TikTok differs from how the media audience is used to seeing other social media platforms. When opening the app, the user does not see the friends you have decided to follow. Instead, you are faced with an algorithmically decided and never-ending feed of content personified individually for the specific user. In recent years, TikTok has become a prominent and rapidly growing platform, especially among younger media users. The emergence of TikTok usage among the youth implies an increased need for examining cultural phenomena that are performed on this platform. This study will be exploring the emergence of the online phenomenon known as mediated public shaming on TikTok by critically reviewing how young Swedish TikTok users are engaging in and experiencing the mediated public shaming that is occurring on TikTok as well as its effects by taking a theoretical departure from media literacy theories. The study is a qualitative reception study where the empirical material is conducted by one-to-one interviews with nine mundane Swedish TikTok users between the ages of 16–27. It was discovered that young TikTok users have a complex relationship with the mediated public shaming they face on TikTok and engage in the concept in a rather objective and reflective manner. They do, however, express concern that the design of the media, in conjunction with mediated public shaming, may allow for subconscious effects of their opinions. Looking forward, there is an indicated compelling need for continued research within the field, proposedly further research of online cultures’ roles in the determination of platform design and construction of algorithms.

Time series is a collection of points gathered at regular intervals. Time series analysis explores the time correlations and tries to model it according to trend and seasonality. One of the most relevant tasks, in time series analysis, is forecasting future values, which is considered fundamental in many real-world scenarios. Nowadays, many companies forecast using hand-written models or naive statistical models. Call centers are the front end of the organization, managing the relationship with the customers. A key challenge for call centers remains the call load forecast and the optimization of the schedule. Call load indicates the number of calls a call center receives. The call load forecast is mostly exploited to schedule the staff. They are interested in the short term forecast to handle the unforeseen and to optimize the staff schedule, and in the long term forecast to hire or assign staff to other tasks. Machine learning has been applied to several fields reporting excellent results, and recently, time series forecasting problems have gained a high-interest thanks to the new recurrent network, named Long-short Term Memory. This thesis has explored the capabilities of machine learning in modeling and forecasting call load time series, characterized by a strong seasonality, both at daily and hourly scale. We compare Seasonal Artificial Neural Network (ANN) and a Long-Short Term Memory (LSTM) models with Seasonal Autoregressive Integrated Moving Average (SARIMA) model, which is one of the most common statistical method utilized by call centers. The primary metric used to evaluate the results is the Normalized Mean Squared Error (NMSE), the secondary is the Symmetric Mean Absolute Percentage Error (SMAPE), utilized to calculate the accuracy of the models. We carried out our experiments on three different datasets provided by the Teleopti. Experimental results have proven SARIMA to be more accurate in forecasting at daily scale across the three datasets. It performs better than the Seasonal ANN and the LSTM with a limited amount of data points. At hourly scale, Seasonal ANN and LSTM outperform SARIMA, showing robustness across a forecasting horizon of 160 points. Finally, SARIMA has shown no correlation between the quality of the model and the number of data points, while both SANN and LSTM improves together with the number of sample / Tidsserie är en samling punkter som samlas in med jämna mellanrum. Tidsseriens analys undersöker tidskorrelationerna och försöker modellera den enligt trend och säsongsbetonade. En av de mest relevanta uppgifterna, i tidsserieranalys, är att förutse framtida värden, som anses vara grundläggande i många verkliga scenarier. Numera förutspår många företag med handskrivna modeller eller naiva statistiska modeller. Callcenter är organisationens främre del och hanterar relationen med kunderna. En viktig utmaning för callcentra är fortfarande samtalslastprognosen och optimeringen av schemat. Samtalslast indikerar antalet samtal ett callcenter tar emot. Samtalslastprognosen utnyttjas mest för att schemalägga personalen. De är intresserade av den kortsiktiga prognosen för att hantera det oförutsedda och för att optimera personalplanen och på långsiktigt prognos för att anställa eller tilldela personal till andra uppgifter. Maskininlärning har använts på flera fält som rapporterar utmärkta resultat, och nyligen har prognosproblem i tidsserier fått ett stort intresse tack vare det nya återkommande nätverket, som heter Long-short Term Memory. Den här avhandlingen har undersökt kapaciteten för maskininlärning i modellering och prognoser samtalsbelastningstidsserier, kännetecknad av en stark säsongsbetonning, både på daglig och timskala. Vi jämför modeller med säsongsmässigt artificiellt neuralt nätverk (ANN) och ett LSTM-modell (Long- Short Term Memory) med Seasonal Autoregressive Integrated Moving Average (SARIMA)-modell, som är en av de vanligaste statistiska metoderna som används av callcenter. Den primära metriken som används för att utvärdera resultaten är det normaliserade medelkvadratfelet (NMSE), det sekundära är det symmetriska genomsnittet absolut procentuellt fel (SMAPE), som används för att beräkna modellernas noggrannhet. Vi genomförde våra experiment på tre olika datasätt från Teleopti. Experimentella resultat har visat att SARIMA är mer exakt när det gäller prognoser i daglig skala över de tre datasätten. Det presterar bättre än Seasonal ANN och LSTM med en begränsad mängd datapoäng. På timskala överträffar Seasonal ANN och LSTM SARIMA och visar robusthet över en prognoshorisont på 160 poäng. SARIMA har slutligen inte visat någon korrelation mellan modellens kvalitet och antalet datapunkter, medan både SANN och LSTM förbättras tillsammans med antalet sampel.

