IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

Real-Time PCR Assays for the Detection of Puccinia psidii

Puccinia psidii (Myrtle rust) is an emerging pathogen that has a wide host range in the Myrtaceae family; it continues to show an increase in geographic range and is considered to be a significant threat to Myrtaceae plants worldwide. In this study, we describe the development and validation of three novel real-time polymerase reaction (qPCR) assays using ribosomal DNA and β-tubulin gene sequences to detect P. psidii. All qPCR assays were able to detect P. psidii DNA extracted from urediniospores and from infected plants, including asymptomatic leaf tissues. Depending on the gene target, qPCR was able to detect down to 0.011 pg of P. psidii DNA. The most optimum qPCR assay was shown to be highly specific, repeatable, and reproducible following testing using different qPCR reagents and real-time PCR platforms in different laboratories. In addition, a duplex qPCR assay was developed to allow coamplification of the cytochrome oxidase gene from host plants for use as an internal PCR control. The most optimum qPCR assay proved to be faster and more sensitive than the previously published nested PCR assay and will be particularly useful for high-throughput testing and to detect P. psidii at the early stages of infection, before the development of sporulating rust pustules.

Experimental and analytical investigation of refrigerant and lubricant migration

The off-cycle refrigerant mass migration has a direct influence on the on-cycle performance since compressor energy is necessary to redistribute the refrigerant mass. No studies, as of today, are available in the open literature which experimentally measured the lubricant migration within a refrigeration system during cycling or stop/start transients. Therefore, experimental procedures measuring the refrigerant and lubricant migration through the major components of a refrigeration system during stop/start transients were developed and implemented. Results identifying the underlying physics are presented. The refrigerant and lubricant migration of an R134a automotive A/C system-utilizing a fixed orifice tube, minichannel condenser, plate and fin evaporator, U-tube type accumulator and fixed displacement compressor-was measured across five sections divided by ball valves. Using the Quick-Closing Valve Technique (QCVT) combined with the Remove and Weigh Technique (RWT) using liquid nitrogen as the condensing agent resulted in a measurement uncertainty of 0.4 percent regarding the total refrigerant mass in the system. The determination of the lubricant mass distribution was achieved by employing three different techniques-Remove and Weigh, Mix and Sample, and Flushing. To employ the Mix and Sample Technique a device-called the Mix and Sample Device-was built. A method to separate the refrigerant and lubricant was developed with an accuracy-after separation-of 0.04 grams of refrigerant left in the lubricant. When applying the three techniques, the total amount of lubricant mass in the system was determined to within two percent. The combination of measurement results-infrared photography and high speed and real time videography-provide unprecedented insight into the mechanisms of refrigerant and lubricant migration during stop-start operation. During the compressor stop period, the primary refrigerant mass migration is caused by, and follows, the diminishing pressure difference across the expansion device. The secondary refrigerant migration is caused by a pressure gradient as a result of thermal nonequilibrium within the system and causes only vapor phase refrigerant migration. Lubricant migration is proportional to the refrigerant mass during the primary refrigerant mass migration. During the secondary refrigerant mass migration lubricant is not migrating. The start-up refrigerant mass migration is caused by an imbalance of the refrigerant mass flow rates across the compressor and expansion device. The higher compressor refrigerant mass flow rate was a result of the entrainment of foam into the U-tube of the accumulator. The lubricant mass migration during the start-up was not proportional to the refrigerant mass migration. The presence of water condensate on the evaporator affected the refrigerant mass migration during the compressor stop period. Caused by an evaporative cooling effect the evaporator held 56 percent of the total refrigerant mass in the system after three minutes of compressor stop time-compared to 25 percent when no water condensate was present on the evaporator coil. Foam entrainment led to a faster lubricant and refrigerant mass migration out of the accumulator than liquid entrainment through the hole at the bottom of the U-tube. The latter was observed for when water condensate was present on the evaporator coil because-as a result of the higher amount of refrigerant mass in the evaporator before start-up-the entrainment of foam into the U-tube of the accumulator ceased before the steady state refrigerant mass distribution was reached.

STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

Improving the assessment and outcome of free tissue transfer breast reconstruction

Introduction: Free tissue transfer using an abdominal tissue flap is a commonly used method of breast reconstruction. However, there are well recognised complications including venous congestion, fat necrosis and flap loss associated with the perfusion of these flaps. Post-operative aesthetic outcome assessment of such breast reconstructions have also proven to be difficult with current methods displaying poor inter-rater reliability and patient correlation. The aim of this research was to investigate potential improvements to the post-operative outcome of free abdominal tissue transfer breast reconstruction by assessing the effects of vascular augmentation interventions on flap perfusion and to assess the use of real-time digital video as a post-operative assessment tool. Methods: An in-vivo pilot study carried out on 12 patients undergoing DIEP flap breast reconstruction assessed the effect on Zone IV perfusion, using LDI and ICG angiography, of vascular augmentation of the flap using the contralateral SIEA and SIEV. A further animal experimental study was carried out on 12 Sprague Dawley rats to assess the effects on main pedicle arterial blood flow and on Zone I and Zone IV perfusion of vascular augmentation of the abdominal flap using the contralateral vascular system. A separate post-operative assessment study was undertaken on 35 breast reconstruction patients who evaluated their own reconstructions via patient questionnaire and underwent photograph and real-time digital video capture of their reconstructions with subsequent panel assessment. Results: Our results showed that combined vascular augmentation of DIEP flaps, using both the SIEA and SIEV together, led to an increase in Zone IV perfusion. Vascular augmentation of the rat abdominal flaps also led to a significant increase in Zone I/IV perfusion, but the augmentation procedure resulted in a decreased main pedicle arterial blood flow. Our post-operative assessment study revealed that real-time digital video footage led to greater inter-rater agreement with regards to cosmesis and shape than photography and also correlated more with patient self-assessment. Conclusion: Vascular augmentation of abdominal free tissue flaps using the contralateral vascular system results in an increase to Zone IV perfusion, however this may lead to decreased main pedicle arterial blood flow. Real-time digital video is a valid post-operative aesthetic assessment method of breast reconstruction outcome and is superior to static photography when coupled with panel assessment.

Art and the Body Image: about Self and Stereotypes

Today's man is socially absorbed by problematic body issues and everything that this means and involves. Literature, publicity, science, technology and medicine compound these issues in a form of this theme that has never been seen before. In the artistic framework, body image is constantly suffering modifications. Body image in sculpture unfolds itself, assuming different messages and different forms. The body is a synonym of subject, an infinite metaphorical history of our looks, desires, that leads one to interrogate his/her image and social and sexual relations. These are understood as a manifestation of individual desires freed from a moral and social imposition. It attempts a return to profound human nature before we are turned into a cloning industry. In thisstudy it isimportant for usto understand in which form doessculpture reflect body image as a sociocultural and psychological phenomenon within the coordinates of our time. To understand how they represent and what artists represent in sculpture as a multiple and complex structure of human sexuality. Today, the sculptural body, expanding its representation, no longer as a reproduction of the corporal characteristics, presents the body in what it possesses of most intimate, unique, human and real, that moves, reacts, feels, suffers and pulsates, a mirror of us all.

Foreign direct investment motives and location decision factors under economic recession: Three cases of Finnish FDI in Portugal

The purpose of this thesis was to study how uncertainty in economic conditions of the FDI host country affects location decision of an investment, and what kinds of motives are behind the investment decision to a country in economic recession, in this case Portugal. The country has attracted foreign direct investment steadily, but it is evident that most multinational firms and investors tend to be more interested in emerging economies in general. The aim was to find out also which host country specific advantages are important in this kind of cross-border investment and which factors are important for an FDI to succeed under economic uncertainty at the host country. The study was done by analyzing three Finnish case companies: a private equity and real estate investment firm Pontos Group, A wave energy technology research and development company AW Energy and NSN, Nokia Solutions and Networks, a global telecommunications company. The research was done empirically, by interviewing experts on the subject, mainly persons representing these companies. In addition relevant articles, journals and content from case companies’ web-pages is used for the desk research regarding the topic. The results of this thesis showed that the FDIs with strategic asset-seeking investments seem most profitable FDI types under uncertain economic conditions. This kind of investments aim to strengthen the company’s long-term strategy, including the time after recession. Firm-specific ownership advantages that bring competitive advantage proved out to be important under these circumstances, as well as first-mover advantages and externally created assets such as government promotional policies regarding FDI incentives. Also the location was considered suitable for resource- or efficiency seeking motives, based on the lowered price level at the host country. Problems were related mainly to financing, but as foreign companies receive financing usually from their home countries, the economic recession of the host country does not have significant effect for FDI decision, according to this study

A framework for abstraction and virtualization of sensors in mobile context-aware computing

110 p.

Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

Performance Analysis of IP based WSNs in real time systems

Wireless sensor networks (WSNs) are the key enablers of the internet of things (IoT) paradigm. Traditionally, sensor network research has been to be unlike the internet, motivated by power and device constraints. The IETF 6LoWPAN draft standard changes this, defining how IPv6 packets can be efficiently transmitted over IEEE 802.15.4 radio links. Due to this 6LoWPAN technology, low power, low cost micro- controllers can be connected to the internet forming what is known as the wireless embedded internet. Another IETF recommendation, CoAP allows these devices to communicate interactively over the internet. The integration of such tiny, ubiquitous electronic devices to the internet enables interesting real-time applications. This thesis work attempts to evaluate the performance of a stack consisting of CoAP and 6LoWPAN over the IEEE 802.15.4 radio link using the Contiki OS and Cooja simulator, along with the CoAP framework Californium (Cf). Ultimately, the implementation of this stack on real hardware is carried out using a raspberry pi as a border router with T-mote sky sensors as slip radios and CoAP servers relaying temperature and humidity data. The reliability of the stack was also demonstrated during scalability analysis conducted on the physical deployment. The interoperability is ensured by connecting the WSN to the global internet using different hardware platforms supported by Contiki and without the use of specialized gateways commonly found in non IP based networks. This work therefore developed and demonstrated a heterogeneous wireless sensor network stack, which is IP based and conducted performance analysis of the stack, both in terms of simulations and real hardware.

Real options as an alternative methodology to assess investment projects

This paper aims to broaden the applicability of the assessment methodology of investment projects through real options as a key element for investment decision making -- Traditional project valuation methodologies are described and their gaps, which special characteristic is uncertainty, are presented -- A parallel between financial and real options that could be used for valuation is made, using the binomial tree method -- Finally, a case study in the construction sector shows a project valuation using expand and waiting options

THE TERMINATION PHASE: THERAPISTS’ PERSPECTIVE ON THE THERAPEUTIC RELATIONSHIP AND OUTCOME

The termination phase of treatment is recognized as a significant aspect of the therapy process and yet remains vastly understudied in psychotherapy literature. In the present study, therapists’ perspectives were used to examine how three elements of the therapy relationship (working alliance, real relationship and transference) during the termination phase relate to perceived client sensitivity to loss, termination phase evaluation and overall treatment outcome. Self-report data was gathered from 233 therapists, recruited from two Divisions of the American Psychological Association. Therapists completed measures for their work with a client with whom they could identify a termination phase of treatment. Results revealed that the working alliance and real relationship during the termination phase related positively to termination phase evaluation and overall treatment outcome, whereas negative transference during the termination phase related negatively to overall treatment outcome. Therapists’ perceptions of client sensitivity to loss related positively to both negative and positive transference during the termination phase. Post-hoc analyses revealed only the working alliance during the termination phase uniquely predicted overall treatment outcome in a model with the three therapy relationship elements examined together. On the other hand, all three therapy relationship variables during the termination phase uniquely predicted termination phase evaluation, when examined together. Limitations and implications of these findings are discussed, and recommendations for future study are suggested.

