The aim of this study is to improve the monitoring and controlling of heating systems located at customer buildings through the use of a decision support system. To achieve this, the proposed system applies a two-step classifier to detect manual changes of the temperature of the heating system. We apply data from the Swedish company NODA, active in energy optimization and services for energy efficiency, to train and test the suggested system. The decision support system is evaluated through an experiment and the results are validated by experts at NODA. The results show that the decision support system can detect changes within three days after their occurrence and only by considering daily average measurements.

In order to reach an acceptable level of confidence in the quality of a software product, testing of the software is paramount. To obtain "good" quality software it is essential to rely on "good" test cases. To define the criteria for what make up for a "good" test case is not a trivial task. Over the past 15 years, a short list of publications have presented criteria for "good" test cases but without ranking them based on their importance. This paper presents a non-exhaustive and non-authoritative tentative list of 15 criteria and a ranking of their relative importance. A number of the criteria come from previous publications but also from discussions with our industrial partners. The ranking is based on results collected via a questionnaire that was sent out to a limited number of randomly chosen respondents in the Swedish software industry. This means that the results are more indicative than conclusive.

The importance of managing organizational knowledge of enterprises has been recognized for decades. The systematic development and reuse of organizational knowledge is expected to improve the competitiveness of the enterprise. While the practice of “reuse” is common in general computer science there is still a lack of surveys in regard to reuse in enterprise modeling. This document reviews four different papers presented at information systems conferences over the last seven years: CAISE, EMMSAD, ICIS, and INCOM. Our analysis indicates that the majority of research is realized by case studies, theoretical frameworks and mostly on business process modeling aspects of enterprise models.

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency.

This paper examines whether social cues, such as facial expressions, can be used to adapt and tailor a robot-assisted training in order to maximize performance and comfort. Specifically, this paper serves as a basis in determining whether key facial signals, including emotions and facial actions, are common among participants during a physical and cognitive training scenario. In the experiment, participants performed basic arm exercises with a social robot as a guide. We extracted facial features from video recordings of participants and applied a recursive feature elimination algorithm to select a subset of discriminating facial features. These features are correlated with the performance of the user and the level of difficulty of the exercises. The long-term aim of this work, building upon the work presented here, is to develop an algorithm that can eventually be used in robot-assisted training to allow a robot to tailor a training program based on the physical capabilities as well as the social cues of the users.

Wireless technology has increased in popularity since its invention, being embedded in many devices, such as smartphones, laptops, earphones etcetera. One of those technologies is Bluetooth, which is a short-range technology that is widely used worldwide. While being a popular and important technology, it is not as optimized as it could be, especially the standard Bluetooth 4.2. According to (Bluetooth, 2023)Bluetooth version 5 has four times the range of Bluetooth version 4.2 which is one area of improvement in Bluetooth. While limited Forward Error Correction (FEC)functionality in terms of (15,10) Hamming codes is present in the Bluetooth classic4.2 stack, however, it is not utilized in that version of Bluetooth. This thesis aims to implement a functionality in Bluetooth that uses FEC to increase the range. Before the experiments were conducted, multiple measurements were done in order to check if the hardware, such as the Bluetooth modules, antennas, air sniffer, could provide reliable and valid data. The experiments were conducted by streaming an audio sample of 48 kHz via Bluetooth and increasing the range until a certain percentage of fail rate in data transmission has occurred. FEC was then enabled, and the same experiment was repeated. The results from the experiments show that the range can be increased up to a few meters. Not only that, but the transmission without FEC allows a high level of errors without a connection cut-off. With FEC, the connection does not allow high levels of errors which means that the audio quality would not drop as low as it would have without FEC which means that a certain audio quality is preserved. This also makes the case for the implementation of higher modes of FEC into the Bluetooth stack to potentially increase the range of Bluetooth classic multiple times, but that implementation is beyond the scope of this thesis. 

The lubrication and tension levels are two important parameters when running a chainsaw, both impacting the cutting performance and lifespan of the tool. An appropriate level of lubrication and tension leads to maximum performance of the chainsaw and direct benefits for the end-user. This thesis addresses the problem of detecting the lubrication status and the tension level using the information contained in the acoustic emissions captured in the guidebar of the chainsaw. Data was collected by running controlled experiments using an acoustic emissions sensor.Information was extracted from acoustic emissions by using a number of features computed on different frequency ranges.Three machine learning models were trained and evaluated on data corresponding to different combinations of lubrication status and tension levels. The models' performances were evaluated using the well-known metrics accuracy, precision, and recall. A pattern was found for each lubrication and tension setup, and the model that registered the highest performance was the Random Forest. The impact of temperature, guidebar, and chain on acoustic emissions is also analyzed. The detection of different lubrication levels using the information contained by acoustic signals is also addressed, the patterns in data being determined by computing features in the time and frequency domains. The analysis shows that the temperature does not have an impact when the running time is less than 10 minutes, and the chain has a bigger impact than the guidebar for the specific setup of the experiments. Moreover, a pattern dependent on the guidebar and chain combination correlated with the lubrication level was identified. The main contribution of this thesis consists of detecting a pattern representative of lubrication and tension setup in acoustic emission using a number of features computed in different frequency ranges.

Abstract

Purpose: The purpose of these theses is to build a deep understanding of CAN-FD and how does it work in the network.

Method:The methods are literature studies that build on scientific books, data sheets, white papers, articles and interviews. 

Findings: This research shows that the scalability of CAN-FD is the same in Classic CAN. Supporting high bit rate and increasing the bandwidth for CAN-FD is the only gap between them. In addition, the result shows that the CAN-FD doesn’t work on Partial Networks.

Implications: The idea of this report was interesting for the companies that have needs for CAN-FD, which help to increase their knowledge about CAN-FD.

