Typicality degrees to measure relevance of the physiological signals

Paper presented at the International Conference on Physiological Computing Systems (PhyCS), Lisbon, Portugal.Physiological measures have a key advantage as they can provide an insight into human feelings that the subjects may not even be consciously aware of. However, modeling user affective states through pysiology still remains with critical questions especially on the relevant physiological measures for real-life emotionally intelligent applications. In this study, we propose the use of typicality degrees defined according to cognitive science and psychology principles to measure the relevance of the physiological features in characterizing user affective states. Thanks to the typicality degrees, we found consistent physiological characteristics for modeling user affective states.Physiological measures have a key advantage as they can provide an insight into human feelings that the subjects may not even be consciously aware of. However, modeling user affective states through pysiology still remains with critical questions especially on the relevant physiological measures for real-life emotionally intelligent applications. In this study, we propose the use of typicality degrees defined according to cognitive science and psychology principles to measure the relevance of the physiological features in characterizing user affective states. Thanks to the typicality degrees, we found consistent physiological characteristics for modeling user affective states

Embedded system for vehicle speed monitoring

The conference aimed at supporting and stimulating active productive research set to strengthen the technical foundations of engineers and scientists in the continent, through developing strong technical foundations and skills, leading to new small to medium enterprises within the African sub-continent. It also seeked to encourage the emergence of functionally skilled technocrats within the continent.This paper investigated the impact of current approaches taken to curb speeding of public service vehicles in Kenya. A qualitative research pointed out that the existing systems are inefficient and ineffective in monitoring speeding and reporting speeding offenses to the relevant authorities. In addition, public service vehicle drivers are not aware of the current speed limit zones in various locations given that the National Transport Service Authority (NTSA) periodically changes speed limit regulations along particular roads. An embedded system for vehicle speed monitoring was proposed and tested. The objective was to design a real time microcontroller based system for mapping speed limit zones and reporting cases of speeding violations to the relevant authorities through an android mobile application. An LCD Screen was integrated to the microcontroller to provide a visual display of the vehicle location and speed limit within the location. In the event of speeding, an audio alert is triggered to notify the driver and an SMS is sent from the GSM module to a central server. Through this system, public service drivers are aware of the speed limit zones on various roads and are alerted once the speed limit is exceeded. The real time reporting system enables the transport agencies and other regulatory bodies to equally monitor speeding vehicles on the roads.Strathmore University; Institute of Electrical and Electronics Engineers (IEEE

Mapping of terrorist activities in Kenya using sentiment analysis

The conference aimed at supporting and stimulating active productive research set to strengthen the technical foundations of engineers and scientists in the continent, through developing strong technical foundations and skills, leading to new small to medium enterprises within the African sub-continent. It also seeked to encourage the emergence of functionally skilled technocrats within the continent.Terrorism has become a subject of concern to many people in Kenya today. Corruption, porous border and lack of government in the neighboring Somali, have made Kenya a potential target for terrorists’.The advancement in technology has brought a new era in criminal activities where Online Social Networks such as Twitter,Facebook has driven the increase use of the internet by criminal organizations and their supporters for a wide range of purposes including recruitment, financing, propaganda, incitement and gathering and dissemination of information for criminal activities such as threats, incitement to imminent violence, harassing speech, libelous speech etc.Although the Kenya government improved its ability to fight terrorism the changing pattern of terrorist activities, human errors and delayed crime analyses have given criminals more time to destroy evidence and escape arrest.The main objective is to test and validate a technique that can be used to establish crime patterns associated with terrorist activities using sentiment information deduced from twitter data.The data collected will then be used as features for training and development of the algorithm which will then be used to carry out real time mapping of terrorist activities. The algorithm’s performance will be then measured for accuracy.Strathmore University; Institute of Electrical and Electronics Engineers (IEEE

