cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34808/00nm-jp78
title: The lognormal model of the multipath fading channel

description: The dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The lognormal fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
The term large-scale fading denotes the variations of the mean envelope or mean power of a received signal. Lognormal statistics can describe the slow variation of the mean signal level for outdoor and indoor environments. This phenomenon is referred to as shadowing from terrain, trees and buildings. The lognormal distribution is usually used to represent the long-term characteristics of the mobile radio channel.
The mean envelope level of the received signal is defined by Equation (1). The distribution of this variable, called the lognormal variable, is given by Equations (2). Its expected value and variance are expressed by Equations (3) and (4), respectively. The normal logarithm of the lognormal variable has a normal distribution. The lognormal processes can be derived through the nonlinear transformation of the lognormal variable that specifies the model applied in the MCS (Equations 5).
The MCS provides a general approach to numerically approximating the distribution function for the value of the output quantity Y(t) = f(X) (where Y(t) is a single (scalar) output quantity. X represents the N input quantities (X1(t), . . . ,XN(t))T .
The inputs to the Monte Carlo simulation procedure are:
- the model Y(t) = f(X),
- the probability density functions for input quantities X1(t), . . . ,XN (t),
- the number M of Monte Carlo trials.
X1(t)= N(t) are is Gaussian random process with expected value equal to 0 and variance equal to 1, i.e. N(0,1). The number of Monte Carlo trials is equal to 100 000. The exemplary simulation results obtained with the virtual simulator designed in the LabVIEW programming environment are shown in Fig. 1.
The simulations were carried out for both different standard deviation values and the mean of the normal logarithm of the lognormal variable.
The attached files contain two columns related to fading envelope: the number of samples and the amplitude of fading envelope in [dB] and two columns related to the histogram: the number of bins and the histogram results in percents of total amplitude. Files can be opened in both the LabVIEW software and Windows Office Notepad.
The files are described as follows: MCS_lognorm_the mean value_the standard deviation.
DOI: 10.34808/2m4t-zd14
title: The Rayleigh model of the multipath fading channel

description: The dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The Rayleigh fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
The Rayleigh probability density function is used as a model for short scale fading in a radio channel. The statistics of the received signal in a mobile radio environment is obtained using the scattering model and the assumption of a large number of randomly phased components. The scattering model describes the local statistics of the received signal envelope. The generation of the Rayleigh fading envelope follows from the basic fact, that the envelope of a Gaussian process with independent quadrature and in-phase components, with the mean equal to zero, has a Rayleigh distribution. The probability density function of the Rayleigh envelope is given by Equation (1).
The Rayleigh envelope can be also written down as a function of the in-phase and quadrature components that specifying the model applied in MCS (Equations 2).
The MCS provides a general approach to numerically approximating the distribution function for the value of the output quantity R(t) = f(X) (where R(t) is a single (scalar) output quantity. X represents the N input quantities (X1(t), . . . ,XN(t))T .
The inputs to the Monte Carlo simulation procedure are:
- the model R(t) = f(X),
- the probability density functions for input quantities X1(t), . . . ,XN (t),
- the number M of Monte Carlo trials.
The probability density functions for X=X1(t) Y=X2(t) are a Gaussian type. The number of Monte Carlo trials is equal to 100 000. The exemplary simulation results, obtained with the virtual simulator designed in the LabVIEW programming environment are shown in Fig. 1.
The simulations were carried out for different values of variance of the Rayleigh distribution.
The attached files contain two columns related to a fading envelope: the number of samples and the amplitude of the fading envelope in [dB] and two columns related to the histogram: the number of bins and the histogram results in percents of total amplitude. Files can be opened in both the LabVIEW software and Windows Office Notepad.
The files are described as follows: MCS_Rayleigh_value of the variance.
DOI: 10.34808/jjr7-c153
title: The α-µ  model of the multipath fading channel