Limitations: A Qualitative method was a useful method to reach the needs of this study. This method leads to real results that have been done in the other studies. The only missing for the authors is the scientific research that could build on real experiments and measurements on the hardware or software was not available under this research and this could lead to more clear results.

Limitations: A Qualitative method was a useful method to reach the needs of this study. This method leads to real results that have been done in the other studies. The only missing for the authors is the scientific research that could build on real experiments and measurements on the hardware or software was not available under this research and this could lead to more clear results.

There is a lack of data-driven training instructions for sports shooters, as instruction has commonly been based on subjective assessments. Many studies have correlated body posture and balance to shooting performance in rifle shooting tasks, but most of them have focused on single aspects of postural control. This thesis has focused on finding relevant rifle shooting factors by examining the entire body over sequences of time. We performed a data collection with 13 human participants who carried out live rifle shooting scenarios while being recorded with multiple biometric sensors, including several body trackers. An experiment was conducted to identify what aspects of rifle shooting could be predicted and explained using these data. We employed a pre-processing pipeline to produce a novel skeleton sequence representation, and used it to train a transformer model. The predictions from this model could be explained on a per sample basis using the attention mechanism, and visualised in an interactive format for humans to interpret. It was possible to separate the different phases of a shooting scenario from body posture with a high classification accuracy (81%). However, no correlation could be shown between shooting performance and body posture from our data. Future work could focus on novel feature engineering, and on examining alternative machine learning approaches. The dataset and pre-processing pipeline, as well as the techniques for generating explainable predictions presented in this thesis has laid the groundwork for future research in the sports shooting domain.

Original equipment suppliers (OES) that develop unique products are continuously faced with changing requirements during both the quotation and product development processes. This challenge is a different reality from companies that develop off-the-shelf products for the end consumer, which use fixed specifications and where product platforms have been a strong enabler for efficient mass customization. However, product platforms cannot adequately support companies working as OES. The reason is that a high level of customization is required which means that interfaces cannot be standardized, the performance is not negotiable, requirements are not initially fixed, and the specific system interacts with, is affected by, or affects other systems that are simultaneously developed in a transdisciplinary environment. The design platform (DP) approach provides a coherent environment for heterogeneous and transdisciplinary design resources to be used in product development by supporting both designing and off-the-shelf solutions. This research describes the introduction, application and further development of the DP approach at an automotive supplier to support the development of customized solutions when traditional modularity or platform scalability do not suffice. A computer tool called Design Platform Manager has been developed to support the creation and visualization of the DP. The support tool has a connection to a product data management database to link the platform model to the various kinds of engineering assets needed or intended to support variant creation. Finally, the support tool was evaluated by the case company representatives showing promising results. 

An Experimental Diagnostic Tool (EDT) was developed to increase the efficiency of the diagnostic process of robotic lawn mowers which resulted in a 200% productivity increase when utilizing a proposed formula specifically designed for the diagnostic process of robotic lawn mowers. The tool does not only extract and process data from the robotic lawn mower wirelessly but also highlights potential faults through an intuitive and easy-to-use interface - empowering servicing technicians who perform the diagnostics to perform at a higher level.

Further, efficiency is a term widely used in various domains and contexts when measuring the capacity of a process. Proposed general definitions of the term have been given by previous authors and researchers. However, due to a lack of universally set definitions which fit all situations, the term remains ambiguous when improvements to a specific process are needed. The unclear definition is due to the variations within each process affecting the definition of both the term itself, but also similar terms fundamentally connected to it such as productivity, performance, and profitability. The following report contains an investigation of exploratory research where the understanding of efficiency and its related concepts are analyzed within the after-sales diagnostic process of robotic lawn mowers.

In forestry, natural forests are forest areas with high biodiversity, in need of preservation. The current mapping of natural forests is a tedious task that requires manual labor that could possibly be automated.

In this paper we explore the main features used by a random forest algorithm to classify natural forest and managed forest in northern Sweden. The goal was to create a model with a substantial strength of agreement, meaning a Kappa value of 0.61 or higher, placing the model in the same range as models produced in previous research.

We used raster data gathered from airborne LiDAR, combined with labeled sample areas, both supplied by the Swedish Forest Agency. Two experiments were performed with different features. Experiment 1 used features extracted using methods inspired from previous research while Experiment 2 further added upon those features. From the total number of used sample areas (n=2882), 70% was used to train the models and 30% was used for evaluation.

The result was a Kappa value of 0.26 for Experiment 1 and 0.32 for Experiment 2. Features shown to be prominent are features derived from canopy height, where the supplied data also had the highest resolution. Percentiles, kurtosis and canopy crown areas derived from the canopy height were shown to be the most important for classification. The results fell short of our goal, possibly indicating a range of flaws in the data used. The size of the sample areas and resolution of raster data are likely important factors when extracting features, playing a large role in the produced model’s performance.

Introduction: Number of strata (NoS) is an informative descriptor of forest structure and is therefore useful in forest management. Collection of NoS as well as other forest properties is performed by fieldworkers and could benefit from automation.

Objectives: This study investigates automated prediction of NoS from airborne laser scanned point clouds over Swedish forest plots.Methods: A previously suggested approach of using vertical gap probability is compared through experimentation against the geometric neural network PointNet++ configured for ordinal prediction. For both approaches, the mean accuracy is measured for three datasets: coniferous forest, deciduous forest, and a combination of all forests.

Results: PointNet++ displayed a better point performance for two out of three datasets, attaining a top mean accuracy of 46.2%. However only the coniferous subset displayed a statistically significant superiority for PointNet++.

Conclusion: This study demonstrates the potential of geometric neural networks for data mining of forest properties. The results show that impediments in the data may need to be addressed for further improvements.