No / Over the past decade, wireless communications has experienced tremendous growth, and this growth is likely to multiply in the near future. The proliferation of mobile users and an ever increasing demand for multimedia services has resulted in greater capacity requirements. Radio frequency spectrum is scarce and cannot meet this ever increasing demand and the required Quality of Service (QoS) will no longer be achieved if efficient Radio Resource Management (RRM) solutions are not found. Conventional Radio Access Networks (RAN) have standalone Base Stations (BS) with capacity preconfigured for peak loads. These RANs have high call blocking and dropping rates since BSs resources cannot be shared. Cloud based RANs (C-RAN) have been proposed as a cost and energy efficient way of meeting high capacity demand of future wireless access networks by consolidating BSs to the cloud. Instead of relying on rejection of new call requests due to limited BS resources, C-RAN takes benefit of the cloud elasticity, which allows dynamic provisioning of cloud BS resources. This paper presents a novel C-RAN Call Admission Control (C-RAN CAC) to ensure Grade of Service (GoS) by improving blocking probability and improvement of call waiting times. Call blocking probability, call average waiting time and system utilization are used to evaluate the performance of the proposed CAC algorithm.

No description available.

There is an urgent need to reduce emissions from maritime transportation to meet environmental targets set by international organizations and governments. To reduce emissions from maritime transportation, technical, market-based, and operational measures can be used. In this thesis, the focus is on operational measures, and in particular Just-in-Time arrival in the port call process. Just-in-Time arrival in the context of port calls refers to maintaining an optimal vessel sailing speed to arrive to the port when the availability of berth and other services are ensured. In earlier studies, the estimated fuel and emission savings potential of Just-in-Time arrival, is promising. Despite the promising potential of Just-in-Time, its implementation remains limited, with few real-world examples. The purpose of this thesis is to explore how to implement Just-in-Time arrival by studying coordination in the port call process.    Two research questions were formulated to address the purpose. The first aims to capture the potential benefits of implementing Just-in-Time arrival in port calls and the second aims to address what is required to implement Just-in-Time arrival in port calls. This thesis is based on two studies in the Swedish context. First, a quantitative study, in which Automatic Identification System data in combination with port call statistics and vessel-specific data were used to estimate the fuel and emission savings potential of Just-in-Time arrival. Second, a qualitative single case-study exploring the coordination mechanisms necessary for implementing Just-in-Time arrival in port calls was conducted.    The studies show that fuel and emission savings potential of Just-in-Time in previous studies is overestimated due to the assumptions used. Though, the implementation of Just-in-Time has potential to improve port call actors’ resource planning and utilization and increase the competitiveness of ports. This is because Just-in-Time arrival has the potential to aid actors in reaching mandatory emission reduction targets. To implement Just-in-Time arrival, it is necessary to coordinate the plans of actors. The required mechanisms to coordinate planning are pre-booking berth allocation policy and port community systems. The pre-booking policy implies booking time-slots for berths, facilitated by using the port community system. The port community system and the pre-booking policy enable the effective coordination of the planning processes of individual actors enabling Just-in-Time arrival in port calls. / Det är nödvändigt att minska utsläppen från sjöfartssektorn för att uppnå de klimatpolitiskamålen som har fastställts av internationella och nationella organisationer. För att minska utsläpp från sjöfarten och uppnå de klimatpolitiskamålen kan tekniska, policy, och operativa åtgärder användas. Fokus i denna avhandling är på operativa åtgärder, mer specifikt Just-in-Time ankomst vid hamnanlöp. Just-in-Time ankomst innebär att hålla en seglingshastighet som möjliggör ankomst till hamn vid den tidpunkt kajplatser och andra tjänster (exempelvis lotsning) är tillgängliga utan fördröjning. Tidigare studier visar att det finns en potential att spara bränsle och minska utsläpp genom att införa Just-in-Time ankomst. Trots potentialen är införandet av Just-in-Time ankomst begränsat i praktiken. Syftet med avhandlingen är att utforska hur Just-in-Time ankomst kan implementeras genom att studera koordineringen av aktörers aktiviteter under anlöpsprocessen.    Syftet uppnås genom att besvara två forskningsfrågor. Den första forskningsfrågan berör potentialen av införandet av Just-in-Time ankomst vid hamnanlöp. I den andra frågan undersöks hur olika koordineringsmekanismer kan användas för att koordinera hamnaktörerna för att realisera potentialen av Just-in-Time ankomst. Två studier har genomförts. Först gjordes en kvantitativ modellering för att uppskatta bränsle- och utsläppsbesparingar för Just-in-Time anlöp i Sverige, baserad på Automatic Identification System data, hamnanlöpstatistik samt fartygsdata. Därefter har en kvalitativ fallstudie genomförts som har utforskat hur olika koordineringsmekanismer kan användas för att koordinera enskilda aktörers planeringsprocesser under anlöpsprocessen samt undersöka potentialen av införandet av Just-in-Time ankomst.    Resultat visar att bränsle- och utsläppsbesparingspotentialen med Just-in-Time ankomst i tidigare studier ofta har överskattats på grund av antaganden som använts. Vidare framkom att implementering av Just-in-Time ankomst ha ett positivt inflyttande på aktörernas resursplanering- och utnyttjade och att hamnar kan öka sin konkurrenskraft tack vare sambandet mellan Just-in-Time ankomst och obligatoriska åtgärder för att minska utsläpp. För att kunna implementera Just-in-Time ankomst krävs förbättrad koordinering mellan aktörerna genom införandet av en förbokningspolicy av kajplatser. För att kunna förboka krävs förbättrad planerings och informationsdelning, det senare kan nås genom införandet av digitala informationsplattformar (port community system).