description: The dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The envelope of the α-µ fading process is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
The α-µ distribution is used to model a small-scale fading. The fading model for the α-µ distribution studies a signal composed of clusters of multipath waves propagating in a nonhomogeneous environment and explores the nonlinearity of the propagation medium. The resulting envelope is obtained as a nonlinear function of the modulus of the sum of the multipath components.
The envelope R can be expressed by Equation (1). The α-µ probability density function for the envelope R is described by Equation (2).
The α-µ distribution is a general fading distribution, which includes the gamma distribution, Nakagami - m  (for α=2 ), exponential, Weibull (for µ=1), one-sided Gaussian (for α=0.5), Rayleigh (for α=2  and µ=1).
The MCS provides a general approach to numerically approximating the distribution function for the value of the output quantity R(t) = f(X) (where R(t) is a single (scalar) output quantity. X represents the N input quantities (X1(t), . . . ,XN(t))T .
The inputs to the Monte Carlo simulation procedure are:
- the model R(t) = f(X),
- the probability density functions for input quantities X1(t), . . . ,XN (t),
- the number M of Monte Carlo trials.
The probability density functions for Xi(t)=Yi(t) are a Gaussian type. The number of Monte Carlo trials is equal to 100 000. The exemplary simulation results, obtained with the virtual simulator designed in the LabVIEW programming environment are shown in Fig. 1.
The simulations were carried out for different values of the parameter of the α-µ distribution.
The attached files contain two columns related to fading envelope: the number of samples and the amplitude of the fading envelope in [dB] and two columns related to the histogram: the number of bins and the histogram results in percents of total amplitude. Files can be opened in both the LabVIEW software and Windows Office Notepad.
The files are described as follows: MCS_ alfa_mi_α _ n_r0.
DOI: 10.34808/ths2-xr58
title: The Suzuki model of the multipath fading channel

description: The dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The Suzuki fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
The multipath fading is an important problem when multiple, scattered, reflected or diffracted signal components of the transmitted signal arrived at the receiver. The quality of the received signal is affected by multipath fading and by slow variations of the mean signal level due to the shadowing. Several types of statistical models have been used to describe the fading, i.e. a composite distribution. The Suzuki distribution is a mixed distribution that considers the short-term Rayleigh fading conditioned to its mean value, lognormal distributed. Let r is a Rayleigh distributed random variable (RV), and gamma is a lognormal distributed RV. We assume that r and gamma are statistically independent. Then a random variable z defined by the product of r and gamma has the Suzuki distribution. The Suzuki distribution is expressed by Equation (1). The expected value and variance of the Suzuki envelope are given by Equations (2) and (3), respectively. The model of generation of Suzuki envelope is described by Equation (4).
The MCS provides a general approach to numerically approximating the distribution function for the value of the output quantity Y(t) = f(X) (where Y(t) is a single (scalar) output quantity. X represents the N input quantities (X1(t), . . . ,XN(t))T .
The inputs to the Monte Carlo simulation procedure are:
- the model Y(t) = f(X),
- the probability density functions for input quantities X1(t), . . . ,XN (t),
- the number M of Monte Carlo trials.
The probability density functions for X1(t)=X2(t), and X3(t)= N(t) are a Gaussian type. The number of Monte Carlo trials is equal to 100 000. The exemplary simulation results, obtained with the virtual simulator designed in the LabVIEW programming environment are shown in Fig. 1.
The simulations were carried out for the Rayleigh variance equal to 0.5, the mean of the lognormal distribution equal to 1 and different values of the standard deviation of the lognormal distribution.
The attached files contain two columns related to fading envelope: the number of samples and the amplitude of fading envelope in [dB] and two columns related to the histogram: the number of bins and the histogram results in percents of the total amplitude. Files can be opened in both the LabVIEW software and Windows Office Notepad.
The files are described as follows: MCS_Suzuki_value of the standard deviation of the lognormal distribution expressed in [dB].
DOI: 10.6084/m9.figshare.14545998
title: Remote work and chilcare dataset - Controlled.xlsx

description: <i>The balancing act: A qualitative study of remote work and childcare during the COVID-19 lockdown in South Africa<br></i><br>This is the data set, informed consent form and questionnaire for the article entitled: "The balancing act: Remote work and childcare during the COVID-19 lockdown in South Africa". <br>This data should be handled confidentially and is the property of the relevant academic institution
DOI: 10.6084/m9.figshare.14545998.v1
title: Remote work and chilcare dataset - Controlled.xlsx