Indoor occupancy prediction is a prerequisite for the management of energy consumption, security, health, and other systems in smart buildings. Previous studies have shown that buildings that automatize their heating, lighting, air conditioning, and ventilation systems through considering the occupancy and activity information might reduce energy consumption by more than 50%. However, it is difficult to use high-resolution sensors and cameras for occupancy prediction due to privacy concerns. In this paper, we propose a novel solution for predicting occupancy using multiple low-cost and low-resolution heat sensors. We suggest two different methods for fusing and processing the data captured from multiple heat sensors and we use a Convolutional Neural Network for predicting occupancy. We conduct experiments to assess both the performance of the proposed solutions and analyze the impact of sensor field view overlaps on the prediction results. In summary, our experimental results show that the implemented solutions show high occupancy prediction accuracy and real-time processing capabilities.

Exploratory Testing (ET) is a software testing practice characterized by simultaneous activities: test design, test execution and learning from the test results. Recently ET has received much attention from testing practitioners and researchers as well as software testing standardization bodies. Nevertheless, scientific evidence and knowledge about ET’s application in software industry are little. This multi case study conducted in three software companies, provides insights into the real perception of Exploratory Testing and the role of this practice in the whole testing process of them. This study identifies three distinct applications of Exploratory Testing in these software companies: ET as a standard process; ET as a discretionary, formalized process; ET as an informal, ad hoc process. Also, a number of key factors that affect the choice of Exploratory Testing in an organization have been identified: product characteristics and features; the products market; pressure for faster product release.

ITIL - Information Technology Infrastructure Library is a widely acclaimed practice framework. It is a framework for Information technology service management (ITSM), which provides IT, business alignment, improved IT services and helps to resolve business issues. ITIL does not function to generate business strategies but to support them. ITIL as a framework describes a lifecycle that includes five stages, which are not technological specific or organization specific. It can be adopted by any organization to meet its goals. Five stages of ITIL lifecycle are; Service Strategy, Service Design, Service Transition, Service Operation, and Continual service improvement.

The primary purpose of this thesis is to elaborate upon the ITIL problem management process with particular regard to challenges that hinder its application and to further supplement this analysis with insights of ITIL professionals about overcoming these challenges. As this research’s data collection is based on semi-structured interviews with IT professionals, gathering their views on ITIL implementation challenges, so expected data to be collected from these interviews is to be non-numerical, therefore; this thesis will follow qualitative research. This thesis will employ deductive approach. As the researcher of this thesis will gather in-depth knowledge of ITIL framework and challenges in implementing ITIL problem management by extensive literature review. As a result, a list of twenty-six challenges, categorized into six categories, was the first outcome of this study by extensive literature review. The literature review didn’t only help to generate a list of challenges but also helped this study to recognize the importance of ITIL framework in the organizations, by contributing to IT governance. To fulfil the purpose of this thesis a detailed guideline for the ITIL implementation was gathered by interviewing the IT professionals.

Organizations that have come to depend on legacy systems face quite a paradoxical problem. Maintaining the system might prove ineffective in accommodating necessary changes, but a system migration project is expensive and incurs a high amount of risk. Organizations are therefore hesitant to respond to the legacy system problem by undertaking action. Legacy system are often not causing their organization any problems at present, but a focus on the future with regard to the legacy system problem is lacking. This results in IT systems reaching an end-of-life state. The research therefore set out to explore a future-oriented perspective on legacy systems by means of observation, a literature review and a survey. The researcher found the key concept of a future-oriented perspective to be that any system that is limiting an organization to grow and innovate can be regarded as a legacy system. A framework to designate legacy status to IT systems is proposed in order to guide practitioners to acknowledge a problematic IT system to facilitate appropriate response at the right time. In relation to a future-oriented perspective, when to designate legacy status is best determined according to the system’s flexibility towards change and the alignment of the system with the business. In that regard, IT systems are end-of-life systems when they are too inflexible to change, and as a result become unaligned with either current operations or a future business opportunity or need.

Physiological markers have long been used to monitor physiological state in individual athletes. More recently, heart rate variability (HRV) has become a popular metric to monitor athletes' physiological state over longer periods of time to guide training and detect fatigue. HRV measured immediately prior to shooting has been shown to be a predictor of shooting performance. However, there is a lack of research on how physiological state as measured by HRV in resting states impacts sports shooting performance over longer periods of time. This thesis explored if there was a relationship between HRV and rifle shooting performance through a six-week-long experiment. Ten participants wore wrist sensors that measured HRV during slow wave sleep and performed simulator rifle shooting tasks twice a week to measure shooting performance. The relationship between HRV and shooting performance was analyzed through Pearson’s correlation coefficient, linear regression, and k-means clustering. The results indicated that there was no relationship between HRV and shooting performance in the participants collectively, except for two participants. The thesis contributed to the current knowledge about physiological state and HRV in relation to sports shooting performance. It also gave new insight into how experiments can be designed to study variability of physiological state in relation to shooting performance over longer periods of time.

Autonomous robots are becoming a bigger part of our society. This thesis aims to evaluate a robot testing dashboard (RTD) that can be used as a new way of finding improvements when developing autonomous robots that do not use machine learning.

The method that is used is design science research, which is used when creating and evaluating an artifact to address a practical problem. In our case the artifact isthe RTD.

This project was performed at a company called Greenworks, which among other things develops and sells autonomous lawn mowers. The company wants to find new testing methods to help develop their autonomous lawnmowers. The RTD is created to visualize the inputs that the lawn mower utilizes to perform its tasks. A human pilot will then control the lawn mower, by only looking at that visualized data. If the pilot using the RTD can execute the same tasks as the lawn mower in its autonomous mode, the test results can be analyzed to see whether the human has done some parts of the tasks differently. The best outcome from the analysis of the test results is to find areas of improvement that can be implemented into the autonomous lawn mower design, both in software and hardware.

