Arbetet har svarat mot frågan om hur ett befäls arbetssituation ser ut i dag på bryggan och hur den mängd regler och riktlinjer som finns för vaktgående befäl påverkar hans förmåga att framföra fartyget på ett säkert sätt. För att studera detta har en litteraturstudie utförts där vi studerat transportstyrelsens utgivna haverirapporter samt forskning inom områdena om mänskliga faktorn, fartygsorganisation och sjösäkerhet.   Det som framkommit under arbetets gång är att manskapet ombord de senaste åren allt mer har fått ge vika till förmån för teknik men då reglerna inte följt med i tempot kan det vara så att fartyg i dag inte uppfyller kraven för minimibesättning. Även om vi kan påvisa att befälen har en hög arbetsbelastning går det inte att se varför de handlat som de gjort vid olyckstillfällena. Vidare har konstaterats att det finns utrymme för framtida forskning i ämnet där man exempelvis kan se över hur haverirapporterna är utformade. / This work answered the question about how the situation is today on the bridge for the nautical officers and how the amount of rules and guidelines that exists affects his ability to manoeuvre the ship in a safe way. To study this we have performed a literature study where we studied the Swedish Transport Agency’s published accident investigation reports as well as research in the fields of human error, shipping organization and safety at sea.   Our findings show that the crew on board has been reduced due to technical advancement. However, the rules have not followed the same pace and therefore today’s ships may not fulfil the requirements of minimum manning on board. Although we can tell that the officers have an increased workload we cannot see why they have acted as they did at the time of the accidents. It can also be shown that there is a need for future research where, for example, studies on how the accident investigation reports are designed.

Förstudiens syfte var att kartlägga användarbehov kring ROE inom svenska Marinen och ta fram stöd och hjälpmedel för att underlätta ROE-arbetet. I kartläggningen medverkade personal från olika staber, förband och skolor inom Försvarsmakten. Flertalet deltog sedan också i det iterativa utvecklingsarbetet. Tre användargrupper urskiljdes; Stabs- och fartygspersonal samt personal under utbildning. Några av de svårigheter som identifierades; Tolkningsskiljaktigheter mellan stabs- och fartygspersonal. ROE-arbetet ger ett administrativt merjobb för stabs- och fartygspersonal. Det finns inte tid eller resurser att öva ROE på ett realistiskt sätt med lämplig upptrappning av hotnivå. Det bedrivs ingen specifik ROE-utbildning vid Försvarsmaktens skolor eller centra. Utvecklingsarbetet bedrevs parallellt med kartläggningen och involverade stabs- och fartygspersonal. Efter ett antal utvärderingar med användare kunde tre koncept för stöd och hjälpmedel ges. För att öka förståelsen och visualisera koncepten har tre demonstratorer skapats. Koncepten har fått arbetsnamnen; - ADMIN - Administrativt stöd för ROE-hantering. - FARTYG - Utbildningshjälpmedel för fartygsledning och eventuellt skolor. - STAB - Stöd för framtagning av ROE-profil. Författarna rekommenderar FOI att fortsätta utreda ROE-arbetet inom Försvarmakten och även internationellt samt vidareutveckla de tre föreslagna koncepten. För att skapa en gemensam grund för sin personal bör Försvarsmakten hålla seminarium och utbildning inom ROE och tydligare definiera ansvarsförhållanden och begrepp.

Stereotypical gender roles have probably existed as long as human culture and are such a natural part if our lives that we barely take notice of them. Nevertheless, images of what we perceive as typically masculine and feminine in appearance and behavior depend on the individual’s perception. Within each gender one can find different stereotypes. A commonly assumed idea is that men are hard tough, while women are soft and vulnerable. I find it interesting hoe stereotypes function and how they are preserved almost without our awareness. Once I started reading and researching the topic of stereotypes it became clear to me that literature contains many stereotypes. The intension of this essay is to critically examine the stereotypical gender roles in the play A Streetcar Named Desire, written by Tennessee Williams in 1947. It is remarkable how the author portrays the three main characters: Stanley, Stella and Blanche. The sharp contracts and the dynamics between them are fascinating.

