Nowadays, increasing numbers of people do travel research on their smartphones. More precisely, digital maps provide locational information, which is important during the planning process. However, smartphones are restricted by their small screen size, resulting in fragmented information delivery; also, the design of digital maps lacks features. The aims of this study are to investigate users’ travel-planning behavior on smartphones, identify the pain points and missing contexts when using digital maps on smartphones, and provide design guidelines for future digital map design. The study was done by conducting a travel-planning activity and a codesign workshop to bring users into the design process, promote in-depth discussion, and explore a new design possibility for digital maps with users. The results showed that people’s goals when planning travel include reducing their workload, improving effectiveness, and ensuring flexibility. People use digital maps to support not only information searching but also information compiling, including saving locations and routes. In addition, several difficulties have been pointed out: cross-platform planning, information hierarchy, and retrieval on digital maps.

<p>Ransomware, a form of malicious software, takes users’ files hostage via encryption and demands payment for their return. Since its inception, ransomware has branched into many different variants, some of which threaten users with scare tactics in order to evoke payment. For this study, four variants of ransomware were examined by presenting vignettes via an anonymous online survey. No actual malware was installed on any devices throughout this study. Their emotional responses were captured as well as their level of familiarity with information security. Responses to the survey after the simulated ransomware vignette were recorded to gauge how users would react to a ransomware attack. Data was analyzed to discover which types of ransomware evoked payment as well as if information security knowledge also had an effect on likelihood to pay. This data is intended to be used to develop better prevention methods and messaging, with an emphasis on promoting training on malware avoidance. The study found most individuals did not choose to pay, and this could be attributed to a distrust of the ransomware threat. Self-reported information security behavior appeared to decrease payment evocation, however, peer information security experience and prior exposure to malware appeared to increase payment evocation.</p>

Detecting human cognitive load is an increasingly important issue in the interaction between humans and machines, computers, and robots. In the past decade, several studies have sought to distinguish the cognitive load, or workload, state of humans based on multiple observations, such as behavioral, physiological, or multi-modal data. In the Human-Machine Interaction (HMI) cases, estimating human workload is essential because manipulators' performance could be adversely affected when they have many tasks that may be demanding. If the workload level can be detected, it will be beneficial to reallocate tasks on manipulators to improve the productivity of HMI tasks. However, it is still on question marks what kinds of cues can be utilized to know the degree of workload. In this research, eye blinking and mouse tracking are chosen as behavioral cues, exploring the possibility of a non-intrusive and automated workload estimator. During tests, behavior cues are statistically analyzed to find the difference among levels, using a dataset focused on three levels of the dual n-back memory game. The statistically analyzed signal is trained in a deep neural network model to classify the workload level. In this study, eye blinking related data and mouse tracking data have been statistically analyzed. The one-way repeated measure analysis of variance test result showed eye blinking duration on the dual 1-back and 3-back are significantly different. The mouse tracking data could not pass the statistical test. A three-dimension convolutional deep neural network is used to train visual data of human behavior. Classifying the dual 1-back and 3-back data accuracy is 51% with 0.66 F1-score on 1-back and 0.14 on 3-back data. In conclusion, blinking and mouse tracking are unlikely helpful cues when estimating different levels of workload. <br>

<div>Information security practitioners and researchers who possess sufficient depth of conceptual understanding to reconstitute systems after attacks or adapt information security concepts to novel situations are in short supply. Education of new information security professionals with sufficient conceptual depth is one method by which this shortage can be reduced. This study reports research that instructed two groups of ten undergraduate, pre-cryptography students majoring in Computer Science in cryptography concepts using representational understanding first and representational fluency first instructional treatment methods. This study compared learning results between the treatment groups using traditional paper-based measures of cognitions and fMRI scans of brain activity during cryptography problem solving. Analysis found no statistical difference in measures of cognitions or in cognitive processing, but did build a statistical model describing the relationships between explanatory variables and cryptography learning, and found common areas of cognitive processing of cryptography among the study’s twenty subjects.</div>