For this purpose, an RTD was built and tested at Greenworks. From the tests using the RTD we concluded that it is helpful in the testing process, and we could find areas of improvements after analysis of our tests. However, the use of the RTD will require more time and resources compared to other methods. Each company that uses a similar dashboard concept will have to evaluate if the benefits are worth the time. Furthermore, the concept may not suit all areas of robotics but does seem to suit situations where a human can have an advantage over robots, such as in creative problem solving.

The need for organizations to operate in changing environments is addressed by proposing an approach that integrates organizational development with information system (IS) development taking into account changes in the application context of the solution. This is referred to as Capability Driven Development (CDD). A meta-model representing business and IS designs consisting of goals, key performance indicators, capabilities, context and capability delivery patterns, is being proposed. The use of themeta-model is validated in three industrial case studies as part of an ongoing collaboration project, whereas one case is presented in the paper. Issues related to the use of the CDD approach, namely, CDD methodology and tool support are also discussed.

This thesis has been performed at consulting firm Sweco Position in Jönköping. The thesis is divided into two main sections: theoretical and practical. The theoretical section contains an investigation into the possibilities of implementing a geographical information system (GIS) for administrations of wells with the integration of Bing Maps for Windows 8 and Windows Phone 8. The practical work comprises the development of a prototype for Windows 8 and Windows Phone 8.

The students review the Model-View-ViewModel-pattern on a theoretical basis, compares the differences between Windows 8 Pro and Windows RT. The thesis also contains and investigation into the pros and cons of a web based application compared to a native one.

The result of the thesis will be comprised of a GIS-service developed in C# in co-operation with XAML with the options of saving data locally and a WMS-based service layer for Windows 8 and Windows Phone 8.

Det finns idag få system som ger en god överblick av en restaurangs bokningar och bordsplaceringar. Oftast används papper och penna som ställer till med problem när kunder avbokar, ändrar deras bokning eller helt enkelt inte kommer till restaurangen. Det är även svårt att avgöra huruvida restaurangen är fullbokad eller ej.

Denna rapport behandlar utvecklingen av ett webbaserat bordsbokningssystem för restauranger på uppdrag av en restaurangägare i Jönköping. Systemet ska ge en grafisk överblick av en restaurangs bokningar och hur alla bord ska stå placerade under en kväll. Då systemet webbapplikationen ska ha flera användare, som använder olika enheter, krävs det att systemet ska vara plattformsoberoende.

Med hjälp av HTML5 undersöks det huruvida det går att göra detta system offlinekompatibelt, då uppdragsgivaren önskar att systemet är åtkomligt då Internetuppkopplingen försvinner. Det undersöks även hur en applikation görs användarvänlig och lättmanövrerad samt hur kommunikationen mellan klient och server görs mest effektivt.

Projektet är uppdelat i fyra delar; grafiskt användargränssnitt, webbapplikation, datahantering och serverkommunikation, som i sin tur är indelade i två kategorier; klient och server. De två kategorierna användes som en bas för hela projektets gång, från litteraturgenomgång och forskning till implementation.

Den slutliga webbapplikationen blev ett plattformsoberoende och offlinekompatibelt bordsbokningssystem, där användaren får en grafisk överblick av en vald dags bokningar samt bordsplaceringar.

The work has been performed in collaboration with Jönköping University. The aim of this work has been to study different methods for mobile adaption of large CMS (Content Management System) websites, where the website of Jönköping has been used as a reference.

The website at Jönköping University is used daily by current students, faculties, prospective students and external users. Research carried out by the University shows that the use of mobile devices has increased, and it is therefore necessary to examine the mobile adaptation of the large CMS website.

A layout proposal has been suggested by determining which method that is most relevant for mobile adaption of a large CMS website. The website should adapt to different resolutions and devices according to how the existing website is based in the current situation. Emphasis has been put on menu operations, to navigate through the large website in a user-friendly way. This is going to be a basis for the University in the development of the mobile website.

Based on the results of the choice of method for mobile adaptation, the students have come to the conclusion that the relevant method for a large CMS website is responsive web design. But the choice of method for mobile adaptation can also be based on the need, purpose and target group that a company or organization has with the website.

The work ends with a conclusion and discussion where their opinions have been raised. The conclusion that the students have come up with is that the benefits of responsive web design and the solution of the menu navigation, is the right option for Jönköping University website.

A problem that exhibition halls have is the balance between having good indoor air quality andminimizing energy waste due to the naturally slow decrease of CO2 concentration, which causes Heat-ing, Ventilation and Air-Conditioning systems to keep ventilating empty halls when occupants have leftthe vicinity. Several studies have been made on the topic of CO2 prediction and occupancy predictionbased on CO2 for smaller spaces such as offices and schools. However, few studies have been madefor bigger venues where a larger group of people gather. An online machine learning model using theRiver library was developed to tackle this problem by predicting the CO2 ahead of time. Five datasetswere used for training and predicting, three with real data and two with simulated data. The resultsfrom this model was compared with three already developed traditional models in order to evaluate theperformance of an online machine learning model compared to traditional models. The online machinelearning model was successful in predicting CO2 one hour ahead of time considerably faster than thetraditional models, achieving a r2 score of up to 0.95.

IoT is a rapidly growing area with products in the consumer, commercial and industrial market. Collecting data with multiple small and often battery-powered devices sets new challenges for both security and communication. There has been a distinct lack of a IoT specific communication protocols. The industry has had to use bulky interfaces not suitable for resource-constrained devices. MQTT is a standardised communication protocol made for the IoT industry. MQTT does however not have built-in security and it is up to the developers to implement a suitable security countermeasure. To evaluate how different security countermeasures impact MQTT in complexity, current consumption and security the following research questions are answered.

How do you derive a measurement from the SEF that can be compared with a current consumption measurement?

Which level of security, according to the SEF, will RSA, AES and TLS provide to MQTT when publishing a message to a broker?

What level of complexity is added to MQTT when using chosen security countermeasure?

Which of the analysed security countermeasure upholds an adequate security level while also having a low current consumption?

