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They're only in high school, but Chen Nafshi and Avital Yegudeyev of the ORT school in Holon have already invented a wireless monitor for women in labor that will signal midwives when they are ready to deliver. The clever device won them first prize in the ORTiada competition, which encourages students to be technologically innovative.
One part of the device is a belt worn around the belly that monitors contractions. But unlike conventional monitors, the midwife/nurse doesn't have to be in the room all the time to observe changes. Instead, she holds a wireless receiver and can follow the woman's contractions while working in another room, hurrying over only when the real-time findings tell her she is needed. The receiver shows the frequency and power of contractions, eliminates unimportant information and buzzes when delivery is likely to begin.
The ORT pupils' supervisor, Ruth Kowalsky, thought up the idea after she herself had a difficult delivery, during which the midwife left her alone much of the time. She asked Chen and Avital - the only girls in the electronics/computers biomedical curriculum among 30 boys - to work on the project. They also received help from Giza Venture Capital, which assists the ORTiada, gives advice on projects being developed and will help them turn it into a commercial product. The competition itself was financed by Ella and Yisrael Weissbort. The girls received NIS 4,000 for the first prize and will share it.
Meanwhile, a device that helps the blind use any telephone, developed by students at the ORT College in Kiryat Bialik, won first prize in the college-level ORTiada competition. The developer, Yossi Elharar, will receive NIS 6,500. The electronic system pronounces the digits as they are dialled. If the number is the one sought, it can be dialled by pressing a button.
Dr. Eli Eisenberg, ORT-Israel's deputy director-general and head of its research and development branch, said the competition reflects the educational network's desire to promote technological education as the basis for vocational advancement and economic growth, and of raising young people's awareness of the importance of community involvement.
Using Wikipedia - the free online encyclopedia written and edited by readers in cyberspace - Technion researchers have developed a way to give computers knowledge of the world to help them "think smarter." The new method helps computers make common-sense and broad-based connections between topics just as the human mind does, and to filter e-mail spam, perform Web searches and even conduct intelligence gathering at more sophisticated levels than current programs.
Evgeniy Gabrilovich and Shaul Markovitch of the Technion's computer science faculty presented their findings recently in Hyderabad, India, at the 20th International Joint Conference for Artificial Intelligence. The program devised by the Technion researchers helps computers map single words and larger fragments of text to a database of concepts built from Wikipedia, which has over a million articles in its English-language version. The Wikipedia-based concepts act as "background knowledge" to help computers figure out the meaning of the text entered into a Web search, for instance. How to give computers this deeper knowledge has been a longstanding problem in artificial intelligence, according to Markovitch. "Humans use a significant amount of background knowledge" to understand text, "but we didn't know how to have computers access such knowledge," he said.
Most Web search and e-mail filter programs appear smart by calculating how often certain words appear in two texts, Markovitch explained. "But what is common to all these applications is that the programs that do this don't understand text. They treat text as a collection of words, but don't understand the meaning." This shallow understanding is what makes an e-mail spam filter block all messages containing the word "vitamin," but fail to block messages containing the word "B12." "If the program never saw "B12" before, it's just a word without any meaning. But you would know it's a vitamin," Markovitch said. "With our methodology, however, the computer will use its Wikipedia-based knowledge base to infer that "B12" is strongly associated with the concept of vitamins, and will correctly identify the message as spam," he added.
Computers could look at a chunk of text about Saddam Hussein and weapons of mass destruction and know that it is conceptually related to topics such as the Iraq war and US Senate debates on intelligence - even if those terms do not appear in the original text. The method also helps computers figure out ambiguous terms - deciding, for instance, whether the word "mouse" refers to the computer device or the furry rodent. This can be especially important in translated documents, Markovitch said.
Soon, the Haifa researchers hope to improve their method by adding information from the page links inside Wikipedia articles. They are already pursuing a patent on their work, which they say will be of interest to the intelligence community and Web search engine companies, among others.