“For example, a user can send type a text message using, for example, Short Message Service-Point to Point (SMS-PP) protocol as defined in GSM recommendation 03.40 where messages are sent via a store-and forward mechanism to a Short Message Service Center (SMSC), which will attempt to send the message to the recipient and possibly retry if the user is not reachable at a given moment. Therefore, SMS-PP requires the use of a backend server to provide the necessary support for transmission of data between sender and receiver.”
“In this way, a sender can select that data which he/she desires to send to a receiver unit using by first converting the data into an appropriate vocal/voice format which is then forwarded to a receiver unit by way of the voice channel,” Apple said. “Once received at the receiver unit, the vocalized data can be converted to an audio signal, which is then output by way of an audio output device (such as a speaker, earphone, etc.).”
The filing suggests that a sender would be able to vocalize any textual data on their display screen (such as a phone number) in order to pass it by way of a voice channel to another iPhone or any number of other iPhones or compatible personal communication devices. Once received by the recipient, processing of the vocalized data would be performed based upon a prompted user request or based upon a pre-selected protocol.
“For example, once received [by an iPhone], the vocalized phone number can be passed to an audio output device that (in the case of a speaker) generates an audible rendition of the vocalized phone number,” Apple wrote. “In another case, the vocalized phone number is forwarded to a voice mail server where the receiver records the vocalized phone number as a voice mail message for subsequent playback.”
To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML HTML
in full HyperText Markup Language
Artificial immune system (AIS) is an adaptive system An adaptive system is a system that is able to adapt its behavior according to changes in its environment or in parts of the system itself. A human being, for instance, is certainly an adaptive system; so are organizations and families. inspired from immunology immunology, branch of medicine that studies the response of organisms to foreign substances, e.g., viruses, bacteria, and bacterial toxins (see immunity). Immunologists study the tissues and organs of the immune system (bone marrow, spleen, tonsils, thymus, lymphatic and immune phenomena, to implement the immune model, principles, and functions through humans or computers (Cai & Gong, 2002). This technology has recently been advancing rapidly, and has shown the strong robustness for processing information and powerful ability to solve complex problems. The research evolved from immunology in the middle 1980s. In 1990, Bersini first used immune algorithms to solve problems in the adaptive network (Bersini & Varela. 1991). Meanwhile, Ishida (1990) used the artificial immune system to solve the fault diagnosis problem of the sensor network A low-speed industrial network that is used to connect sensors to actuators. A sensor network implies limited or no controller functions. Multiple sensor networks may be coupled to form device networks. See industrial control network. . In 1994, Forrest, Perelson, Allen, and Cherukuri first applied immune algorithms to computer security and virus detection (Dasgupta & Forrest, 1998). In 1995, Cooke and Hunt began to apply immune algorithms to the machine learning field. In 2002, Gong and Cai first proposed the multi-dimension immune network, used the immune mechanism to solve the security problem of the education network, and investigated the relations between robustness and immunity, then Gong (2003) investigated the multi-dimension education immune agent in his master thesis, and discussed how to use the immune computation techniques to build a new e-learning system. Recently, AIS is regarded as a new and good technique to solve web problems, like network security and fault diagnosis (Castro & Timmis, 2002).
In Figure 1, the communication interface is an important part of the common module for the tri-dimension e-learning agent. Typing, text, symbolic language (1) A programming language that uses symbols, or mnemonics, for expressing operations and operands. All modern programming languages are symbolic languages.
(2) A language that manipulates symbols rather than numbers. See list processing. , and instructing language are valuable for the communication, which is composed of seven processes:
1. Intention: the teacher module decides what to teach students.
2. Generation: the teacher module decides what to talk to the student module with the standard instructing language.
4. Perception: for sound media, the perception is phonic phon·ic
Of, relating to, or having the nature of sound, especially speech sounds.
pertaining to the voice. recognition; for print media, the perception is optical recognition.