To answer the above research questions an experiment approach has been used. Implementations of TLS, RSA and AES have been evaluated to measure how they affect the security level and current consumption of an MQTT publication, compared to no security countermeasures at all.Both RSA and AES had the same security level, but the current consumption for RSA was four times higher. The experiment showed that the security level is significantly higher for TLS, while it also has the highest current consumption. The security countermeasure evaluated differs greatly. TLS provides complete protections, while RSA and AES lacks authentication and does not ensure integrity and non-repudiation.Even if the current consumption for TLS is higher, the security it provides make it unreasonable to recommend any of the other security countermeasure implementations.

Enterprise modeling (EM) is a discipline supporting business and IT alignment by providing means for capturing, visualizing and improving different perspectives of an enterprise, including processes,organization structures, products, systems, and business objectives. However, there is a lot of relevant information besides the one presented in enterprise models. Including such information into enterprise models or an integrated presentation of model and data view is supposed to ease decision making for stakeholders in organizations by providing contextual information for the decision at hand. Additional information however usually means additional complexity. This paper explores possibilities of an integrated presentation guided by the following questions: (1) What kind of complementary information should be visualized in an enterprise model?  (2) How can the information be visualized?  (3) How can the content of a specific visualization be adapted by the business stakeholder using it?

Possibilities and benefits of enhancing the existing enterprise models with visualization of additional information are illustrated using a small case study.

Introduction: Instead of replacing existing analogue water meters with Internet of Things (IoT) connected substitutes, an alternative would be to attach an IoT connected module to the analogue water meter that optically reads the meter value using Optical Character Recognition (OCR). Such a module would need to be battery-powered given that access to the electrical grid is typically limited near water meters. Research has shown that offloading the OCR process can reduce the power dissipation from the battery, and that this dissipation can be reduced even further by reducing the amount of data that is transmitted. 

Purpose: For the sake of minimising energy consumption in the proposed solution, the purpose of the study is to find out to what extent it is possible to reduce an input image’s file size by means of resolution, colour depth, and compression before the Google Cloud Vision OCR engine no longer returns feasible results.  

Method and implementation: 250 images of analogue water meter values were processed by the Google Vision Cloud OCR through 38 000 different combinations of resolution, colour depth, and upscaling. 

Results: The highest rate of successful OCR readings with a minimal file size were found among images within a range of resolutions between 133 x 22 to 163 x 27 pixels and colour depths between 1- and 2-bits/pixel. 

Conclusion: The study shows that there is a potential for minimising data sizes, and thereby energy consumption, by offloading the OCR process by means of transmitting images of minimal file size. 

Approximate string matching consists in identifying strings as similar even ifthere is a number of mismatch between them. This technique is one of thesolutions to reduce the exact matching strictness in data comparison. In manycases it is useful to identify stream variation (e.g. audio) or word declension (e.g.prefix, suffix, plural).

Approximate string matching can be used to score terms in InformationRetrieval (IR) systems. The benefit is to return results even if query terms doesnot exactly match indexed terms. However, as approximate string matchingalgorithms only consider characters (nor context neither meaning), there is noguarantee that additional matches are relevant matches.

This paper presents the effects of some approximate string matchingalgorithms on search results in IR systems. An experimental research design hasbeen conducting to evaluate such effects from two perspectives. First, resultrelevance is analysed with precision and recall. Second, performance is measuredthanks to the execution time required to compute matches.

Six approximate string matching algorithms are studied. Levenshtein andDamerau-Levenshtein computes edit distance between two terms. Soundex andMetaphone index terms based on their pronunciation. Jaccard similarity calculatesthe overlap coefficient between two strings.

Tests are performed through IR scenarios regarding to different context,information need and search query designed to query on a technicaldocumentation related to software development (man pages from Ubuntu). Apurposive sample is selected to assess document relevance to IR scenarios andcompute IR metrics (precision, recall, F-Measure).

Experiments reveal that all tested approximate matching methods increaserecall on average, but, except Metaphone, they also decrease precision. Soundexand Jaccard Similarity are not advised because they fail on too many IR scenarios.Highest recall is obtained by edit distance algorithms that are also the most timeconsuming. Because Levenshtein-Damerau has no significant improvementcompared to Levenshtein but costs much more time, the last one is recommendedfor use with a specialised documentation.

Finally some other related recommendations are given to practitioners toimplement IR systems on technical documentation.

This thesis aims to investigate how a Polychromatic Two Dimentional Barcode mightoutperform a Monochromatic Two Dimentional Barcode when the scanner resolutionis limited. The performance differences are captured through an experiment. In theexperiment three different scanners are used, each scanner having a different resolutionto represent a wide range of scanners that are being used at the time of writing. Thesymbologies are displayed on a tablet and photos of them are captured from a fixeddistance, then the photos are tested for decodability. The scanner and tablet are mounted ina fixture to reduce the impact from undesired factors. To represent the Monochromatic TwoDimentional Barcode the Quick response symbology is used and for the PolychromaticTwo Dimentional Barcode the Just Another Barcode symbology is used. The result of theexperiment shows that the lowest resolution scanner is not able to decode a larger amountof data from the Polychromatic Two Dimentional Barcode. The two scanners with thehighest resolution are able to decode more data from the Polychromatic Two DimentionalBarcode because the symbology has the ability to encode more data compared to theMonochromatic Two Dimentional Barcode.

Abstract

Purpose – To study the possibility of using a NIR hardware solution to photograph individuals in a private vehicle as well as an analysis of its images.

Method – A study of existing theories around the NIR-method’s performance in selected conditions and individual tests were performed to examine if the literature statements were valid for this study. Two empirical tests have been carried out, the first was carried out at Kapsch test track and the other outside the test track in a single stationary test. An interview which formed the basis for the assessment on the quality of empirical data with a focus on computer-based detection of the number of individuals in the vehicle.