description: This is the data set for the article entitled: "The balancing act: Remote work and childcare during the COVID-19 lockdown in South Africa". This data should be handled confidentially and is the property of the relevant academic institution
DOI: 10.34808/hvg7-s051
title: Nuts  52 (voj. opolskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. opolskie (Poland, nuts 52)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
1601
2127
733
193
2320
2000
1632
2196
715
167
2363
2001
1440
1944
632
149
2093
2002
1366
1756
578
141
1897
2003
1348
1725
529
163
1888
2004
1191
1536
494
150
1686
2005
1013
1294
422
148
1442
2006
1048
1325
361
128
1453
2007
1087
1404
408
136
1540
2008
1043
1281
349
141
1422
2009
912
1128
311
114
1242
2010
836
1028
270
107
1135
2011
836
1001
264
99
1100
2012
798
977
268
82
1059
2013
790
923
222
96
1019
2014
738
857
179
104
961
2015
710
808
166
102
910
2016
754
859
299
99
958
2017
700
849
311
78
927
2018
705
787
272
81
868
2019
614
703
223
73
776
DOI: 10.34808/kk77-fm39
title: The aggregation of objects representing buildings in the Kartuzy district - scale 1:10000. Data from OSM.

description: The process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
The data include the spatial scope of Kartuzy district. Most buildings do not have a prescribed type. The provided data include original data downloaded from OSM (on 26 April 2021) [1] as well as processed data. The aggregation process was performed taking into account the proximity of the neighborhood [2] based on the minimum size of the figure [3, 4]. The data are the basis for the subsequent steps in the process of sequential generalization of building groups.
Literature
[1] http://download.geofabrik.de/ [access: 26.04.2021].
[2] Kozioł, Krystian, and Michał Lupa. "The use of merging and aggregation operators for MRDB data feeding." Geoinformatica Polonica 12 (2013): 17-24.
[3] Chrobak, Tadeusz. Badanie przydatności trójkąta elementarnego w komputerowej generalizacji kartograficznej. Uczelniane Wydawnictwa Naukowo-Dydaktyczne AGH, 1999.
[4] Chrobak, Tadeusz, et al. "A method for assessing generalized data accuracy with linear object resolution verification." Geocarto International 32.3 (2017): 238-256.
DOI: 10.34808/pr55-xd24
title: Nuts  43 (voj. lubuskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. lubuskie (Poland, nuts 43)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
930
1135
540
180
1315
2000
950
1186
629
185
1371
2001
801
1070
433
145
1215
2002
799
1083
400
177
1260
2003
788
1055
391
180
1235
2004
847
1209
356
168
1377
2005
860
1169
245
174
1343
2006
835
1125
282
147
1272
2007
908
1193
445
157
1350
2008
906
1236
788
170
1406
2009
992
1323
549
137
1460
2010
845
1113
673
108
1221
2011
823
1086
693
122
1208
2012
803
1086
570
99
1185
2013
747
1019
507
94
1113
2014
717
957
379
81
1038
2015
639
786
432
92
878
2016
684
878
460
113
991
2017
682
855
339
84
939
2018
663
790
392
79
869
2019
660
775
403
92
867
DOI: 10.34808/22xd-hs58
title: Three series of measurement of spring force in relation to deflection of disc springs assembled in X configuration.

description: Attached data consist of three series of conducted measurement of disc springs package characteristic. The characteristic describes relation between spring force and deflection of the package. First column of each serie present axial deflection of the package, while second columns contain recorded spring force. Object of research contained six disc springs 03511850 manufactured by Sodemann company according to standard DIN 2093. The springs were assembled in series, parallel to each other.
DOI: 10.34808/545j-6m72
title: Nuts  42 (voj. zachodniopomorskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. zachodniopomorskie (Poland, nuts 42)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
 
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
2602
3361
833
322
3683
2000
2451
2992
718
332
3324
2001
2174
2764
643
250
3014
2002
2179
2716
678
250
2966
2003
2057
2551
632
243
2794
2004
2034
2683
617
235
2918
2005
1875
2357
557
236
2593
2006
1771
2173
489
233
2406
2007
1938
2421
728
229
2650
2008
1860
2342
700
244
2586
2009
1818
2237
651
206
2443
2010
1485
1802
464
151
1953
2011
1544
1885
464
170
2055
2012
1407
1744
544
131
1875
2013
1503
1812
473
155
1967
2014
1418
1717
523
147
1864
2015
1298
1470
429
125
1595
2016
1332
1608
474
149
1757
2017
1232
1435
404
120
1555
2018
1182
1357
494
129
1486
2019
1221
1406
540
129
1535
DOI: 10.34808/dw4d-j225
title: Nuts  41 (voj. wielkopolskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. wielkopolskie (Poland, nuts 41)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
 
