We present the first comparative study of two fundamentally distinct feature extraction techniques: Histogram of Oriented Gradients (HOG) and Topological Data Analysis (TDA), for medical image classification using retinal fundus images. HOG captures local texture and edge patterns through gradient orientation histograms, while TDA, using cubical persistent homology, extracts high-level topological signatures that reflect the global structure of pixel intensities. We evaluate both methods on the large APTOS dataset for two classification tasks: binary detection (normal versus diabetic retinopathy) and five-class diabetic retinopathy severity grading. From each image, we extract 26244 HOG features and 800 TDA features, using them independently to train seven classical machine learning models with 10-fold cross-validation. XGBoost achieved the best performance in both cases: 94.29 percent accuracy (HOG) and 94.18 percent (TDA) on the binary task; 74.41 percent (HOG) and 74.69 percent (TDA) on the multi-class task. Our results show that both methods offer competitive performance but encode different structural aspects of the images. This is the first work to benchmark gradient-based and topological features on retinal imagery. The techniques are interpretable, applicable to other medical imaging domains, and suitable for integration into deep learning pipelines.

A large number of robotic and human-assisted missions to the Moon and Mars are forecast. NASA's efforts to learn about the geology and makeup of these celestial bodies rely heavily on the use of robotic arms. The safety and redundancy aspects will be crucial when humans will be working alongside the robotic explorers. Additionally, robotic arms are crucial to satellite servicing and planned orbit debris mitigation missions. The goal of this work is to create a custom Computer Vision (CV) based Artificial Neural Network (ANN) that would be able to rapidly identify the posture of a 7 Degree of Freedom (DoF) robotic arm from a single (RGB-D) image - just like humans can easily identify if an arm is pointing in some general direction. The Sawyer robotic arm is used for developing and training this intelligent algorithm. Since Sawyer's joint space spans 7 dimensions, it is an insurmountable task to cover the entire joint configuration space. In this work, orthogonal arrays are used, similar to the Taguchi method, to efficiently span the joint space with the minimal number of training images. This ``optimally'' generated database is used to train the custom ANN and its degree of accuracy is on average equal to twice the smallest joint displacement step used for database generation. A pre-trained ANN will be useful for estimating the postures of robotic manipulators used on space stations, spacecraft, and rovers as an auxiliary tool or for contingency plans.

Sign up to receive the Future Tense newsletter every other Saturday. I showed up for my first "Flow sesh" feeling sluggish. It was 6 p.m. on a Monday, and I had promised myself I was going to use the time to try to make headway on a writing project I had been putting off all day. But I was also pretty skeptical. Flow Club, a platform for virtual coworking sessions, promises to allow members to "Feel good getting work done."

Less than a week after the last drops of Hurricane Harvey fell, Houston is just beginning to assess the damage. At least 46 people have died. More than 30,000 houses are flooded and as many as a million vehicles waterlogged. Early estimates suggest the hurricane has inflicted $120 billion in damage on the region, making it the most expensive natural disaster in the country's history. "This is going to be a massive, massive cleanup process," Texas governor Greg Abbott told ABC's Good Morning America on Friday.

Computer pioneer Alan Kotok, an MIT alumnus who helped create both the first video game and the gaming joystick, died of a heart attack in his home in Cambridge, Mass., on Friday, May 26. A native of Philadelphia, he was 64. Kotok (S.B. 1962) entered MIT at age 16 and became swiftly involved in developing chess-playing computer programs, designing new systems for MIT's Tech Model Railroad and, with a group of friends, coming up with their original video game, Spacewar. Tim Berners-Lee, founder and director of the World Wide Web Consortium (W3C), which is housed in MIT's Computer Science and Artificial Intelligence Laboratory, described Kotok as "one of the early wise men of computer science." The unflappable Kotok was "not only technically adept well beyond the norm, but also possessed a childlike delight in all things ingenious or intriguing. Wit, wisdom and sheer human warmth defined him, yet he commanded total respect. He would humbly take on anything which simply needed doing," Berners-Lee said.