[FIGURE 1 OMITTED]
5. Analysis: it consists of sentence understanding and semantic understanding.
6. Optimization: when a talk has more than one meaning, select one as the optimal solution to apply to the education agent.
7. Synthesis: the student module processes instructions with all kinds of factors.
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After the e-learning agent receives the virus alert, its immune computing module is activated. Then the e-learning agent will communicate with the core of immune computing. The e-learning agent has the following characteristics:
1. Immunity and robustness: there are often some viruses in the e-learning web, and the immune agent is required to resist the viruses. So robustness can be kept in the crucial parts of the e-learning web.
2. Virus detection: for a fault-tolerant architecture virus detection is a critical process. Most sophisticated recovery methods are only as good as the virus detection scheme that initiates their operations (Bradley & Tyrrell, 2002; Castro & Zuben, 2002). Virus detection is the process of scanning the file system and finding the malicious programs residing in the file system. File-based virus detection can be parallel.
3. Evolution: the e-learning web is like a sea of knowledge, the agent is a robot working in the sea, and the programs of the robot contain the intelligence of programmers. When human intelligence of the programmers evolves, the agent also maybe evolves.
4. Distribution and Parallelism. The e-learning web is a large-scaled network, and many agents are required to implement different missions. To increase efficiency, the agents can also be parallel, for example in grids.
5. Security: through the AIS, the e-learning web has better security. When the e-learning web is attacked, the e-learning agent activates its inner immune module, and recursively decreases the damage of the adventitious ADVENTITIOUS, adventitius. From advenio; what comes incidentally; us adventitia bona, goods that, fall to a man otherwise than by inheritance; or adventitia dos, a dowry or portion given by some other friend beside the parent. attack until the e-learning web recovers normal.
Wi-Fi Alliance: Press Releases - 0 views
"Wi-Fi Direct represents a leap forward for our industry. Wi-Fi users worldwide will benefit from a single-technology solution to transfer content and share applications quickly and easily among devices, even when a Wi-Fi access point isn't available," said Wi-Fi Alliance executive director Edgar Figueroa. "The impact is that Wi-Fi will become even more pervasive and useful for consumers and across the enterprise."
The specification targets both consumer electronics and enterprise applications, provides management features for enterprise environments, and includes WPA2® security. Devices that support the specification will be able to discover one another and advertise available services. Wi-Fi CERTIFIED Wi-Fi Direct devices will support typical Wi-Fi ranges and the same data rates as can be achieved with an infrastructure connection, so devices can connect from across a home or office and conduct bandwidth-hungry tasks with ease.
7away for voice or SMS.
- The primary objective of this system would be to allow authorities or officials to broadcast a text message to the public, even in the absence of electricity, radio transmitters, or cell phone towers. It's not designed for a member of the public to send a message to call for help, although I have some ideas about how you could implement that in a future phase.
- Authentication: you would probably want to use some form of public key cryptography, so that handsets could verify that the text message package was officially authenticated, and that eavesdroppers couldn't learn enough to spoof an official message. My limited understanding of PKC says that this is possible.
- Here's how a message would be sent. In an emergency, an official would use a specially-programmed handset (or one into which an authentication code could be entered) and would author and send a special emergency message. The message would be broadcast on the special "listen" frequency that cell phones use to receive messages from a cell network tower. The broadcast would be repeated something like every minute for 10 minutes (network engineers can figure out what a good rate would be).
- Ordinary handsets would be listening in to the tower frequency even if they aren't in range of a working tower. (I'm not sure how exactly handsets operate when towers are down or out of range, but presumably they are least hunting at regular intervals. Perhaps they would have to be programmed to be listening constantly for a special message, which might cause more battery drain; I'm not sure.) When the handset receives and authenticates the special text message, it displays it and then rebroadcasts it every minute for 10 minutes.
- You would probably use message IDs and a rate limiter to avoid overwhelming transmission or unnecessarily repeating a message.
- The net result is that if your handset is within a few miles of another handset, it should receive the emergency message within minutes, even if there is no power, no cell phone towers, etc.