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
5825
7449
1977
692
8141
2000
5803
7443
1778
603
8046
2001
5364
7013
1637
495
7508
2002
5362
7079
1571
520
7599
2003
5070
6494
1394
525
7019
2004
4910
6435
1311
540
6975
2005
4268
5567
1184
503
6070
2006
4499
5709
1205
511
6220
2007
4890
6351
1342
512
6863
2008
4882
6265
1383
553
6818
2009
3989
5171
1082
403
5574
2010
2930
3624
918
343
3967
2011
2996
3663
912
405
4068
2012
2565
3085
819
315
3400
2013
2633
3126
827
289
3415
2014
2392
2808
927
268
3076
2015
2196
2523
938
245
2768
2016
2316
2683
1039
249
2932
2017
3122
3594
1064
294
3888
2018
3232
3766
1163
261
4027
2019
3894
4566
1285
279
4845
DOI: 10.34808/h3yk-1m84
title: Nuts  22 (voj. slaskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. slaskie (Poland, nuts 22)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
 
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
7230
8890
2153
633
9523
2000
6898
8512
1956
588
9100
2001
6496
8218
1883
457
8675
2002
6420
7930
1803
512
8442
2003
6379
7814
1756
513
8327
2004
7046
8703
1909
511
9214
2005
6355
7897
1655
439
8336
2006
6179
7742
1622
427
8169
2007
6325
7891
1677
476
8367
2008
5903
7294
1646
455
7749
2009
5566
6857
1486
414
7271
2010
5015
6132
1343
352
6484
2011
5035
6115
1503
347
6462
2012
4675
5707
1343
336
6043
2013
4529
5506
1358
267
5773
2014
4360
5324
1274
249
5573
2015
3792
4584
1252
255
4839
2016
3650
4347
1283
257
4604
2017
3501
4306
1166
246
4552
2018
3222
3783
1055
219
4002
2019
2965
3561
1026
199
3760
DOI: 10.34808/w86p-tc73
title: Nuts 61 (voj. kujawsko-pomorskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. kujawsko-pomorskie (Poland, nuts 61)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
2505
3049
1162
343
3392
2000
2877
3614
1360
327
3941
2001
2664
3348
1283
311
3659
2002
2626
3343
1198
320
3663
2003
2495
3123
1110
290
3413
2004
2395
3013
1087
298
3311
2005
2157
2758
955
325
3083
2006
2051
2559
837
347
2906
2007
2037
2566
826
364
2930
2008
1908
2343
805
311
2654
2009
1646
1943
655
231
2174
2010
1490
1799
570
228
2027
2011
1336
1463
556
234
1697
2012
1319
1486
530
222
1708
2013
1182
1365
453
179
1544
2014
1044
1112
458
179
1291
2015
1008
1135
462
153
1288
2016
1018
1101
449
178
1279
2017
949
1080
470
151
1231
2018
970
1031
409
171
1202
2019
940
974
416
211
1185
DOI: 10.34808/f17b-me05
title: Nuts  21 (voj. malopolskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. malopolskie (Poland, nuts 21)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
 
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
5538
7038
2054
427
7465
2000
5427
7051
1924
400
7451
2001
5237
6814
1870
384
7198
2002
5285
6823
1848
375
7198
2003
4968
6378
1580
367
6745
2004
4880
6361
1590
335
6696
2005
4437
5596
1465
334
5930
2006
4440
5692
1314
308
6000
2007
4720
6155
1492
342
6497
2008
4677
5973
1541
344
6317
2009
4418
5603
1504
314
5917
2010
4004
5047
1326
235
5282
2011
4364
5425
1484
312
5737
2012
3902
4775
1249
253
5028
2013
3764
4659
1265
221
4880
2014
3936
4805
1318
234
5039
2015
3839
4619
1224
198
4817
2016
3939
4764
1225
185
4949
2017
3612
4310
1117
194
4504
2018
3404
4003
1151
223
4226
2019
3136
3716
1067
176
3892
DOI: 10.34808/gzcx-4343
title: Nuts 81 (voj. lubelskie). Number of accidents, injuries, seriously Injured and fatalities