Findings – The results have demonstrated the potential of the NIR method’s performance in a fully automated detection system for the number of individuals inside the vehicle. Empirical data indicates that the method can depict individuals inside vehicles of sufficiently high quality, but it is greatly affected by reflections, weather and light conditions.

Implications – Result supports the assumption that the NIR method using an external light source can be used to image the interior through a varying number of weather and lightning conditions. The study originated until the results suggested that a NIR-based hardware setup can create images with high enough quality for the human eye to be able to detect the number of individuals inside the vehicle.If the overall performance into account, it suggests that the main problem with the use of the hardware set is to maintain the quality of the whole sample and that the crucial variables for the method’s performance is the influence of light and reflection conditions.

Limitations – The major limitations have been that we limited ourselves to a subjective analysis of the selection and assessment on the image features for computer-based detection of the number of individuals in the vehicle. We were limited to two tests, one in tough conditions where only the driver was in the vehicle and the second stationary test, where the focus was on the number of people in vehicles and light sources impact on the result.

This study presents an investigation into the use of ChatGPT in the software development field. With the rapid growth of artificial intelligence (AI) and its impact on the technology field, tools like ChatGPT have become increasingly relevant in software development. The main aim of the study is to investigate how ChatGPT can work as a tool in the software development process and if it can help facilitate the development process for a developer.Through a combination of questionnaire survey and experiments, the study has shown that ChatGPT has the potential to be a tool of great value in software development. This by offering automatic code completion and other aids that can improve developers' efficiency. The results of this study indicate that the integration of AI tools such as ChatGPT into the software development process can lead to improved workflows and increased productivity. However, further research should be conducted to better understand potential benefits and challenges. To further understand ChatGPT's role in software development, it is recommended to conduct more extensive field studies where the tool is used in real world development projects.

The goal of this study is to compare the differences between Virtual Reality with a head mounted display and traditional, 2-dimensional monitors when used in simulation and testing. By conducting this comparison, the aim was to find out whether a visualization method that uses 3-dimensions as opposed to a method which only uses 2-dimensions, provides a better solution for viewing 3-dimensional data gathered from actual vehicles in real-world tests. 

The approach to investigate this is by developing a tool that can visualize data from a dataset in both 2 and 3-dimensions. The tool was then evaluated by allowing a group of participants, whose work is related to testing within the automotive industry, perform tasks using the tool and timing the results. In addition to the timed results, the participants were also asked to answer a questionnaire with the aim of providing a more detailed look into how they experienced the two methods of visualisation. 

Overall, the impression of using VR as a method of visualization was by all participants positive and it was concluded that the participants performed marginally better with VR but at the cost of slight discomfort and some fatigue. However, the results could be accurately improved as the precision of the gathered data was found limited by the method used to collect it in the experiment.

The purpose of this study is to investigate how transfer time differs in relation toscalability between two back-end solutions in LoRaWAN. The solutions are Node-REDand Chirpstack. The study is carried out using the methods experiment and case study.In the experiment, a t-test was performed to answer whether the null hypothesis can berejected or not. The results show that the null hypothesis could not be rejected, and thatthere is no difference in scalability. Apart from the t-test, the results show that Chirpstackscales worse than Node-RED at four or more added LoRa-units. The conclusion,however, is that the difference is small enough to be considered insignificant for thechoice of back-end solution. The study is limited to seven connected LoRa units. 

In this thesis, a method for detecting ditches using digital elevation data derived from LiDAR scans was developed in collaboration with the Swedish Forest Agency.

The objective was to compare a machine learning based method with a state-of-the-art automated method, and to determine which LiDAR-based features represent the strongest ditch predictors.

This was done by using the digital elevation data to develop several new features, which were used as inputs in a random forest machine learning classifier. The output from this classifier was processed to remove noise, before a binarisation process produced the final ditch prediction. Several metrics including Cohen's Kappa index were calculated to evaluate the performance of the method. These metrics were then compared with the metrics from the results of a reproduced state-of-the-art automated method.

The confidence interval for the Cohen's Kappa metric for the population was calculated to be [0.567 , 0.645] with a 95 % certainty. Features based on the Impoundment attribute derived from the digital elevation data overall represented the strongest ditch predictors.

Our method outperformed the state-of-the-art automated method by a high margin. This thesis proves that it is possible to use AI and machine learning with digital elevation data to detect ditches to a substantial extent.

The rise of Large Language Models (LLMs) over the past years and their use in software development has raised questions and concerns about the quality of the code they generate. While LLMs such as ChatGPT have the potential to accelerate the development of new software and boost code productivity, their ability to generate high-quality code is debatable. This study presents an investigation into the code quality that is generated by LLMs, specifically focusing on iOS applications generated by ChatGPT.

To investigate the code quality of the generated iOS applications, the study implemented three movie applications in Swift with ChatGPT-3.5 and ChatGPT-4, along with a similar application written by a human developer. To measure the code quality, a set of code quality metrics was chosen to make a fair evaluation of the results.

The findings showed that ChatGPT can generate iOS applications with code quality comparable to a human-written application, and ChatGPT-4 in particular showed this capability. However, the ChatGPT-3.5 model showed inconsistent results, suggesting potential limitations in the current model. The level of human intervention required for development varies depending on the complexity of the task, with simpler tasks requiring less intervention. Overall, the study suggests that human intervention and guidance are essential for developing a working application.

Keywords: Code generation, Code Quality, Generative AI, iOS code quality, iOS development, Large Language Models

Simulations are an important part of the process of designing new computer boards at the Centre of Excellence - Computers at Saab AB in Jönköping. The earlier problems and weaknesses in the design can be found during the design process the less time and money it will take to fix them. The engineers at CoE uses HyperLynx, an analysis and simulation software from Mentor Graphics, to simulate all the critical nets at the board. By doing so, the majority of the problems can be fixed before the prototyping stage.

