Flanking sound transmission between room module elements made of massive timber

Massiivipuurakenteisten tilaelementtien välinen ilmaääneneristävyys ei aina täytä rakentamismääräysten vaatimuksia asuinhuoneiden välillä. Välipohjarakenne tilaelementtien välillä on yleensä luonnostaan kaksinkertainen ja sen laskennallinen ilmaääneneristävyys voi olla suuri. Äänen rakenteellisen sivutiesiirtymän vaikutus on kuitenkin niin suuri, että sivuaville rakenteille tarvitaan ääneneristävyyttä parantavia ratkaisuja. Massiivipuurakenteet kuten CLT voidaan rinnastaa muihin massiivirakenteisiin ja esimerkiksi joustavan kerroksen vaikutus rakenteiden liitoksessa on hyvin samanlainen massiivipuurakenteilla ja betonirakenteilla. Massiivipuulla on kuitenkin suuremmat sisäiset häviöt ja pienempi pintamassa kuin betonilla. Massiivipuurakenteilla on tehty liitoseristävyyden ja värähtelytasoerotuksen mittauksia, mutta tilaelementtirakenteilla hyvin vähän. Tässä diplomityössä tarkastellaan rakenteellista äänen sivutiesiirtymää puurakenteisten tilaelementtien välillä tutkimustiedon avulla, laskennallisesti ja mittauksin. Diplomityön keskeisin osa on standardin ISO 10848 mukaisen liitoseristävyyden mittausmenetelmän testaus ja kehitys. Mitattua ilmaääneneristävyyttä R’ verrataan standardin EN 12354-1 mukaan laskettuun ilmaääneneristävyyteen. Mitattua liitoseristävyyttä Kij verrataan tutkimuksista saatuihin liitoseristävyyksiin sekä mitattuun ilmaääneneristävyyteen. Yksi tämän tutkimuksen keskeisistä havainnoista on liitoseristävyyden ja ilmaääneneristävyyden välinen yhteys. Kun mitattu ilmaääneneristävyys oli suurempi, mitattiin myös suurempi liitoseristävyys. Tämä voi kertoa rakenteellisesta äänen sivutiesiirtymästä. Tutkimuksessa saadut mittaustulokset mukailevat Ågrenin & Ljunggrenin (2016) tilaelementeillä tehdyn mittauksen tuloksia, mutta suurilla taajuuksilla liitoseristävyys ei lähde samalla tavalla jyrkkään kasvuun. Tutkimuksen lopussa arvioidaan, että menetelmä on sellaisenaan liian työläs sivutiesiirtymän arviointiin kenttämittauksilla.Airborne sound insulation between room module elements made of massive timber do not always fulfill the requirements given in the National Building Code of Finland. The intermediate floor structure between the modules has practically at least two layers separated by an air gap, thus the calculated sound reduction index for the structure can be high. However, the effect of structure borne flanking transmission is significant enough for the flanking structures to require additional layers to improve the airborne sound insulation. Massive timber structures like CLT are comparable to other massive structures and for example the effect of an elastic layer in a joint is very similar for massive timber and concrete structures. The internal losses are higher and the surface mass is smaller in massive timber than in concrete, though. Measurements of the vibration reduction index Kij and vibration level difference have been done with massive timber structures, but very few with room module element structures. In this thesis, the structural flanking transmission between room module elements made of massive timber is studied through international research papers, calculations and in-situ measurements. The central part of this thesis is the development and testing of a measurement method for flanking transmission according to the standard ISO 10848. Measured values of airborne sound reduction index R’ are compared to values calculated according to the standard EN 12354. Measured values of vibration reduction indexes Kij are compared to values obtained in research papers and to measured values of air-borne sound reduction indexes. One of the key observations made is a consistency between the vibration reduction index and the airborne sound reduction index. When the airborne sound insulation was higher a higher value for the flanking transmission index was also measured. It can be a sign of structural flanking transmission. The results of the measurements resemble the results from Ågren & Ljunggren (2016), except on high frequencies where a similar steep slope was not measured. Feasibility of the measurement method for evaluating flanking transmission in-situ is discussed and concluded that the method is too labor-intensive for in-situ measurements as it is in the standard