There is an urgent need to reduce emissions from maritime transportation to meet environmental targets set by international organizations and governments. To reduce emissions from maritime transportation, technical, market-based, and operational measures can be used. In this thesis, the focus is on operational measures, and in particular Just-in-Time arrival in the port call process. Just-in-Time arrival in the context of port calls refers to maintaining an optimal vessel sailing speed to arrive to the port when the availability of berth and other services are ensured. In earlier studies, the estimated fuel and emission savings potential of Just-in-Time arrival, is promising. Despite the promising potential of Just-in-Time, its implementation remains limited, with few real-world examples. The purpose of this thesis is to explore how to implement Just-in-Time arrival by studying coordination in the port call process. Two research questions were formulated to address the purpose. The first aims to capture the potential benefits of implementing Just-in-Time arrival in port calls and the second aims to address what is required to implement Just-in-Time arrival in port calls. This thesis is based on two studies in the Swedish context. First, a quantitative study, in which Automatic Identification System data in combination with port call statistics and vessel-specific data were used to estimate the fuel and emission savings potential of Just-in-Time arrival. Second, a qualitative single case-study exploring the coordination mechanisms necessary for implementing Just-in-Time arrival in port calls was conducted. The studies show that fuel and emission savings potential of Just-in-Time in previous studies is overestimated due to the assumptions used. Though, the implementation of Just-in-Time has potential to improve port call actors’ resource planning and utilization and increase the competitiveness of ports. This is because Just-in-Time arrival has the potential to aid actors in reaching mandatory emission reduction targets. To implement Just-in-Time arrival, it is necessary to coordinate the plans of actors. The required mechanisms to coordinate planning are pre-booking berth allocation policy and port community systems. The pre-booking policy implies booking time-slots for berths, facilitated by using the port community system. The port community system and the pre-booking policy enable the effective coordination of the planning processes of individual actors enabling Just-in-Time arrival in port calls. / Det är nödvändigt att minska utsläppen från sjöfartssektorn för att uppnå de klimatpolitiskamålen som har fastställts av internationella och nationella organisationer. För att minska utsläpp från sjöfarten och uppnå de klimatpolitiskamålen kan tekniska, policy, och operativa åtgärder användas. Fokus i denna avhandling är på operativa åtgärder, mer specifikt Just-in-Time ankomst vid hamnanlöp. Just-in-Time ankomst innebär att hålla en seglingshastighet som möjliggör ankomst till hamn vid den tidpunkt kajplatser och andra tjänster (exempelvis lotsning) är tillgängliga utan fördröjning. Tidigare studier visar att det finns en potential att spara bränsle och minska utsläpp genom att införa Just-in-Time ankomst. Trots potentialen är införandet av Just-in-Time ankomst begränsat i praktiken. Syftet med avhandlingen är att utforska hur Just-in-Time ankomst kan implementeras genom att studera koordineringen av aktörers aktiviteter under anlöpsprocessen.    Syftet uppnås genom att besvara två forskningsfrågor. Den första forskningsfrågan berör potentialen av införandet av Just-in-Time ankomst vid hamnanlöp. I den andra frågan undersöks hur olika koordineringsmekanismer kan användas för att koordinera hamnaktörerna för att realisera potentialen av Just-in-Time ankomst. Två studier har genomförts. Först gjordes en kvantitativ modellering för att uppskatta bränsle- och utsläppsbesparingar för Just-in-Time anlöp i Sverige, baserad på Automatic Identification System data, hamnanlöpstatistik samt fartygsdata. Därefter har en kvalitativ fallstudie genomförts som har utforskat hur olika koordineringsmekanismer kan användas för att koordinera enskilda aktörers planeringsprocesser under anlöpsprocessen samt undersöka potentialen av införandet av Just-in-Time ankomst.    