description: The data contains information about the number of accidents, injuries, seriously Injured and fatalities between 1999 and 2019 in months in voj. lubelskie (Poland, nuts 81)
Source of data: Police Accident database SEWIK, Data has been processed by GUT.
Year
Accidents
Injuries
Seriously Injured
Fatalities
Victims
1999
2900
3673
1931
393
4066
2000
3539
4411
1761
411
4822
2001
2705
3459
1558
358
3817
2002
3043
3954
1351
354
4308
2003
2644
3372
1164
336
3708
2004
2586
3287
1303
358
3645
2005
2446
3160
1211
322
3482
2006
2212
2758
1047
341
3099
2007
2425
3080
1304
354
3434
2008
2358
2955
1301
372
3327
2009
2093
2674
1093
318
2992
2010
1819
2287
839
256
2543
2011
1798
2250
891
252
2502
2012
1623
1877
772
241
2118
2013
1497
1795
767
250
2045
2014
1408
1669
677
195
1864
2015
1252
1436
589
188
1624
2016
1262
1484
634
178
1662
2017
1242
1432
654
157
1589
2018
1216
1286
598
179
1465
2019
1139
1233
610
170
1403
DOI: 10.6084/m9.figshare.14661657
title: Ionpath metabolic profiling

description: Please cite original article: https://doi.org/10.1101/2020.01.17.909796
DOI: 10.6084/m9.figshare.14661657.v4
title: Ionpath metabolic profiling

description: Please cite original article: https://doi.org/10.1101/2020.01.17.909796
DOI: 10.6084/m9.figshare.14661657.v3
title: Ionpath metabolic profiling

description: Please cite original article: https://doi.org/10.1101/2020.01.17.909796
DOI: 10.5517/ccdc.csd.cc25xmb2
title: CCDC 2023504: Experimental Crystal Structure Determination

description: Related Article: Muhammad Khalid, Akbar Ali, Zia UdDin, Muhammad Nawaz Tahir, Sara Figueirêdo de Alcântara Morais, Ataualpa Albert Carmo Braga, Muhammad Nadeem Akhtar, Muhammad Imran, Edson Rodrigues-Filho|2021|J.Mol.Struct.|1241|130650|doi:10.1016/j.molstruc.2021.130650
DOI: 10.5517/ccdc.csd.cc25xmc3
title: CCDC 2023505: Experimental Crystal Structure Determination

description: Related Article: Muhammad Khalid, Akbar Ali, Zia UdDin, Muhammad Nawaz Tahir, Sara Figueirêdo de Alcântara Morais, Ataualpa Albert Carmo Braga, Muhammad Nadeem Akhtar, Muhammad Imran, Edson Rodrigues-Filho|2021|J.Mol.Struct.|1241|130650|doi:10.1016/j.molstruc.2021.130650
DOI: 10.5281/zenodo.4816110
title: Replication Package for "Ethnic Violence Across Space"

description: This is the replication package for the article "Ethnic Violence Across Space", forthcoming at the Economic Journal. Credit for the code provided in the zipped folder goes to David Schönholzer.
DOI: 10.5281/zenodo.4816109
title: Replication Package for "Ethnic Violence Across Space"

description: This is the replication package for the article "Ethnic Violence Across Space", forthcoming at the Economic Journal. Credit for the code provided in the zipped folder goes to David Schönholzer.
DOI: 10.6084/m9.figshare.14661771.v1
title: slideseqV2

description: Please cite original article: https://doi.org/10.1038/s41587-020-0739-1<br>
DOI: 10.34740/kaggle/dsv/2288058
title: From Images to 3D Shapes(FI3S)
DOI: 10.25625/utt4sn/6mafdb
title: filterNHP data

description: Dataset supporting filterNHP, an R package and web-based application at https://filterNHP.dpz.eu.
DOI: 10.5281/zenodo.4880427
title: Supporting data (structural data and sample descriptions)

description: Supporting data (structural data and sample descriptions) for the manuscript entitled "Two Cenozoic burial phases revealed by structural and geochronological data from the Nevado-Filábride complex (Sierra de los Filábres, Southeastern Spain)", submitted to Tectonics.
DOI: 10.25625/utt4sn/ltrmus
title: Metadata for filterNHP dataset

description: Metadata describing the variables and content of the tables of the "filterNHP data.xlsx" file.