However, the engineers need to know how the simulated signals relate to real signals if the simulator is to be useful. Therefore the question to be answered in this study is how well does the simulated signals in HyperLynx imitate real signals? The question was answered by comparing simulated signals with measurements of corresponding signals on a test board.

Overall the shapes of the signals are matching for both which reflections occurs and the timing of the reflections. The only noticeable difference found throughout the study is a slightly smaller amplitude of the reflections for the simulated signals compared to the corresponding measured signal. Due to these results, HyperLynx can be considered a high quality simulator.

The idea would be to unify it into a system where people from different countries can provide information on their hometowns, helping people who are interested in them. The system created is a collaborative Web system in which people can access and edit contents by entering information about their hometowns, and this information will help other people who decide to move to the different cities.

Energy consumption reduction has been an increasing trend in machine learning over the past few years due to its socio-ecological importance. In new challenging areas such as edge computing, energy consumption and predictive accuracy are key variables during algorithm design and implementation. State-of-the-art ensemble stream mining algorithms are able to create highly accurate predictions at a substantial energy cost. This paper introduces the nmin adaptation method to ensembles of Hoeffding tree algorithms, to further reduce their energy consumption without sacrificing accuracy. We also present extensive theoretical energy models of such algorithms, detailing their energy patterns and how nmin adaptation affects their energy consumption. We have evaluated the energy efficiency and accuracy of the nmin adaptation method on five different ensembles of Hoeffding trees under 11 publicly available datasets. The results show that we are able to reduce the energy consumption significantly, by 21% on average, affecting accuracy by less than one percent on average.

The strategy by which a platform owner manages the future trajectory of its platform involves many unknowns. In particular, the ambition to simultaneously control the platform and distribute design capability to users is challenging. While there is an emerging literature on strategy in platform ecosystems, little empirical evidence exists about the series of strategic actions that platform owners conduct to create value in an ecosystem context. Drawing on a strategy-as-process perspective, this paper augments existing platform perspectives by seeking to understand the micro-strategizing of a platform owner. To this end, we report a multiple case study of Apple’s use of application programming interfaces for generating value from the iPhone platform. Our comparative analysis identifies and explores five different micro-strategies that can be enacted proactively or reactively: counteracting, monetizing, resourcing, securing, and sustaining. The paper concludes with a number of theoretical and practical implications of these micro-strategies and their interaction.

This thesis has been carried out in cooperation with Saab Electronic Defence Systems in Jönköping which has a wide range of products, mainly for Avionic applications. In order to evaluate and verify their design it is often required to simulate behaviour and debug as early as possible. System simulation can enable software development and debug to commence long before a hardware prototype is available and also scale with the size and complexity of the system.

Another benefit of simulation is to more easily determine root causes to system crashes, establish worst case execution time cases and making fault injection. Therefore this thesis will focus on evaluating simulators and emulators, as development- and testing tools.

This report contains a marketing research, where ten emulators and simulators were found. Of these, two simulators were chosen for further investigation; WindRiver Simics and Imperas OVPSim. The evaluations considered both usability and debugging features as well as comparative tests between real hardware and the simulated environment. The results show that simulators can help in product development, but they are not yet optimal for evaluating hardware. This is because deviations may occur in execution times between real and simulated hardware architectures.

Websites today only offer simpler form of technical analysis and are not fun to use, therefore student decided to build a website that makes technical analysis a bit more fun by giving user possibility to experiment with settings for technical indicators and also see clear visible results from analysis. Student decided to build website in ASP.NET. Technical indicators for this project only consist of those who give buy and sell-signals via cross-over, no divergence or pattern finding.This project has three questions that define this project. It’s important that there is good functionality so that performing an analysis is perceived as simple, one question is therefore; what functionality for website is needed in order for analysis to be perceived as more simple?Technical analysis is a pretty complex subject and demands an interface that is perceived as easy to understand and easy to use, it’s therefore important that the interface is well designed, second question is therefore; how should the interface be designed to be user-friendly?When systems grow large they often become hard to develop and later on unmaintainable because of the accumulated complexity and dependency between classes, the code is a mess, the last question is therefore; how can the systems complexity be eased with object-oriented design principles?Jakob Nielsens ten heuristics for User Interface Design were used as inspiration for designing the interface for the website. The system design follows SOLID principles, some pattern-design were also used because pattern-design often fulfills SOLID principles or makes for pretty good solutions in regular code-problems.At the beginning of the project the student did a small research to find out what was needed in order to complete project. Work-method for project follows agile development where decisions were made on a weekly basis. The project was divided into three phases where each phase was strongly coupled to a specific area of responsibility. Prototypes for interface were made and used as a basis for the resulting interface.The project led to a working website with good functionality. Filter was considered as important in order to ease shaping of analysis because the user could more easily sort and pick stock. The student assumed that the user would want fast and easy access to their stock so portfolio management were implemented so that user could more easily get to stock that was considered as favorites. The interface follows to a big extent Jakob Nielsens ten heuristics for User Interface Design and is proven by comparing interface with principles. The same goes for design of the system, design is proven by comparing with principles, still to this day system is considered easy to continue development.Student made the conclusion that SOLID principles were very important in order for the system to maintain its health and took experience from these principles. Student became happy with the interface but more focus could’ve been given for a more interactive interface because it might’ve been perceived as more intuitive.

This thesis is about development of administrative functions for the application QuickPick, which is a value system for warehouses. Today, there are no functions for the user to sort, group or filter the view settings in the application. Those who use the system need to contact Qsys Sverige AB to make this changes. Where also this thesis has been performed. The thesis deals theoretically with how a warehouse works, how you program in a general way, so it will be easier to continue the development of the functions and make a user friendly system for an administrator. The new functions will be available in a web-portal for administrators and it has been developed in C# and ASP.NET. The result of the thesis will be administrative functions for the view settings in a web-portal which can be used in the QuickPick application.