Multimodal Video Analysis and Modeling

From recalling long forgotten experiences based on a familiar scent or on a piece of music, to lip reading aided conversation in noisy environments or travel sickness caused by mismatch of the signals from vision and the vestibular system, the human perception manifests countless examples of subtle and effortless joint adoption of the multiple senses provided to us by evolution. Emulating such multisensory (or multimodal, i.e., comprising multiple types of input modes or modalities) processing computationally offers tools for more effective, efficient, or robust accomplishment of many multimedia tasks using evidence from the multiple input modalities. Information from the modalities can also be analyzed for patterns and connections across them, opening up interesting applications not feasible with a single modality, such as prediction of some aspects of one modality based on another. In this dissertation, multimodal analysis techniques are applied to selected video tasks with accompanying modalities. More specifically, all the tasks involve some type of analysis of videos recorded by non-professional videographers using mobile devices.Fusion of information from multiple modalities is applied to recording environment classification from video and audio as well as to sport type classification from a set of multi-device videos, corresponding audio, and recording device motion sensor data. The environment classification combines support vector machine (SVM) classifiers trained on various global visual low-level features with audio event histogram based environment classification using k nearest neighbors (k-NN). Rule-based fusion schemes with genetic algorithm (GA)-optimized modality weights are compared to training a SVM classifier to perform the multimodal fusion. A comprehensive selection of fusion strategies is compared for the task of classifying the sport type of a set of recordings from a common event. These include fusion prior to, simultaneously with, and after classification; various approaches for using modality quality estimates; and fusing soft confidence scores as well as crisp single-class predictions. Additionally, different strategies are examined for aggregating the decisions of single videos to a collective prediction from the set of videos recorded concurrently with multiple devices. In both tasks multimodal analysis shows clear advantage over separate classification of the modalities.Another part of the work investigates cross-modal pattern analysis and audio-based video editing. This study examines the feasibility of automatically timing shot cuts of multi-camera concert recordings according to music-related cutting patterns learnt from professional concert videos. Cut timing is a crucial part of automated creation of multicamera mashups, where shots from multiple recording devices from a common event are alternated with the aim at mimicing a professionally produced video. In the framework, separate statistical models are formed for typical patterns of beat-quantized cuts in short segments, differences in beats between consecutive cuts, and relative deviation of cuts from exact beat times. Based on music meter and audio change point analysis of a new recording, the models can be used for synthesizing cut times. In a user study the proposed framework clearly outperforms a baseline automatic method with comparably advanced audio analysis and wins 48.2 % of comparisons against hand-edited videos