Vehicle exhaust emissions inspection system for roadworthiness enforcement

The conference aimed at supporting and stimulating active productive research set to strengthen the technical foundations of engineers and scientists in the continent, through developing strong technical foundations and skills, leading to new small to medium enterprises within the African sub-continent. It also seeked to encourage the emergence of functionally skilled technocrats within the continent.Air pollution has been a growing concern as Kenya tries to industrialize. Increase in the number of vehicles and factories as well as constructions in Nairobi make this all the more critical. This polluted air has far reaching consequences which include illnesses that lead to death. Measuring the concentration of air pollutants is necessary to establish the quality of air in the city. By extension, measuring the concentration of pollutants being emitted through vehicle exhaust fumes can help establish if the vehicle is worthy to be on the road. To best measure the degree of these pollutants, random on-the-road inspection of vehicle inspection of vehicle exhaust emissions is key. However, this has not been achieved by the Kenyan law enforcement agencies. The ability to inspect the emissions from cars on the road will help law enforcement remove unroadworthy vehicles from the roads and thus minimize air pollution caused by vehicles. Conventional inspection methods are done in controlled environments such as laboratories. Vehicles are driven in and are inspected while they remain stationary. These controlled tests fall short of revealing the true state of a vehicle’s exhaust emissions: the fumes emitted while a car is on open road are different in composition from those emitted in such a controlled environment. In addition, manufacturers can tweak their vehicles to emit gases that are within the prescribed thresholds as was done by Volkswagen in order to meet and exceed the US Environment Protection Agency standards. This study will present a model that utilizes sensors to assess the level of pollutants produced from a vehicle exhaust to the air and register these to back-end server hosted on the cloud. The model will have an LCD screen on which law enforcement can view levels of pollutants as measured by the sensors. The information will be stored inStrathmore University; Institute of Electrical and Electronics Engineers (IEEE

Characterizing player’s experience from physiological signals using fuzzy decision trees

Author manuscript, published in "IEEE Conference on Computational Intelligence and Games (CIG) 2010, Copenhagen : Denmark (2010)"In the recent years video games have enjoyed a dramatic increase in popularity, the growing market being echoed by a genuine interest in the academic field. With this flourishing technological and theoretical efforts, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player’s subjective experience, and especially the emotional aspect. In this study, we addressed the possibility of developing a model for assessing the player’s enjoyment (amusement) with respect to challenge in an action game. Our aim was to explore the viability of a generic model for assessing emotional experience during gameplay from physiological signals. In particular, we propose an approach to characterize the player’s subjective experience in different psychological levels of enjoyment from physiological signals using fuzzy decision trees.In the recent years video games have enjoyed a dramatic increase in popularity, the growing market being echoed by a genuine interest in the academic field. With this flourishing technological and theoretical efforts, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player’s subjective experience, and especially the emotional aspect. In this study, we addressed the possibility of developing a model for assessing the player’s enjoyment (amusement) with respect to challenge in an action game. Our aim was to explore the viability of a generic model for assessing emotional experience during gameplay from physiological signals. In particular, we propose an approach to characterize the player’s subjective experience in different psychological levels of enjoyment from physiological signals using fuzzy decision trees

ASSESSING GAMEPLAY EMOTIONS FROM PHYSIOLOGICAL SIGNALS: A FUZZY DECISION TREES BASED MODEL

International audienceAs video games become a widespread form of entertainment, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player's subjective experience, and especially the emotional aspect. Video game developers could benefit from being aware of how the player reacts emotionally to specific game parameters. In this study, we addressed the possibility to record physiological measures on players involved in an action game, with the main objective of developing adequate models to describe emotional states. Our goal was to estimate the emotional state of the player from physiological signals so as to relate these variations of the autonomic nervous system to the specific game narratives. To achieve this, we developed a fuzzy set theory based model to recognize various episodes of the game from the user's physiological signals. We used fuzzy decision trees to generate the rules that map these signals to game episodes characterized by a variation of challenge at stake. A specific advantage to our approach is that we automatically recognize game episodes from physiological signals with explicitly defined rules relating the signals to episodes in a continuous scale. We compare our results with the actual game statistics information associated with the game episode

Assessing Gameplay Emotions from physiological signals: a fuzzy decision trees based model

