Image-Based Fire Detection in Industrial Environments with YOLOv4

Fires have destructive power when they break out and affect their surroundings on a devastatingly large scale. The best way to minimize their damage is to detect the fire as quickly as possible before it has a chance to grow. Accordingly, this work looks into the potential of AI to detect and recognize fires and reduce detection time using object detection on an image stream. Object detection has made giant leaps in speed and accuracy over the last six years, making real-time detection feasible. To our end, we collected and labeled appropriate data from several public sources, which have been used to train and evaluate several models based on the popular YOLOv4 object detector. Our focus, driven by a collaborating industrial partner, is to implement our system in an industrial warehouse setting, which is characterized by high ceilings. A drawback of traditional smoke detectors in this setup is that the smoke has to rise to a sufficient height. The AI models brought forward in this research managed to outperform these detectors by a significant amount of time, providing precious anticipation that could help to minimize the effects of fires further.Comment: Accepted for publication at ICPRA

Synthetic Data for Object Classification in Industrial Applications

One of the biggest challenges in machine learning is data collection. Training data is an important part since it determines how the model will behave. In object classification, capturing a large number of images per object and in different conditions is not always possible and can be very time-consuming and tedious. Accordingly, this work explores the creation of artificial images using a game engine to cope with limited data in the training dataset. We combine real and synthetic data to train the object classification engine, a strategy that has shown to be beneficial to increase confidence in the decisions made by the classifier, which is often critical in industrial setups. To combine real and synthetic data, we first train the classifier on a massive amount of synthetic data, and then we fine-tune it on real images. Another important result is that the amount of real images needed for fine-tuning is not very high, reaching top accuracy with just 12 or 24 images per class. This substantially reduces the requirements of capturing a great amount of real data.Comment: Accepted for publication at ICPRA

Kulturella skillnader vid gränsöverskridande företagsförvärv

Syftet med denna studie är att bidra med en ökad förståelse om hur kulturella skillnader i ett företagsförvärv påverkar den europeiska förvärvarens avkastning på sikt

Visual Detection of Personal Protective Equipment and Safety Gear on Industry Workers

Workplace injuries are common in today's society due to a lack of adequately worn safety equipment. A system that only admits appropriately equipped personnel can be created to improve working conditions. The goal is thus to develop a system that will improve workers' safety using a camera that will detect the usage of Personal Protective Equipment (PPE). To this end, we collected and labeled appropriate data from several public sources, which have been used to train and evaluate several models based on the popular YOLOv4 object detector. Our focus, driven by a collaborating industrial partner, is to implement our system into an entry control point where workers must present themselves to obtain access to a restricted area. Combined with facial identity recognition, the system would ensure that only authorized people wearing appropriate equipment are granted access. A novelty of this work is that we increase the number of classes to five objects (hardhat, safety vest, safety gloves, safety glasses, and hearing protection), whereas most existing works only focus on one or two classes, usually hardhats or vests. The AI model developed provides good detection accuracy at a distance of 3 and 5 meters in the collaborative environment where we aim at operating (mAP of 99/89%, respectively). The small size of some objects or the potential occlusion by body parts have been identified as potential factors that are detrimental to accuracy, which we have counteracted via data augmentation and cropping of the body before applying PPE detection.Comment: Accepted for publication at ICPRA

Entreprenörens motivation

Gasellföretagen skapar många nya arbetstillfällen i Sverige. Under åren 2004 till 2007 stod gasellföretagen för drygt 10 procent av ökningen av Sveriges BNP. För att framgångsrika företag ska skapas och växa krävs individer som tar initiativet att starta och driva dessa. Tidigare forskning har fokuserat på vad som driver entreprenörer i uppstartsskedet, men lika viktigt är det att förstå vad det är som driver entreprenören i senare skeden. Vi har därför valt att se hur motivationen förändras över tiden hos den grundande entreprenören i gasellföretag. Den kvalitativa studien bygger på nio intervjuer med företagsgrundare av gaseller som delat med sig av sina berättelser och erfarenheter. Vi presenterar i vår studie vad som utmärker samt motiverar dem i deras arbete

A pooled analysis of karyotypic patterns, breakpoints and imbalances in 783 cytogenetically abnormal multiple myelomas reveals frequently involved chromosome segments as well as significant age- and sex-related differences.

