Implementing Li-Fi protocols
Bibliographic record
Abstract
LI-FI is the latest technology in the Field of wireless communication. Nowadays many people are using internet to fulfill most of their tasks through wired or wireless networks. As the number of users is increasing, the rate of data transmission in the wireless network automatically decreases. WI-FI provides us speeds near about 150mbps as per IEEE 802.11n but still it is not able to fulfill the requirement of the user because of such reason we are introducing the LI-FI. According to the German physicist Harald Hass, LI-FI provides much higher data transmission speeds (10gbps and max up to 224gbps per second) by using visible light. In this condition the LI-FI/WI-FI is analyzed. It’s the same idea band behind infrared remote controls but is more powerful. Haas says his invention, which he calls D-LIGHT, can produce data rates faster than our average broadband connection. Nowadays, parking vehicles is one of the most tedious jobs. Hence, in order to solve this problem, a reliable system is proposed. Our system solves the current parking problems by offering guaranteed parking reservations with the lowest possible cost and searching time for drivers and the highest revenue and resource utilization for parking managers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".