Abstract The aim of this thesis was twofold: firstly, to increase understanding about the user of health information; namely about differences of users´ characteristics of health information behaviour, and secondly, to contribute to the research on factors that could be used as bases to tailor health information. Health information behaviour was scrutinised as information needs and seeking and information use in particular. It was also studied in relation to individuals´ physical health status. More studies on information use are needed, because understanding individual characteristics in issues related to information use has been considered critical for promoting healthy behaviours. Moreover, the thesis addressed the gap in research on the relationship between health information behaviour and tailoring health information. The thesis consists of three empirical studies and a literature review. The empirical research environments were provided by an intervention study aiming to prevent type&#160;2 diabetes among a high risk population and by a population-based study among military conscription aged men. The setting was the City of Oulu in Northern Finland with the University of Oulu and the Oulu Deaconess Institute as the main operators of the studies. The empirical data were collected through questionnaires as well as through physiological and biochemical measurements during years 2010 and 2011. The data were analysed with statistical methods. Moreover, a literature review of tailored interventions studies using a computer as the medium of delivery in the context of physical activity, nutrition and weight management, was conducted. The findings indicate differences in health information users´ characteristics related to their information use as such and in relation to the indicators of their physical health status. It is suggested that, for example, health information presentation could be tailored on the basis of found differences and different message strategies and tactics could be used for different kinds of individuals. In addition, in the literature review the biases of tailored intervention studies stood out as influential on their outcomes. The thesis contributes to the current field of research on both health information behaviour and tailoring health communication. Moreover, the findings can support the development of more effective health promotion programs and intervention studies. / Tiivistelmä Väitöskirjatutkimukseni tavoitteena on lisätä ymmärrystä terveystiedon käyttäjistä ja erityisesti heidän terveysinformaatiokäyttäytymiseensä liittyvistä ominaisuuksista. Tutkimukseni tuottaa tietoa tekijöistä, joita voidaan käyttää terveystiedon räätälöinnin lähtökohtana. Terveysinformaatiokäyttäytymistä tarkastelen tiedontarpeiden ja -hankinnan sekä erityisesti tiedon käytön näkökulmasta. Informaatiokäyttäytymistä tutkitaan myös suhteessa tiedon käyttäjän fyysiseen terveydentilaan. Tutkimukseni vastaa tarpeeseen tutkia tiedon käyttäjiä, sillä tiedon käyttöön liittyvien yksilöllisten ominaisuuksien ymmärtäminen on keskeistä terveyden edistämisessä. Väitöskirja tuottaa uutta tietoa myös informaatiokäyttäytymisen ja terveystiedon räätälöinnin välisestä suhteesta. Väitöskirjani käsittää neljä osajulkaisua: kolme empiiristä tutkimusta ja kirjallisuuskatsauksen. Empiiriset tutkimukset toteutettiin tyypin&#160;2 diabeteksen ehkäisyyn tähtäävän interventiotutkimuksen (PreDiabEx) ja väestöpohjaisen tutkimuksen (MOPO) tarjoamissa tutkimusympäristöissä. Tutkimusten kohteina olivat miehet ja naiset, joiden riski sairastua tyypin&#160;2 diabetekseen oli korkea sekä kutsuntaikäiset miehet. Tutkimukset toteutettiin Oulussa ja päätoteuttajia olivat Oulun yliopisto ja Oulun Diakonissalaitos. Empiirinen aineisto kerättiin kyselyillä sekä fysiologisilla ja biokemiallisilla terveydentilaa ilmaisevilla mittareilla vuosien 2010 ja 2011 aikana. Aineisto analysoitiin tilastollisesti. Kirjallisuuskatsauksessa analysoidaan fyysisen aktiivisuuden, ravitsemuksen ja painonhallinnan interventiotutkimuksia, joissa tarkastellaan terveystiedon räätälöinnin vaikuttavuutta silloin, kun tiedonvälitykseen käytetään tietokonetta. Empiiristen tutkimusten tulokset viittaavat siihen, että niin terveystiedonkäyttäjien ominaisuuksissa informaatiokäyttäytymisessä kuin sen suhteessa heidän fyysisen terveydentilaansa on eroja. Terveystietoa tulisikin esittää eri tavoin erilaisille ihmisille, muun muassa erilaisia viestistrategioita ja -taktiikoita käyttäen. Kirjallisuuskatsauksen tulokset lisäsivät ymmärrystä siitä, miten tutkimusasetelman vinoumat voivat vaikuttaa interventiotutkimusten tuloksiin.

<p>Cybercrime and online scams are rampant in today’s tech-savvy world. In the past, scammers relied heavily on emails to contact potential victims but today, the presence and widespread usage of social networking platforms and e-commerce businesses has increased the availability of potential victims and made them easily accessible. It could be assumed that since unsuspecting users seek various products or services online - rentals, booking trips, seeking jobs, dating, it makes them easy targets for scammers yet, it is not just individual users who suffer from fraud, but organizations and institutions as well. A study at the Bank of America Merrill Lynch Global Research found that cybercrime costs the global economy up to approximately 540 billion euros annually. There is plenty of research on the technical measures that individuals and organizations may take to prevent themselves from falling prey to fraudsters, however, research trends in the recent past have shifted towards analyzing the human element present in the scenarios. Researchers have argued that identifying the underlying psychological and sociological factors used by fraudsters could help tackle the very root cause of such fraudulent attacks. While there exists some research focusing on the experiences and psychology of victims of these attacks as well as the countermeasures that can be taken to protect them from such attacks, there is little research on the psychology and motivation of those who commit online fraud. This study aims to identify the psychological factors that affect the predilection of scammers to commit online fraud.</p>

