Varför nationellt ämnesprov skolår 5?

Detta arbete har syftet att undersöka varför det nationella ämnesprovet (Np) i skolår 5 genomförs. För att undersöka den frågan har vi tagit del av information och åsikter från Skolverket samt intervjuat 16 personer som arbetar i eller för skolan i en av Sveriges kommuner. Informationsinsamlandet består bland annat av två rapporter (böcker) från Skolverket. Intervjuerna är basen för denna undersökning då det finns lite skrivet om detta ämne. Av de resultat vi redovisar kring varför det nationella ämnesprovet i skolår 5 genomförs har vi valt att utförligare presentera de viktigaste av dem, vilka är; Information/Kommunikation, Likvärdighet, Lärarunderlag och Resursfördelning.Denna undersökning visar att nationella ämnesprovet i skolår 5 är väldigt uppskattat bland lärarna, provet hjälper läraren att finna kvaliteter och brister hos elever och det ger dem även ett bra underlag för att följa och dokumentera elevernas utveckling. Många lärare framhåller samtidigt att provet är krävande vad det gäller planering och genomförande. Av personal på skolor i den aktuella kommunen efterfrågades att det nationella ämnesprovet skall ligga till grund för resursfördelningen, vilket den inte gör, idag. Resultatet av denna undersökning visar på stora brister i information och kommunikation mellan de olika nivåerna i skolan. Det vill säga från Barn- och skolnämnd till lärare, via skolområdeschefer och rektorer. Vidare visar resultatet att många lärare väljer att plocka bort vissa delar ur det nationella ämnesprovet i skolår 5, vilket inte är tillåtet enligt den aktuella kommunens bestämmelser.

University Scheduling using Genetic Algorithm

The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

BEE COLONIES APPLIED TO MULTIPROCESSOR SCHEDULING

In order to achieve the high performance, we need to have an efficient scheduling of a parallelprogram onto the processors in multiprocessor systems that minimizes the entire executiontime. This problem of multiprocessor scheduling can be stated as finding a schedule for ageneral task graph to be executed on a multiprocessor system so that the schedule length can be minimize [10]. This scheduling problem is known to be NP- Hard.In multi processor task scheduling, we have a number of CPU’s on which a number of tasksare to be scheduled that the program’s execution time is minimized. According to [10], thetasks scheduling problem is a key factor for a parallel multiprocessor system to gain betterperformance. A task can be partitioned into a group of subtasks and represented as a DAG(Directed Acyclic Graph), so the problem can be stated as finding a schedule for a DAG to beexecuted in a parallel multiprocessor system so that the schedule can be minimized. Thishelps to reduce processing time and increase processor utilization. The aim of this thesis workis to check and compare the results obtained by Bee Colony algorithm with already generatedbest known results in multi processor task scheduling domain.

Use Multilevel Graph Partitioning Scheme to solve traveling salesman problem

The traveling salesman problem is although looking very simple problem but it is an important combinatorial problem. In this thesis I have tried to find the shortest distance tour in which each city is visited exactly one time and return to the starting city. I have tried to solve traveling salesman problem using multilevel graph partitioning approach.Although traveling salesman problem itself very difficult as this problem is belong to the NP-Complete problems but I have tried my best to solve this problem using multilevel graph partitioning it also belong to the NP-Complete problems. I have solved this thesis by using the k-mean partitioning algorithm which divides the problem into multiple partitions and solving each partition separately and its solution is used to improve the overall tour by applying Lin Kernighan algorithm on it. Through all this I got optimal solution which proofs that solving traveling salesman problem through graph partition scheme is good for this NP-Problem and through this we can solved this intractable problem within few minutes.Keywords: Graph Partitioning Scheme, Traveling Salesman Problem.

Optimization of cable cycles : a trade-off between reliability and cost

This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.