Fair referee assignments for professional football leagues

Assignment of referees to football games is an important problem faced in professional football leagues. Despite its importance, the problem has received limited academic attention. This paper presents a model and analysis of the problem for fair referee assignments, and develops a constructive heuristic and a local search procedure for its solution. Results from an extensive computational study show that the methods are effective in solving the problem in a second of computation time and yielding an excellent solution quality.     

Searching for Complex Human Activities with No Visual Examples

We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach is based on units of activity at segments of the body, that can be composed across space and across the body to produce complex queries. The presence of search units is inferred automatically by tracking the body, lifting the tracks to 3D and comparing to models trained using motion capture data. Our models of short time scale limb behaviour are built using labelled motion capture set. We show results for a large range of queries applied to a collection of complex motion and activity. We compare with discriminative methods applied to tracker data; our method offers significantly improved performance. We show experimental evidence that our method is robust to view direction and is unaffected by some important changes of clothing.     

Interpretation of MR images using self-organizing maps and knowledge-based expert systems

A new image segmentation system is presented to automatically segment and label brain magnetic resonance (MR) images to show normal and abnormal brain tissues using self-organizing maps (SOM) and knowledge-based expert systems. Elements of a feature vector are formed by image intensities, first-order features, texture features extracted from gray-level co-occurrence matrix and multiscale features. This feature vector is used as an input to the SOM. SOM is used to over segment images and a knowledge-based expert system is used to join and label the segments. Spatial distributions of segments extracted from the SOM are also considered as well as gray level properties. Segments are labeled as background, skull, white matter, gray matter, cerebrospinal fluid (CSF) and suspicious regions.     

Neural network and fuzzy logic-based hybrid attitude controller designs of a fixed-wing UAV

Neural Computing and Applications - In this paper, a mini unmanned aerial vehicle (UAV) is planned to be used in applications such as spraying pesticide and weed control in agricultural areas....     

Atmospheric and anthropogenic deterioration of the İvriz rock monument: Ereğli-Konya,Central Anatolia,Turkey

Bulletin of Engineering Geology and the Environment - The aim of this study is to determine the extent of deterioration of the limestone on which the İvriz rock monument is engraved. This...     

Model Predictive Control Coupled with Artificial Intelligence for Eddy Current Dynamometers

The recent studies on Artificial Intelligence (AI) accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adaptiveness and fast responding features. The Model Predictive Control (MPC) technique is a widely used, safe and reliable control method based on constraints. On the other hand, the Eddy Current dynamometers are highly nonlinear braking systems whose performance parameters are related to many processes related variables. This study is based on an adaptive model predictive control that utilizes selected AI methods. The presented approach presents an updated the mathematical model of an Eddy Current Dynamometer based on experimentally obtained system operational data. Finally, the comparison of AI methods and related learning performances based on the assessment technique of mean absolute percentage error (MAPE) issues are discussed. The results indicate that Single Hidden Layer Neural Network (SHLNN), General Regression Neural Network (GRNN), Radial Basis Network (RBNN), Neuro Fuzzy Network (ANFIS) coupled MPC have quite satisfying performances. The presented results indicate that, amongst them, GRNN appears to provide the best performance.     

Increasing the conversion fraction of sulfur to sodium thiosulfate with the ultrasound energy

The usage of ultrasound has gained popularity in the recent years. Ultrasonic processing means blasting liquids, usually water, with very intense sound at high frequency, producing very well mixed powerful chemical and physical reactions. This paper deals with the investigation of the effect of ultrasonic energy on the conversion fraction of sulfur in the production reaction of sodium thiosulfate which was obtained from sulfur and Na₂SO₃ solution. Concentration of Na₂SO₃ solution parameter was chosen as the constant parameter. The experiments were performed with various amplitudes of ultrasound power and in the absence and presence of ultrasound energy in various temperatures with various particle sizes. The results indicate that the conversion fraction values increase in the presence of ultrasound energy and increase at high amplitude values.     

Palladium-Catalyzed Suzuki–Miyaura Reaction Using Saturated N-Heterocarbene Ligands

Recent studies have pointed to the heptamethylbenzenium cation as a prominent intermediate in the methanol to hydrocarbons (MTH) reaction. The reactions of the heptamethylbenzenium cation in a H-beta zeolite was studied at 300 °C by feeding its corresponding base (WHSV = 0.4 h^?1). The reactant was converted completely into aliphatic products, polymethylbenzenes and coke under the employed conditions. The results testify that the proposed reaction intermediate yields the same product spectrum as methanol. The composition of the material retained in the catalyst micropores after 15 min of reaction was determined by dissolving the catalyst in 15% HF. Polymethylated benzenes (predominantly pentamethylbenzene), dihydro-trimethylnaphthalenes, and hexamethylnaphthalene were the major components. The results also support the idea that the lowest naphthalene derivative is formed from the heptamethylbenzenium cation by a molecular rearrangement. Hence, the heptamethylbenzenium cation is inherently linked to both product formation and catalyst deactivation in the MTH reaction.     

Realizations of mutative 4-ports and their applications to memstor simulations

In this paper, in addition to the universal 4-port mutator circuit introduced earlier with an adder and a subtractor block, two more 4-port mutator circuits, one with plus type (CCII+) and minus type current conveyors (CCII?), the other with a plus type current conveyor (CCII+) and one minus type current follower (CF?) are presented, their port relation matrix and their realization of different memstors are tabulated. How the transfer characteristics of the ideal mutative 4-ports with respect to frequency hold is verified using their transistor level simulations. By terminating properly two ports of the mutative 4-port simulations of a memristor with three different mutators, of a meminductor and of a memcapacitor are presented and compared also with some mutators existing in the literature.