The dataset contains the medical ultrasound imaging measurement data. The phantom dataset was measured by using three different imaging methods. These methods are diverging wave imaging (DWI), synthetic transmit aperture imaging (STAI), and conventional single-focused phased array imaging (CSFI). We used a Digital Phased Array System (DiPhAS, Fraunhofer IBMT, Frankfurt, Germany) for data acquisition. We also used 128 elements phased array transducer (Fraunhofer IBMT, Frankfurt, Germany) operating at a 7.5 MHz center frequency.

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We applied appropriate time delays to each transducer array element to obtain divergent wavefronts in DWI. We used 8-bit complementary Golay sequences (CGSs) with different bit lengths (0.5, 1, 1.5, and 2-cycle/bit) to code the transmitted signal and binary phase-shift keying for modulation in DWI. In CSFI measurements, we transmitted a 1-cycle pulse. We used 181 steered and focused beam transmissions to construct the image scan lines. The steering angle is between -45° and 45°, with 0.5° intervals. We focused each transmission at 40 mm away from the transducer array center. All array elements were used in each transmit and receive event. In STAI measurements, we transmitted a 2-cycle pulse. We transmitted from an array element at a time, successively. We measured STAI data from all transmit/receive element pairs. We measured the noise in each channel without any transmission. The array was kept acoustically in contact with the phantom surface to ensure the noise contribution of the radiation resistance. We recorded 13 separate measurements, where the transducer displaced by about 1 mm in each measurement. We also performed measurements in freshwater. We immersed a highly reflective material, a steel plate, in the water at a 5 cm depth (approximately). We fired the 64th element of the transducer and received the reflecting echoes from all elements. Do not hesitate to contact the author (yasin.kumru@bilkent.edu.tr) if you have any questions about the dataset.

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This is the result found by multi-tree-search.</p>

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we present a new conversational database that we have created and made publically available, namely ScenarioSA, for interactive sentiment analysis. We manually label 2,214 multi-turn English conversations collected from various websites that provide online communication services.

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The dataset is the result of exhaustive search of primary extended 1-perfect unitrades in the 10-cube, or, equivalently, triangle-free 5-regular connected induced subgraphs of the halved 10-cube. We list representatives of all the 38 equivalence classes.

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In the file "uni10bin.txt", each unitrade C is represented by a line where the words from C are separated by comma.

The file "uni10dec.txt" contains the decimal representation of the same words.

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