Paper presented at INTERNATIONAL CONFERENCE ON KANSEI ENGINEERING AND EMOTION RESEARCH 2010, KEER2010, PARIS | MARCH 2-4 2010As video games become a widespread form of entertainment, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player’s subjective experience, and especially the emotional aspect. Video game developers could benefit from being aware of how the player reacts emotionally to specific game parameters. In this study, we addressed the possibility to record physiological measures on players involved in an action game, with the main objective of developing adequate models to describe emotional states. Our goal was to estimate the emotional state of the player from physiological signals so as to relate these variations of the autonomic nervous system to the specific game narratives. To achieve this, we developed a fuzzy set theory based model to recognize various episodes of the game from the user’s physiological signals. We used fuzzy decision trees to generate the rules that map these signals to game episodes characterized by a variation of challenge at stake. A specific advantage to our approach is that we automatically recognize game episodes from physiological signals with explicitly defined rules relating the signals to episodes in a continuous scale. We compare our results with the actual game statistics information associated with the game episodes.As video games become a widespread form of entertainment, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player’s subjective experience, and especially the emotional aspect. Video game developers could benefit from being aware of how the player reacts emotionally to specific game parameters. In this study, we addressed the possibility to record physiological measures on players involved in an action game, with the main objective of developing adequate models to describe emotional states. Our goal was to estimate the emotional state of the player from physiological signals so as to relate these variations of the autonomic nervous system to the specific game narratives. To achieve this, we developed a fuzzy set theory based model to recognize various episodes of the game from the user’s physiological signals. We used fuzzy decision trees to generate the rules that map these signals to game episodes characterized by a variation of challenge at stake. A specific advantage to our approach is that we automatically recognize game episodes from physiological signals with explicitly defined rules relating the signals to episodes in a continuous scale. We compare our results with the actual game statistics information associated with the game episodes

Modélisation de systèmes émotionnels à partir de signaux physiologiques et application dans la conception de jeux vidéo

Les émotions jouant un rôle essentiel dans les rapports humains, il est important de développer des méthodologies pour évaluer les états émotionnels ressentis par un utilisateur lorsqu'il interagit avec des ordinateurs. Dans le domaine de la conception des jeux vidéo en particulier, ce besoin est primordial. Dans ce contexte, les mesures physiologiques ont un avantage clé parce qu'elles permettent un accès à des processus inconscients. Mais, faire correspondre des motifs physiologiques à des émotions reste encore une tâche extrêmement difficile. Dans cette thèse, nous développons un modèle d'apprentissage automatique le plus adapté à cette tâche particulière. Nous avons considéré deux méthodologies: l'apprentissage automatique par des arbres de décision flous, et la construction automatique de prototypes flous grâce aux calculs de typicalité. Grâce à ce modèle, nous avons développé un contrôleur flou psychophysiologique capable de mesurer de manière continue des états émotionnels.PARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

Gradual Pattern Mining Tool on Cloud

National audienceThis paper describes an approach that illustrates how gradual pattern mining algorithms are integrated into a containerized Docker Cloud platform that implements OGC (Open Geospatial Consortium) SensorThings API (application interface). We present a practical application of the SensorThings API as a source of real-time data streams and propose an architecture that allows for extraction of gradual patterns among these data streams

Integrated Intrusion Detection Security System Model

A Thesis submitted in partial fulfillment of the requirements for the Degree of Masters of Science in Information Technology at Strathmore UniversityOrganizations are investing heavily in security systems to secure their premises and assets . In an effort to enhance security, organizations have turned to the adoption of Intrusion Detection Systems. lDSs have improved in efficiency and effectiveness in the way they detect and respond to intrusions. They are moving from manual detection of intrusions to automated detection of intrusions. Most of the existing IDSs are stand-alone hence making it difficult to associate intrusions. They also cannot offer a complete organization security hence needs to be integrated with other system security components. Exploratory research design was adopted in coming up with the solution due to the nature of the study. Data was collected through questionnaires, journals, theses and observation of existing security systems. The collected data was organized and analyzed using SPSS tool. The finding and analysis of the data were presented in descriptive statistics where tables, percentage and charts were used. The model developed was informed by the research findings that showed most organizations secure their premises and assets but lack a standardized model to integrate different security system components. An Integrated Intrusion Detection Security System Model provides a standard for developing systems to integrate different security system components in an organization. The integration of heterogeneous IDSs and different security system components improves the security performance as this associates different security system components to share intrusion information