none

Mining association rules, means a process of nontrivial extraction of implicit, previously and potentially useful information from data in databases. Mining maximal large itemsets is a further work of mining association rules, which aims to find the set of all subsets of large (frequent) itemsets that could be representative of all large itemsets. Previous algorithms to mining maximal large itemsets can be classified into two approaches: exhausted and shortcut. The shortcut approach could generate smaller number of candidate itemsets than the exhausted approach, resulting in better performance in terms of time and storage space. On the other hand, when updates to the transaction databases occur, one possible approach is to re-run the mining algorithm on the whole database. The other approach is incremental mining, which aims for efficient maintenance of discovered association rules without re-running the mining algorithms. However, previous algorithms for mining maximal large itemsets based on the shortcut approach can not support incremental mining for mining maximal large itemsets. While the algorithms for incremental mining, {it e.g.}, the SWF algorithm, could not efficiently support mining maximal large itemsets, since it is based on the exhausted approach. Therefore, in this thesis, we focus on the design of an algorithm which could provide good performance for both mining maximal itemsets and incremental mining. Based on some observations, for example, ``{it if an itemset is large, all its subsets must be large; therefore, those subsets need not to be examined further}", we propose a Sliding-Window approach, the SWMax algorithm, for efficiently mining maximal large itemsets and incremental mining. Our SWMax algorithm is a two-passes partition-based approach. We will find all candidate 1-itemsets ($C_1$), candidate 3-itemsets ($C_3$), large 1-itemsets ($L_1$), and large 3-itemsets ($L_3$) in the first pass. We generate the virtual maximal large itemsets after the first pass. Then, we use $L_1$ to generate $C_2$, use $L_3$ to generate $C_4$, use $C_4$ to generate $C_5$, until there is no $C_k$ generated. In the second pass, we use the virtual maximal large itemsets to prune $C_k$, and decide the maximal large itemsets. For incremental mining, we consider two cases: (1) data insertion, (2) data deletion. Both in Case 1 and Case 2, if an itemset with size equal to 1 is not large in the original database, it could not be found in the updated database based on the SWF algorithm. That is, a missing case could occur in the incremental mining process of the SWF algorithm, because the SWF algorithm only keeps the $C_2$ information. While our SWMax algorithm could support incremental mining correctly, since $C_1$ and $C_3$ are maintained in our algorithm. We generate some synthetic databases to simulate the real transaction databases in our simulation. From our simulation, the results show that our SWMax algorithm could generate fewer number of candidates and needs less time than the SWF algorithm.

Targeting a small portion of customers for advertising has long been recognized by businesses. In this thesis we proposed a novel approach to promoting products with no prior transaction records. This approach starts with discovering the GP-association rules between customer types and product genres that had occurred frequently in transaction records. Customers are characterized by demographic attributes, some of these attributes have concept hierarchies and products can be generalized through some product taxonomy. Based on GP-association rules set, we developed a comprehensive algorithm to locating a short list of prospective customers for a given promotion product. The new approach was evaluated using the patron¡¦s circulation data from OPAC system of our university library. We measured the accuracy of estimated method and the effectiveness of targeted advertising in different parameters. The result shows that our approach achieved higher accuracy and effectiveness than other methods.

Classification, an important problem of data mining, is one of useful techniques for prediction. The goal of the classification problem is to construct a classifier from a given database for training, and to predict new data with the unknown class. Classification has been widely applied to many areas, such as medical diagnosis and weather prediction. The decision tree is the most popular model among classifiers, since it can generate understandable rules and perform classification without requiring any computation. However, a major drawback of the decision tree model is that it only examines a single attribute at a time. In the real world, attributes in some databases are dependent on each other. Thus, we may improve the accuracy of the decision tree by discovering the correlation between attributes. The CAM method applies the method of mining association rules, like the Apriori method, for discovering the attribute dependence. However, traditional methods for mining association rules are inefficient in the classification applications and could have five problems: (1) the combinatorial explosion problem, (2) invalid candidates, (3) unsuitable minimal support, (4) the ignored meaningful class values, and (5) itemsets without class data. The FP-growth avoids the first two problems. However, it is still suffered from the remaining three problems. Moreover, one more problem occurs: Unnecessary nodes for the classification problem which make the FP-tree incompact and huge. Furthermore, the workload of the CAM method is expensive due to too many times of database scanning, and the attribute combination problem causes some misclassification. Therefore, in this thesis, we present an efficient and accurate decision tree building method which resolves the above six problems and reduces the overhead of database scanning in the CAM method. We build a structure named class-rooted FP-tree which is a tree similar to the FP-tree, except the root of the tree is always a class item. Instead of using a static minimal support applied in the FP-growth method, we decide the minimal support dynamically, which can avoid some misjudgement of large itemsets used for the classification problem. In the decision tree building phase, we provide a pruning strategy that can reduce the times of database scanning. We also solve the attribute combination problem in the CAM method and improve the accuracy. From our simulation, we show that the performance of the proposed class-rooted FP-tree mining method is better than that of other mining association rule methods in terms of storage usage. Our simulation also shows the performance improvement of our method in terms of the times of database scanning and classification accuracy as compared with the CAM method. Therefore, the mining strategy of our proposed method is applicable to any method for building decision tree, and provides high accuracy in the real world.

In this paper, the heuristic rules are proposed to derive the rephasing strategy of laterals and distribution transformers to improve the three phase unbalance of distribution systems. The distribution feeder network has been obtained by retrieving the attribute data of distribution components from the database of outage management system (OMS) in Taipower. The topology process and node reduction have also been executed to identify the network configuration and to prepare the input data for load flow analysis. With the monthly energy consumption of customers served by each transformer, which has been retrieved from the Customer Information System (CIS), the hourly loading of each distribution transformer can be derived. By performing the three phase load flow analysis, the three phase currents and neutral current of each primary trunk line section and each lateral can be calculated. The heuristic rule is employed to determine the phase adjustment strategy laterals and distribution transformers for rephasing to achieve three phase balancing. In order to demonstrate the effectiveness of the proposed methodology for three phase balancing, two practical distribution feeders in Taipower Fengshan District are selected for simulation. After rephasing the distribution transformers and laterals proposed by this paper, the three phase currents and netural of the test feeders have been collected. By companing to the neutral current before rephasing, it is found that the neutral current of test feeders have been reduced significantly and there phase balancing has been obtained by executing the proposed strategy derived using the heuristic rule.

No description available.

None