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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 280, in _generate_tables
                  df = pandas_read_json(f)
                       ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 34, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 791, in read_json
                  json_reader = JsonReader(
                                ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 905, in __init__
                  self.data = self._preprocess_data(data)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
                  data = data.read()
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
                  out = read(*args, **kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^
                File "<frozen codecs>", line 322, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode bytes in position 15-16: invalid continuation byte
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 283, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 246, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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A unified deep learning framework for high-performance RUL prediction

BSEBench status: raw_mirror_pending_validation

This dataset repository is a raw mirror of the Mendeley Data dataset "A unified deep learning framework for high-performance RUL prediction" by Yong Jin Jeong.

Source: Mendeley Data
Source URL: https://data.mendeley.com/datasets/npjy7vdgky/1
DOI: 10.17632/npjy7vdgky.1
Published: 2025-07-21
Institution: Seoul National University
License: CC BY 4.0
Mirror download date: 2026-05-08T10:05:56Z

Contents

  • source/Battery raw data.zip: original source archive downloaded from the official Mendeley public file endpoint.
  • BSEBENCH_SOURCE.json: machine-readable provenance and verification metadata.
  • SHA256SUMS.txt: SHA-256 checksum for the mirrored source archive.

The Mendeley source describes NCA/Gr-Si Sony 18650 VTC6 and Samsung SDI INR18650 25R battery cycling datasets with Markov user-profile charging protocols, periodic 0.2C capacity checks, SOH/RUL labels, and voltage/current/capacity measurements recorded every 10 seconds.

Provenance

The source page was checked before upload and verified to list:

  • Title: "A unified deep learning framework for high-performance RUL prediction"
  • DOI: 10.17632/npjy7vdgky.1
  • License: CC BY 4.0
  • Institution: Seoul National University

The file was downloaded from the official Mendeley public API file URL linked from the source page metadata. No data files were transformed or extracted for this mirror.

Citation

Jeong, Yong Jin (2025), "A unified deep learning framework for high-performance RUL prediction", Mendeley Data, V1, doi: 10.17632/npjy7vdgky.1.

Validation Status

This is a raw mirror pending BSEBench validation. No benchmark conclusions, performance claims, or leaderboard claims are made in this repository.

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