Flanking sound transmission between room module elements made of massive timber

Massiivipuurakenteisten tilaelementtien välinen ilmaääneneristävyys ei aina täytä rakentamismääräysten vaatimuksia asuinhuoneiden välillä. Välipohjarakenne tilaelementtien välillä on yleensä luonnostaan kaksinkertainen ja sen laskennallinen ilmaääneneristävyys voi olla suuri. Äänen rakenteellisen sivutiesiirtymän vaikutus on kuitenkin niin suuri, että sivuaville rakenteille tarvitaan ääneneristävyyttä parantavia ratkaisuja. Massiivipuurakenteet kuten CLT voidaan rinnastaa muihin massiivirakenteisiin ja esimerkiksi joustavan kerroksen vaikutus rakenteiden liitoksessa on hyvin samanlainen massiivipuurakenteilla ja betonirakenteilla. Massiivipuulla on kuitenkin suuremmat sisäiset häviöt ja pienempi pintamassa kuin betonilla. Massiivipuurakenteilla on tehty liitoseristävyyden ja värähtelytasoerotuksen mittauksia, mutta tilaelementtirakenteilla hyvin vähän. Tässä diplomityössä tarkastellaan rakenteellista äänen sivutiesiirtymää puurakenteisten tilaelementtien välillä tutkimustiedon avulla, laskennallisesti ja mittauksin. Diplomityön keskeisin osa on standardin ISO 10848 mukaisen liitoseristävyyden mittausmenetelmän testaus ja kehitys. Mitattua ilmaääneneristävyyttä R’ verrataan standardin EN 12354-1 mukaan laskettuun ilmaääneneristävyyteen. Mitattua liitoseristävyyttä Kij verrataan tutkimuksista saatuihin liitoseristävyyksiin sekä mitattuun ilmaääneneristävyyteen. Yksi tämän tutkimuksen keskeisistä havainnoista on liitoseristävyyden ja ilmaääneneristävyyden välinen yhteys. Kun mitattu ilmaääneneristävyys oli suurempi, mitattiin myös suurempi liitoseristävyys. Tämä voi kertoa rakenteellisesta äänen sivutiesiirtymästä. Tutkimuksessa saadut mittaustulokset mukailevat Ågrenin & Ljunggrenin (2016) tilaelementeillä tehdyn mittauksen tuloksia, mutta suurilla taajuuksilla liitoseristävyys ei lähde samalla tavalla jyrkkään kasvuun. Tutkimuksen lopussa arvioidaan, että menetelmä on sellaisenaan liian työläs sivutiesiirtymän arviointiin kenttämittauksilla.Airborne sound insulation between room module elements made of massive timber do not always fulfill the requirements given in the National Building Code of Finland. The intermediate floor structure between the modules has practically at least two layers separated by an air gap, thus the calculated sound reduction index for the structure can be high. However, the effect of structure borne flanking transmission is significant enough for the flanking structures to require additional layers to improve the airborne sound insulation. Massive timber structures like CLT are comparable to other massive structures and for example the effect of an elastic layer in a joint is very similar for massive timber and concrete structures. The internal losses are higher and the surface mass is smaller in massive timber than in concrete, though. Measurements of the vibration reduction index Kij and vibration level difference have been done with massive timber structures, but very few with room module element structures. In this thesis, the structural flanking transmission between room module elements made of massive timber is studied through international research papers, calculations and in-situ measurements. The central part of this thesis is the development and testing of a measurement method for flanking transmission according to the standard ISO 10848. Measured values of airborne sound reduction index R’ are compared to values calculated according to the standard EN 12354. Measured values of vibration reduction indexes Kij are compared to values obtained in research papers and to measured values of air-borne sound reduction indexes. One of the key observations made is a consistency between the vibration reduction index and the airborne sound reduction index. When the airborne sound insulation was higher a higher value for the flanking transmission index was also measured. It can be a sign of structural flanking transmission. The results of the measurements resemble the results from Ågren & Ljunggren (2016), except on high frequencies where a similar steep slope was not measured. Feasibility of the measurement method for evaluating flanking transmission in-situ is discussed and concluded that the method is too labor-intensive for in-situ measurements as it is in the standard

