Used Car Price Prediction Using Machine Learning
Bibliographic record
Abstract
The Stingray or IMSI-catcher is a surveillance device for cellular phones that was initially developed by the Harris Corporation for military use.Nowadays, various local and state law enforcement agencies across countries such as Canada, the United States, and the United Kingdom use similar devices widely.The term Stingray has also become a general term for this type of device.The IMSI catcher has two modes of operation-active and passive.In the active mode, the device pretends to be a cell tower, tricking all nearby mobile phones and cellular devices to connect to it.It can be mounted on vehicles, low flying airplanes and helicopters, UAVs, etc.It broadcasts signals that seem stronger than the cell tower, and thus, it forces each compatible cellular device to disconnect from its service provider (e.g., Jio, BSNL, etc.) and establish a new connection with the device. Cellular communications protocols require mobile phones and cellular devices to connect to the strongest signal. We have used a Software Defined Radio (SDR) to replicate the Stingray device manufactured by the Harris Corporation. Although this device has a shorter range, it can still track the IMSI of all cellular devices around it. This project also demonstrates how fragile our privacy is concerning our deviI. INTRODUCTION Cyber-Surveillance has been increasingly relied on by governments to carry out certain administrative tasks in the health, welfare, education and civil security sectors.Businesses keen to protect certain information or to monitor the behavior of their employees or clients have also engaged in "cyber-surveillance" and corporate surveillance.Civil society and citizens' organizations may also use information technologies to monitor the words and deeds of authorities or businesses as part of strategies to publicly denounce conduct they deem to be unacceptable.Finally, delinquents and criminal groups may turn to cyber-surveillance in the pursuit of their objectives.The stingray device can be extremely beneficial to the government if used for the intended purpose, i.e. to hunt for criminals and national threats.If an approximate location of the threat is known, a stingray can be deployed near the region.The stingray will provide the phone numbers present in a particular radius around it.An even more advanced version can intercept the calls and messages being sent through the target's device.The motivation for this project was taken from the highly regarded Netflix documentary, "Web of Make Believe."II.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".