<p dir="ltr">Asian international students face various challenges and emotional issues during the process of acculturation, often finding it difficult to truly connect with the domestic culture. Current research often focuses on interactions and adaptation within the international student community, with little mention of how international students communicate with domestic students. Especially in the digital age, the ways people acquire information and communicate have evolved significantly from the past. This research takes into account the current era's context, seeks to understand the current status and needs of new Asian international students and propose further assistance guidelines. It employed interviews and co-design activities to delve into the issues from the perspective of Asian international students, encouraging them to integrate into the domestic culture. The findings suggest that new Asian students encounter similar challenges and utilize various strategies, with a view to fostering social connections with domestic students in future platforms.</p>

<div>This thesis combines human and machine intelligence for consensus decision-making, and it contains four interrelated research areas. Before presenting the four research areas, this thesis presents a literature review on decision-making using two criteria: trust and risk. The analysis involves studying the individual and the multi-stakeholder decision-making. Also, it explores the relationship between trust and risk to provide insight on how to apply them when making any decision. This thesis presents a grouping procedure of the existing trust-based multi-stakeholder decision-making schemes by considering the group decision-making process and models. In the first research area, this thesis presents the foundation of building multi-stakeholder consensus decision-making (MSCDM). This thesis describes trust-based multi-stakeholder decision-making for water allocation to help the participants select a solution that comes from the best model. Several criteria are involved when deciding on a solution such as trust, damage, and benefit. This thesis considers Jain's fairness index as an indicator of reaching balance or equality for the stakeholder's needs. The preferred scenario is when having a high trust, low damages and high benefits. The worst scenario involves having low trust, high damage, and low benefit. The model is dynamic by adapting to the changes over time. The decision to select is the solution that is fair for almost everyone. In the second research area, this thesis presents a MSCDM, which is a generic framework that coordinates the decision-making rounds among stakeholders based on their influence toward each other, as represented by the trust relationship among them. This thesis describes the MSCDM framework that helps to find a decision the stakeholders can agree upon. Reaching a consensus decision might require several rounds where stakeholders negotiate by rating each other. This thesis presents the results of implementing MSCDM and evaluates the effect of trust on the consensus achievement and the reduction in the number of rounds needed to reach the final decision. This thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in the stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the distance of the choices made by the stakeholders. Trust is useful in decreasing the distances. In the third research area, this thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the perturbation in the rating matrix. Trust is useful in increasing the rating matrix perturbation. Such perturbation helps to decrease the number of rounds. Therefore, trust helps to increase the speed of agreeing upon the same decision through the influence. In the fourth research area, this thesis presents Rating Aggregation operators in the implemented MSCDM framework. This thesis addresses the need for aggregating the stakeholders' ratings while they negotiate on the round of decisions to compute the consensus achievement. This thesis presents four aggregation operators: weighted sum (WS), weighted product (WP), weighted product similarity measure (WPSM), and weighted exponent similarity measure (WESM). This thesis studies the performance of those aggregation operators in terms of consensus achievement and the number of rounds needed. The consensus threshold controls the performance of these operators. The contribution of this thesis lays the foundation for developing a framework for MSCDM that facilitates reaching the consensus decision by accounting for the stakeholders' influences toward one another. Trust represents the influence.</div>