The cytogenetic features (ploidy, complexity, breakpoints, imbalances) were ascertained in 783 abnormal multiple myeloma (MM) cases to identify frequently involved chromosomal regions as well as a possible impact of age/sex. The series included MM patients from the Mitelman Database of Chromosome Aberrations in Cancer and from our own laboratory. Hyperdiploidy was most common, followed by hypodiploidy, pseudodiploidy and tri-/tetraploidy. Most cases were complex, with a median of eight changes per patient. The distribution of modal numbers differed between younger and older patients, but was not related to sex. No sex- or age-related differences regarding the number of anomalies were found. The most frequent genomic breakpoints were 14q32, 11q13, 1q10, 8q24, 1p11, 1q21, 22q11, 1p13, 1q11, 19q13, 1p22, 6q21 and 17p11. Breaks in 1p13, 6q21 and 11q13 were more common in the younger age group. The most frequent imbalances were + 9, - 13, + 15, + 19, + 11 and - Y. Trisomy 11 and monosomy 16 were more common among men, while -X was more frequent among women. Loss of Y as the sole change and + 5 were more common in elderly patients, and - 14 was more frequent in the younger age group. The present findings strongly suggest that some karyotypic features of MM are influenced by endogenous and/or exogenous factors

Mimicking respiratory phosphorylation using purified enzymes

The enzymes of oxidative phosphorylation are a striking example of the functional association of multiple enzyme complexes, working together to form ATP from cellular reducing equivalents. These complexes, such as cytochrome c oxidase or the ATP synthase, are typically investigated individually and therefore, their functional interplay is not well understood. Here, we present methodology that allows the co-reconstitution of purified terminal oxidases and ATP synthases in synthetic liposomes. The enzymes are functionally coupled via proton translocation where upon addition of reducing equivalents the oxidase creates and maintains a transmembrane electrochemical proton gradient that energizes the synthesis of ATP by the F1F0 ATP synthase. The method has been tested with the ATP synthases from Escherichia coli and spinach chloroplasts, and with the quinol and cytochrome c oxidases from E. coli and Rhodobacter sphaeroides, respectively. Unlike in experiments with the ATP synthase reconstituted alone, the setup allows in vitro ATP synthesis under steady state conditions, with rates up to 90 ATP×s(-1)×enzyme(-1). We have also used the novel system to study the phenomenon of "mild uncoupling" as observed in mitochondria upon addition of low concentrations of ionophores (e.g. FCCP, SF6847) and the recoupling effect of 6-ketocholestanol. While we could reproduce the described effects, our data with the in vitro system does not support the idea of a direct interaction between a mitochondrial protein and the uncoupling agents as proposed earlier

Affinity proteomics reveals elevated muscle proteins in plasma of children with cerebral malaria

Systemic inflammation and sequestration of parasitized erythrocytes are central processes in the pathophysiology of severe Plasmodium falciparum childhood malaria. However, it is still not understood why some children are more at risks to develop malaria complications than others. To identify human proteins in plasma related to childhood malaria syndromes, multiplex antibody suspension bead arrays were employed. Out of the 1,015 proteins analyzed in plasma from more than 700 children, 41 differed between malaria infected children and community controls, whereas 13 discriminated uncomplicated malaria from severe malaria syndromes. Markers of oxidative stress were found related to severe malaria anemia while markers of endothelial activation, platelet adhesion and muscular damage were identified in relation to children with cerebral malaria. These findings suggest the presence of generalized vascular inflammation, vascular wall modulations, activation of endothelium and unbalanced glucose metabolism in severe malaria. The increased levels of specific muscle proteins in plasma implicate potential muscle damage and microvasculature lesions during the course of cerebral malaria