There is a high demand to summarize and analyze the opinions in online customer reviews. Sentiment analysis is one of the study fields in this area. Mining comparative opinions is an important application of sentiment analysis. It includes identifying the comparative opinions and the aspects that are compared. It also identifies the sentiment classification of the opinion as positive or negative. This helps businesses to make effective decisions in the development and promotion of their products and services, and to better understand their competitors. Different approaches could be used to address this sentiment analysis application, such as Machine Learning. The application is a multi-label classification problem from a machine learning perspective. This paper presents a case study to evaluate three multi-label machine learning classification techniques in addressing the problem. Empirical experiments are conducted on a domain-independent dataset of online customer reviews from Amazon for the evaluation purpose.

Deepfakes are an emerging problem in social media and for celebrities and political profiles, it can be devastating to their reputation if the technology ends up in the wrong hands. Creating deepfakes is becoming increasingly easy. Attempts have been made at detecting whether a face in an image is real or not but training these machine learning models can be a very time-consuming process. This research proposes a solution to training deepfake detection models cooperatively on the edge. This is done in order to evaluate if the training process, among other things, can be made more efficient with this approach. 

The feasibility of edge training is evaluated by training machine learning models on several different types of iPhone devices. The models are trained using the YOLOv2 object detection system. 

To test if the YOLOv2 object detection system is able to distinguish between real and fake human faces in images, several models are trained on a computer. Each model is trained with either different number of iterations or different subsets of data, since these metrics have been identified as important to the performance of the models. The performance of the models is evaluated by measuring the accuracy in detecting deepfakes. 

Additionally, the deepfake detection models trained on a computer are ensembled using the bagging ensemble method. This is done in order to evaluate the feasibility of cooperatively training a deepfake detection model by combining several models. 

Results show that the proposed solution is not feasible due to the time the training process takes on each mobile device. Additionally, each trained model is about 200 MB, and the size of the ensemble model grows linearly by each model added to the ensemble. This can cause the ensemble model to grow to several hundred gigabytes in size.

To develop or maintain a piece of code requires a certain level of comprehension of the developed or maintained software itself. To achieve this goal the developer uses a set of different tools. This report will focus on two types of debug tools: single trace and multiple traces. The purpose of the study is to examine how multiple traces can contribute to an improved program comprehension. The study was carried out through experiments and interviews. The experiment consisted of 10 typical comprehension tasks in a development context. Eclipse and Trace Compass were used to display the logs. Eclipse is a development environment that shows the source code. Trace Compass is a tool for inspecting traces.  After the experiment, an interview was carried out with the subjects of the experiment. The results of this study indicated that multiple traces could have an advantage over a single trace when the task is to understand the interactions between code components in a software system. One of the limitations of the study was due to the limited number of subjects taken part in the study and cannot be used to draw a more general conclusion. 

Today, CAD-system are used for much more than just geometric modeling. They are complemented by various software and information sources forming a complete environment for handling all life-cycle aspects of the product. In such systems, the CAD-system works as a central hub. The software and information sources may be of various types making the system highly heterogenous. This presents problems with transparency and traceability in the system making long term management difficult. In this paper, a novel tool is presented to keep track of the dependencies between the various parts of such systems providing an overview and making it possible to predict the effect of proposed changes and facilitating long term management. The tool is tested in a highly heterogeneous environment at a manufacturer of aerospace components, with the result that the traceability is expected to increase at the expense of that time must be spent on defining dependencies and meta-information as the system is evolving.

Students at Jönköping School of Engineering were given an assignment from Jönköping municipality, to evaluate their decision support system, QlikView. The students have also developed proposals for improvement with focus on usability.The Jönköpings municipality has currently got 11000 employees and consists of nine different administrations. The target group for QlikView is approximately 600 first-line managers.

The intention of QlikView is that the users can get an overall picture of their business by having all information in just one system.

The purpose of the thesis is to obtain a picture of what the users think about the system today and present relevant suggestions for improvement, which the Jönköping municipality can use when the introduction of the new version of QlikView takes place. The research questions that the study aims to answer are:

• Has QlikView got a user friendly interface?• How can the interface be improved to become more user friendly?

Theories that this work is based on is Jacob Nielsens ten usability principles and Ben Schneidermans eight golden rules. They are both well-known authors in the subject of interaction design. The thesis also deals with theories regarding how an evaluation should be performed and how you collect data in the most positive way.

The evaluation is started with a questionnaire that was sent out to the employees who had been logged into the system the past six months, the students also carried out interviews with 6 first-line managers. The result from the questionnaire and the interviews is presented in both diagrams, tables and in running text.

In the questionnaire, 44% of the respondents thought that the usability in QlikView was low. Opinions that stood out were that the selections are marked in an unclear way and that respondents found it difficult to know how to use the system.

The six interviewed persons agreed that they all wanted to have a search box instead of the search function that today is ”hidden”.

The suggested improvements that are presented are based on theories and result from the questionnaire and interviews.

The work ends with a discussion and a conclusion. The conclusion is that the Jönköping municipality should make some changes in terms of functions and layout to enhance the usability. The students hope that this work will help the Jönköping municipality in their new version of QlikView.

This report describes a further development of an application for handling documents in investment projects. The older version of the application is developed in VB6, which is a relatively out-of-date programming language. This application is also developed for a specific customer and handles therefore only their needs regarding the handling of documents.

There are two main reasons for the further development of this application. The first is modernization, i.e. that the new application is going to be developed in C#, which is both a more modern programming language and adds new opportunities to further develop the application into a web-based application. The second and most important reason is that the new application shall be more general and easy to adapt for several costumers needs.

The most important function for the further development was that you should not have to change anything in the code to customize the application for different customers, but instead just have to modify a database which then defines the structure of the application.