Abstract This dissertation aims to uncover emerging practices in how people seek information while on the move in augmented urban spaces. The backdrop for a majority of the work presented here is the City of Oulu in Finland, where we have installed a variety of new ubiquitous computing infrastructure and services including, among others, a network of large interactive public displays called UBI-hotspots. The hotspots serve as a versatile platform on top of which new types of services can be developed, deployed and tested in an authentic urban setting with real, non-coached users and a sufficiently long timespan to truly evaluate the impact of such services on the everyday life and practices of the city and its citizens. The case studies presented in this dissertation aim at understanding the effect of such highly visible additions to the urban space from the point of view of human information behaviour. I seek to understand the underlying information seeking strategies people employ while foraging the hotspots for information, and the types of information people see as valuable while attending their daily business in the downtown area of the City. Questions such as how do people utilize the new sources of information in their daily information seeking tasks, and what is the preferred medium for information delivery, are addressed. The theoretical framework for the studies is derived from both ubiquitous and urban computing, and from the field of human information behaviour research. The main findings of the presented studies indicate that people have adapted the new infrastructure and services as parts of their daily information seeking tasks. The detailed usage data logged by all hotspots provide insight into the browsing habits of users, and analysis of inter-session navigation show that various latent strategies of information seeking exist. Further, findings indicate that there is a clear difference between the types of services people perceive as useful prior to using the hotspots, and services that people actually use on the hotspots. Also, findings indicate that people are willing to download information items from the hotspots to their mobile devices for later reference, thus adding information to their personal information repository. / Tiivistelmä Tämä väitöskirja pyrkii löytämään ja selittämään uusia tapoja joilla ihmiset etsivät informaatiota älykkäissä kaupunkitiloissa. Tausta suurelle osalle työstä on Oulun kaupunki, jonne olemme asentaneet erilaisia jokapaikan tietotekniikan laitteistoja sekä palveluja. Erityisesti väitöskirjassa tutkitaan suurten julkisten näyttöjen – ”UBI-näyttöjen” – verkostoa. UBI-näytöt toimivat monipuolisena alustana jonka päällä uusia palveluja voidaan kehittää sekä testata autenttisessa kaupunkitilassa todellisten käyttäjien toimesta riittävän pitkällä aikavälillä, joka puolestaan mahdollistaa palveluiden todellisen merkittävyyden arvioimisen suhteessa ihmisten jokapäiväiseen informaatiokäyttäytymiseen sekä informaatiotarpeisiin. Väitöskirjassa esitetyt tapaustutkimukset pyrkivät ymmärtämään tällaisten erittäin näkyvien tietoteknisten laitteiden vaikutusta ihmisten käyttäytymiseen informaatiotutkimuksen näkökulmasta. Tarkastelun kohteena ovat ihmisten jokapäiväiseen tiedonhakuun liittyvät strategiat heidän käyttäessään UBI-näyttöjä, sekä erilaiset informaatiotyypit joita ihmiset pitävät tärkeinä hoitaessaan jokapäiväisiä asioitaan kaupunkitiloissa. Kysymykset kuten kuinka ihmiset käyttävät uusia informaation lähteitä etsiessään tietoa jokapäiväisiin tarpeisiinsa sekä millä laitteilla ihmiset mieluiten etsivät ko. tietoa ohjaavat suurta osaa tutkimuksesta. Tutkimuksen teoreettinen viitekehys muodostuu jokapaikan tietotekniikan tutkimuksesta, urbaanin tietotekniikan tutkimuksesta, sekä ihmisten informaatiokäyttäytymisen tutkimuksesta. Tutkimuksen tärkeimmät löydökset osoittavat että ihmiset ovat ottaneet uudet tietotekniset resurssit osaksi päivittäistä informaatiokäyttäytymistään. Yksityiskohtainen lokitieto yhdistettynä haastattelu- ja havainnointidataan tarjoaa syvällisen näkemyksen käyttäjien tiedontarpeisiin. Dataa analysoimalla olemme havainneet joukon strategioita joita ihmiset käyttävät etsiessään tietoa kaupunkitiloissa. Tutkimus osoittaa myös, että ihmisten oletettujen tiedontarpeiden sekä havainnoidun käyttäytymisen välillä on suuria eroavaisuuksia. Käyttäjät ovat myös halukkaita lataamaan tietosisältöä matkapuhelimiinsa myöhempää käyttöä varten, täten lisäten tietoa omaan henkilökohtaiseen tietovarastoonsa.

Although many counter-drone systems such as drone jammers and anti-drone guns have been implemented, drone incidents are still increasing. These incidents are categorized as deviant act, a criminal act, terrorist act, or an unintentional act (aka system failure). Examples of reported drone incidents are not limited to property damage, but include personal injuries, airport disruption, drug transportation, and terrorist activities. Researchers have examined only drone incidents from a technological perspective. The variance in drone architectures poses many challenges to the current investigation practices, including several operation approaches such as custom commutation links. Therefore, there is a limited research background available that aims to study the intercomponent mapping in unmanned aircraft system (UAS) investigation incorporating three critical investigative domains---behavioral analysis, forensic intelligence (FORINT), and unmanned aerial vehicle (UAV) forensic investigation. The UAS forensic intelligence-led taxonomy (U-FIT) aims to classify the technical, behavioral, and intelligence characteristics of four UAS deviant actions --- including individuals who flew a drone too high, flew a drone close to government buildings, flew a drone over the airfield, and involved in drone collision. The behavioral and threat profiles will include one criminal act (i.e., UAV contraband smugglers). The UAV forensic investigation dimension concentrates on investigative techniques including technical challenges; whereas, the behavioral dimension investigates the behavioral characteristics, distinguishing among UAS deviants and illegal behaviors. Moreover, the U-FIT taxonomy in this study builds on the existing knowledge of current UAS forensic practices to identify patterns that aid in generalizing a UAS forensic intelligence taxonomy. The results of these dimensions supported the proposed UAS forensic intelligence-led taxonomy by demystifying the predicted personality traits to deviant actions and drone smugglers. The score obtained in this study was effective in distinguishing individuals based on certain personality traits. These novel, highly distinguishing features in the behavioral personality of drone users may be of particular importance not only in the field of behavioral psychology but also in law enforcement and intelligence.