MANIPULATION OF IONS, ELECTRONS, AND PHOTONS IN 2D MATERIALS BY ION INTERCALATION

2D materials have attracted tremendous attention due to their unique physical and chemical properties since the discovery of graphene. Despite these intrinsic properties, various modification methods have been applied to 2D materials that yield even more exciting results. Among all modification methods, the intercalation of 2D materials provides the highest possible doping and/or phase change to the pristine 2D materials. This doping effect highly modifies 2D materials, with extraordinary electrical transport as well as optical, thermal, magnetic, and catalytic properties, which are advantageous for optoelectronics, superconductors, thermoelectronics, catalysis and energy storage applications. To study the property changes of 2D materials, we designed and built a planar nanobattery that allows electrochemical ion intercalation in 2D materials. More importantly, this planar nanobattery enables characterization of electrical, optical and structural properties of 2D materials in situ and real time upon ion intercalation. With this device, we successfully intercalated Li-ions into few layer graphene (FLG) and ultrathin graphite, heavily dopes the graphene to 0.6 x 10^15 /cm2, which simultaneously increased its conductivity and transmittance in the visible range. The intercalated LiC6 single crystallite achieved extraordinary optoelectronic properties, in which an eight-layered Li intercalated FLG achieved transmittance of 91.7% (at 550 nm) and sheet resistance of 3 ohm/sq. We extend the research to obtain scalable, printable graphene based transparent conductors with ion intercalation. Surfactant free, printed reduced graphene oxide transparent conductor thin film with Na-ion intercalation is obtained with transmittance of 79% and sheet resistance of 300 ohm/sq (at 550 nm). The figure of merit is calculated as the best pure rGO based transparent conductors. We further improved the tunability of the reduced graphene oxide film by using two layers of CNT films to sandwich it. The tunable range of rGO film is demonstrated from 0.9 um to 10 um in wavelength. Other ions such as K-ion is also studied of its intercalation chemistry and optical properties in graphitic materials. We also used the in situ characterization tools to understand the fundamental properties and improve the performance of battery electrode materials. We investigated the Na-ion interaction with rGO by in situ Transmission electron microscopy (TEM). For the first time, we observed reversible Na metal cluster (with diameter larger than 10 nm) deposition on rGO surface, which we evidenced with atom-resolved HRTEM image of Na metal and electron diffraction pattern. This discovery leads to a porous reduced graphene oxide sodium ion battery anode with record high reversible specific capacity around 450 mAh/g at 25mA/g, a high rate performance of 200 mAh/g at 250 mA/g, and stable cycling performance up to 750 cycles. In addition, direct observation of irreversible formation of Na2O on rGO unveils the origin of commonly observed low 1st Columbic Efficiency of rGO containing electrodes. Another example for in situ characterization for battery electrode is using the planar nanobattery for 2D MoS2 crystallite. Planar nanobattery allows the intrinsic electrical conductivity measurement with single crystalline 2D battery electrode upon ion intercalation and deintercalation process, which is lacking in conventional battery characterization techniques. We discovered that with a “rapid-charging” process at the first cycle, the lithiated MoS2 undergoes a drastic resistance decrease, which in a regular lithiation process, the resistance always increases after lithiation at its final stage. This discovery leads to a 2- fold increase in specific capacity with with rapid first lithiated MoS2 composite electrode material, compare with the regular first lithiated MoS2 composite electrode material, at current density of 250 mA/g.

Learning English is Fun! Incidental vocabulary acquisition of music and traditional class ninth graders via listening to pop songs

Finnish youth are constantly exposed to music and lyrics in English in their free time. It is likely that this has a positive effect on vocabulary learning. Learning vocabulary while simultaneously accompanied with melodies is likely to result in better learning outcomes. The present thesis covers a study on the vocabulary learning of traditional and music class ninth graders in a south-western upper comprehensive school in Finland, mainly concentrating on vocabulary learning as a by-product of listening to pop music and learning vocabulary through semantic priming. The theoretical background presents viable linguistic arguments and theories, which provide clarity for why it would be possible to learn English vocabulary via listening to pop songs. There is conflicting evidence on the benefits of music on vocabulary learning, and this thesis sets out to shed light on the situation. Additionally, incorporating pop music in English classes could assist in decreasing the gap between real world English and school English. The thesis is a mixed method research study consisting of both quantitative and qualitative research materials. The methodology comprises vocabulary tests both before and after pop music samples and a background questionnaire filled by students. According to the results, all students reported liking listening to music and they clearly listened to English pop music the most. A statistically significant difference was found when analysing the results of the differences in pre- and post-vocabulary tests. However, the traditional class appeared to listen to mainstream pop music more than the students in the music class, and thus it seems likely that the traditional class benefited more from vocabulary learning occurring via listening to pop songs. In conclusion, it can be established that it is possible to learn English vocabulary via listening to pop songs and that students wish their English lectures would involve more music-related vocabulary exercises in the future. Thus, when it comes to school learning, pop songs should be utilised in vocabulary learning, which could also in turn result in more diverse learning and the students could, more easily than before, relate to the themes and topics of the lectures. Furthermore, with the help of pop songs it would be possible to decrease the gap between school English and real-world English.