Multimodal Video Analysis and Modeling

From recalling long forgotten experiences based on a familiar scent or on a piece of music, to lip reading aided conversation in noisy environments or travel sickness caused by mismatch of the signals from vision and the vestibular system, the human perception manifests countless examples of subtle and effortless joint adoption of the multiple senses provided to us by evolution. Emulating such multisensory (or multimodal, i.e., comprising multiple types of input modes or modalities) processing computationally offers tools for more effective, efficient, or robust accomplishment of many multimedia tasks using evidence from the multiple input modalities. Information from the modalities can also be analyzed for patterns and connections across them, opening up interesting applications not feasible with a single modality, such as prediction of some aspects of one modality based on another. In this dissertation, multimodal analysis techniques are applied to selected video tasks with accompanying modalities. More specifically, all the tasks involve some type of analysis of videos recorded by non-professional videographers using mobile devices.Fusion of information from multiple modalities is applied to recording environment classification from video and audio as well as to sport type classification from a set of multi-device videos, corresponding audio, and recording device motion sensor data. The environment classification combines support vector machine (SVM) classifiers trained on various global visual low-level features with audio event histogram based environment classification using k nearest neighbors (k-NN). Rule-based fusion schemes with genetic algorithm (GA)-optimized modality weights are compared to training a SVM classifier to perform the multimodal fusion. A comprehensive selection of fusion strategies is compared for the task of classifying the sport type of a set of recordings from a common event. These include fusion prior to, simultaneously with, and after classification; various approaches for using modality quality estimates; and fusing soft confidence scores as well as crisp single-class predictions. Additionally, different strategies are examined for aggregating the decisions of single videos to a collective prediction from the set of videos recorded concurrently with multiple devices. In both tasks multimodal analysis shows clear advantage over separate classification of the modalities.Another part of the work investigates cross-modal pattern analysis and audio-based video editing. This study examines the feasibility of automatically timing shot cuts of multi-camera concert recordings according to music-related cutting patterns learnt from professional concert videos. Cut timing is a crucial part of automated creation of multicamera mashups, where shots from multiple recording devices from a common event are alternated with the aim at mimicing a professionally produced video. In the framework, separate statistical models are formed for typical patterns of beat-quantized cuts in short segments, differences in beats between consecutive cuts, and relative deviation of cuts from exact beat times. Based on music meter and audio change point analysis of a new recording, the models can be used for synthesizing cut times. In a user study the proposed framework clearly outperforms a baseline automatic method with comparably advanced audio analysis and wins 48.2 % of comparisons against hand-edited videos

Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultra-high-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.Academy of Finland (285474

Multimodal Semantics Extraction from User-Generated Videos

User-generated video content has grown tremendously fast to the point of outpacing professional content creation. In this work we develop methods that analyze contextual information of multiple user-generated videos in order to obtain semantic information about public happenings (e.g., sport and live music events) being recorded in these videos. One of the key contributions of this work is a joint utilization of different data modalities, including such captured by auxiliary sensors during the video recording performed by each user. In particular, we analyze GPS data, magnetometer data, accelerometer data, video- and audio-content data. We use these data modalities to infer information about the event being recorded, in terms of layout (e.g., stadium), genre, indoor versus outdoor scene, and the main area of interest of the event. Furthermore we propose a method that automatically identifies the optimal set of cameras to be used in a multicamera video production. Finally, we detect the camera users which fall within the field of view of other cameras recording at the same public happening. We show that the proposed multimodal analysis methods perform well on various recordings obtained in real sport events and live music performances

Hierarchical deconvolution for incoherent scatter radar data

Abstract We propose a novel method for deconvolving incoherent scatter radar data to recover accurate reconstructions of backscattered powers. The problem is modelled as a hierarchical noise-perturbed deconvolution problem, where the lower hierarchy consists of an adaptive length-scale function that allows for a non-stationary prior and as such enables adaptive recovery of smooth and narrow layers in the profiles. The estimation is done in a Bayesian statistical inversion framework as a two-step procedure, where hyperparameters are first estimated by optimisation and followed by an analytical closed-form solution of the deconvolved signal. The proposed optimisation-based method is compared to a fully probabilistic approach using Markov chain Monte Carlo techniques enabling additional uncertainty quantification. In this paper we examine the potential of the hierarchical deconvolution approach using two different prior models for the length-scale function. We apply the developed methodology to compute the backscattered powers of measured polar mesospheric winter echoes, as well as summer echoes, from the EISCAT VHF radar in Tromsø, Norway. Computational accuracy and performance are tested using a simulated signal corresponding to a typical background ionosphere and a sporadic E layer with known ground truth. The results suggest that the proposed hierarchical deconvolution approach can recover accurate and clean reconstructions of profiles, and the potential to be successfully applied to similar problems