Resultat visar att bränsle- och utsläppsbesparingspotentialen med Just-in-Time ankomst i tidigare studier ofta har överskattats på grund av antaganden som använts. Vidare framkom att implementering av Just-in-Time ankomst ha ett positivt inflyttande på aktörernas resursplanering- och utnyttjade och att hamnar kan öka sin konkurrenskraft tack vare sambandet mellan Just-in-Time ankomst och obligatoriska åtgärder för att minska utsläpp. För att kunna implementera Just-in-Time ankomst krävs förbättrad koordinering mellan aktörerna genom införandet av en förbokningspolicy av kajplatser. För att kunna förboka krävs förbättrad planerings och informationsdelning, det senare kan nås genom införandet av digitala informationsplattformar (port community system).

The purpose with this paper is to study anti-muslim content within Swedish parliament proposals between the years 2019 and 2022. The constitutional comittee response is highlighted so it could be compared to EU:s attempts to create a unified European identity. The questions for this paper are: what ideological content is uttered in anti-muslim Swedish parliament proposals during 2019 and 2022, what ideological content is shown in parliament debate and the following parliament decisions in relation to anti-muslim proposals and how does the Swedish parliament debate relate to both binding and nonbinding international guidelines and documents? Document- and content analysis has been used for this paper. The chosen theory for this paper is the multilateral model for understanding islamophobia as well as the conclusions made by Olivier Roy. The conclusions for this paper are that Swedish parliament proposals are in accordance with what is warned by international documents where islamophobias presence is increased in Sweden. The constitutional committe is seen as in accordance with international documents for the promotion of a united European identity and European values.

No description available.

No description available.

Radio frequency system optimization and troubleshooting remains one of the most challenging aspects of working in a cellular network. To stay competitive, cellular providers continually monitor the performance of their networks and use this information to determine where to improve or expand services. As a result, operators are saddled with the task of wading through overwhelmingly large amounts of data in order to trouble-shoot system problems. Part of the difficulty of this task is that for many complicated problems such as hand-off failure, clues about the cause of the failure are hidden deep within the statistics of underlying dynamic physical phenomena like fading, shadowing, and interference. In this research we propose that Hidden Markov Models (HMMs) be used as a method to infer signature statistics about the nature and sources of faults in a cellular system by fitting models to various time-series data measured throughout the network. By including HMMs in the network management tool, a provider can explore the statistical relationships between channel dynamics endemic to a cell and its resulting performance. This research effort also includes a new distance measure between a pair of HMMs that approximates the Kullback-Leibler divergence (KLD). Since there is no closed-form solution to calculate the KLD between the HMMs, the proposed analytical expression is very useful in classification and identification problems. A novel HMM based position location technique has been introduced that may be very useful for applications involving cognitive radios. / Ph. D.