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Publikacije (22)

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Emir Cogo, E. Žunić, Admir Besirevic, Sead Delalic, K. Hodzic

This paper presents a data visualization method in 3D space that includes actual positions, volumes and space relations of the chunks of data that are being visualized. Data that is being visualized is real-time information provided by the smart warehouse management system about packages distributed on pallet places within a warehouse. Three different visualizations are shown: qualitative, quantitative and cumulative. The method is graded for the time needed to determine the location of all pallet places that fulfill searched criteria and getting the exact value of searched information for each pallet place. Challenges in presenting this data and interacting with resulting visualizations are discussed. It is concluded that showing actual positions of chunks of data greatly increases the speed of acquiring searched values and positions at the same time for outliers but has issues with clusters and multiple types of queried data.

Irfan Prazina, Edina Kovač, Damir Pozderac, Zerina Ramić, V. Okanović, Emir Cogo

The objective of this paper is to develop the tool which aids the implementation of test specifications for web page layout testing. The tool combines the process of user interface mockup design and implementation of tests. Generated test specifications are verified using two mutation testing operators. Mutation testing was also performed on referent test specifications generated by Galen Framework from goal web page dump files. Tests should detect mutations with a visual change on a web page. Additional image comparison of web page screenshots was performed to determine if there was a visual change. Verification showed that mockup test specifications are less precise than referent test specifications. Nonetheless, they also show fewer false-positive results. It was concluded that generated tests have some limitations, but they can be used as a starting point for writing more precise layout tests.

Emir Cogo, Irfan Prazina, K. Hodzic, Hana Haseljic, S. Rizvić

This article presents an overview of integrability of procedural modeling techniques needed to create a complete virtual city with streets, roads, building lots, exteriors and interiors with arranged furniture. Techniques are distributed into four hierarchies: urban plan, buildings, interior and furniture. Each technique is analyzed from the aspect of control of space definition, style uniformity, automatic interaction with other hierarchies and ability to procedurally generate a result around existing content. Each paper presented in this survey contributes either as a new control feature that has a potential of integrating with other techniques of higher, lower or same level of hierarchy, or as a new important part for creating a complete procedural city from highest to lowest level of hierarchy. The paper is concluded with a discussion of strong links between each area in the chain and important challenges in procedural generation of a complete city.

K. Hodzic, Haris Hasic, Emir Cogo, Ž. Jurić

In modern market it is very important to deliver products to customers fast. That delivery can be on site or to customer's homes. In order to achieve that it is important to have enough goods stored in warehouses and prepared for delivery. It is not a good decision to clutter up warehouses with the goods because space is limited and expensive and it makes it more complicated to collect orders. Those are the reasons why it is important that number of stored goods converge to the exact number of product units that will be ordered in the future. Demand forecasting tries to solve that problem. In this work demand forecasting algorithm based on Long Short-Term Memory recurrent neural network is described and compared with demand forecasting algorithms developed by authors before.

Hana Haseljic, Emir Cogo, Irfan Prazina, Razija Turcinhodzic, E. Buza, Amila Akagić

Multi-, many-core, hybrid processors and parallel programming languages are slowly becoming pervasive in main- stream computing. It is expected that they will affect a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This architectural change has already challenged programmers to efficiently write an application code that can scale over many cores to utilize its computational power. Moreover, many heterogeneous architectures exist today, hence there was an emergent need for a uniform interface to these architectures. Recently, Khronos Group defined the Open Computing Language (OpenCL) for abstracting the underlying hardware, which enables software developers to write a portable code across different shared-memory architectures. In this paper, we introduce a new parallel implementation of one of the fastest image segmentation algorithms known as Simple Linear Iterative Clustering based on OpenCL. We evaluate the effectiveness of this implementation using only multi-core GPCPU. Our implementation is fully compatible with sequential implementation. When the algorithm is executed sequentially it utilizes only 25% of total computational power of a GPCPU for any image resolution, while its modified algorithm is able to utilize close to 100% for high resolution images. The resulting algorithm is up to 5×faster than its sequential counterpart.

This paper presents results of using clustering to improve results of collaborative filtering. Clusters of users are created using friendship links within a social network using Markov Chain Algorithm (MCL). Clusters are then used to make prediction of user choices using item based collaborative filtering with cosine similarity. Using the results from analyzing different cluster sizes, new algorithm was proposed that saves time and memory resources.

E. Bajrami, M. Asic, Emir Cogo, Dino Trnka, N. Nosovic

This paper presents results of performance comparison of simulated annealing algorithm execution on central processing unit (CPU) and Graphics Processing Unit (GPU) that uses Compute Unified Device Architecture (CUDA). Algorithm used for measurement is a meta-heuristic embarrassingly parallel algorithm based on idea of material crystallization process when temperature is being increased to melting point and then decreased to minimum pre-defined value. Algorithm was implemented for quad-core CPU using C and on CUDA enabled GPU using C for CUDA. Execution time was used as criteria for performance comparison and was measured in two scenarios: fixed number of points with number of threads as a parameter and vice versa. Results of measurements were analyzed and presented.

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