried out, followed by a mixed-methods research that combines multiple qualitative interview studies and a quantitative questionnaire study. The dissertation contributes new insights regarding the evolving HCD practice at an important time of transition from stationary computing to mobile computing. Firstly, a gap is identified between interaction design as practiced in research and in the industry regarding the involvement of users in context; whereas the utilization of field evaluations, i.e. in real-life environments, has become more common in academic projects, interaction designers in the industry still rely, by large, on lab evaluations. Secondly, the findings indicate on new aspects that can explain this gap and the rationality of interaction designers in the industry in attending to users and context; essentially, the professional-client relationship was found to inhibit the involvement of users, while the mental distance between practitioners and users as well as the perceived innovativeness of the designed system are suggested in explaining the inclination to study users in situ. Thirdly, the research contributes the first explanatory model on the relation between the organizational context and HCD; essentially, innovation-focused organizational strategies greatly affect the cost-effective usage of data on users and context of use. Last, the findings suggest a change in the nature of HCD in the mobile apps era, at least with universal consumer systems; evidently, the central attention on the explicit understanding of users and context of use shifts from an early requirements phase and continual activities during design and development to follow-up activities. That is, the main effort to understand users is by collecting data on their actual usage of the system, either before or after the system is deployed. The findings inform both researchers and practitioners in interaction design. In particular, the dissertation suggest on action research as a useful approach to support interaction designers and further inform theories on interaction design. With regard to the interaction design practice, the dissertation highlights strategies that encourage a more cost-effective user- and context-informed interaction design process. With the continual embeddedness of computing into people’s life, e.g. with wearable devices and connected car systems, the dissertation provides a timely and valuable view on the evolving humancentered design.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.