ENTROPY-SWITZ 润色咨询

Entropy

出版年份:1999 年文章数:7882 投稿命中率: 开通期刊会员,数据随心看

出版周期:Monthly 自引率:19.7% 审稿周期: 开通期刊会员,数据随心看

前往期刊查询

期刊讨论

  1. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2023-01-19 ms4000000717792052 来自河南省

    审稿速度:2.0 | 投稿命中率:50.0
    经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。

    0

  2. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2021-12-29 rayms

    是否一定要按照结果的顺序撰写方法的顺序?

    1

    展开1条回复
  3. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2021-12-29 ms6000000264964247

    方法的撰写顺序/逻辑顺序是什么?

    1

    展开1条回复
  4. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2020-05-19 ms8775166821456669

    审稿速度:4.0
    经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。

    0

  5. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2020-05-18 ms2983094698733738

    审稿速度:2.0
    经验分享:你真不容易,要我就换期刊了

    0

  6. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2020-04-05 ms313574960747337

    审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了

    0

  7. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2020-03-30 ms2614478266438915

    审稿速度:1.0
    经验分享:received date
    21 february 2020
    revised date
    25 march 2020
    accepted date
    28 march 2020
    熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。

    0

  8. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2019-12-12 ms4512939187244456

    递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。

    0

  9. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2019-12-12 ms4729674192825029

    期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。

    0

  10. [GetPortalCommentsPageByObjectIdResponse(id=2110802, encodeId=20ff2110802d0, content=审稿速度:2.0 | 投稿命中率:50.0<br>经验分享:分了三个审稿人,一共给了33条意见,提的问题还是非常专业的。, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=41, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=7d3a8452177, createdName=ms4000000717792052, createdTime=Thu Jan 19 01:13:36 CST 2023, time=2023-01-19, status=1, ipAttribution=河南省), GetPortalCommentsPageByObjectIdResponse(id=1101566, encodeId=4f4711015661d, content=是否一定要按照结果的顺序撰写方法的顺序?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=48, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220301/6252e946e5ef413b86dc0f7d1f73b6db/9a7e8c88a38e487b8da4968a67bbd261.png, createdBy=b9f692910, createdName=rayms, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1101565, encodeId=483c1101565b2, content=方法的撰写顺序/逻辑顺序是什么?, beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=42, replyNumber=1, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=/v1.0.0/img/user_icon.png, createdBy=1ff65466529, createdName=ms6000000264964247, createdTime=Wed Dec 29 14:52:51 CST 2021, time=2021-12-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860705, encodeId=a1ef860e05bd, content=审稿速度:4.0<br>经验分享:该刊物质量水平还是蛮高的,比很多ieee trans要好。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=111, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=72925414015, createdName=ms8775166821456669, createdTime=Tue May 19 00:38:24 CST 2020, time=2020-05-19, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=860696, encodeId=934186069667, content=审稿速度:2.0<br>经验分享:你真不容易,要我就换期刊了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=27a45414023, createdName=ms2983094698733738, createdTime=Mon May 18 19:40:43 CST 2020, time=2020-05-18, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=859114, encodeId=e975859114a8, content=审稿非常严格,虽然收费,但感觉并不容易发.三个审稿人提了好多修改意见,大修两次、小修三次~~都改吐血了 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=117, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=3de05414115, createdName=ms313574960747337, createdTime=Sun Apr 05 12:38:15 CST 2020, time=2020-04-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=858909, encodeId=367585890922, content=审稿速度:1.0<br>经验分享:received date<br> 21 february 2020<br> revised date<br> 25 march 2020<br> accepted date<br> 28 march 2020<br> 熵的跨学科应用,一审大修,专家意见一周左右返回,主编decision花了十天左右,然后大修给十天。大修提交后一周内返回小修后录用。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b6e05414152, createdName=ms2614478266438915, createdTime=Mon Mar 30 16:57:11 CST 2020, time=2020-03-30, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855744, encodeId=4899855e441c, content=递交稿件,他又说试验样本太少,坚决拒稿。我也是醉了。我只是使用熵值方法来区分我的刺激诱发的神经活动,不是去研究机器学习算法的,现在变成了仅仅很少一部分是关于熵的,满篇都是特征提取、特征选择和机器学习等算法对比研究。让我加入八个算法进去,最后又说我试验样本太少拒稿。20个受试,每个受试做20组,每组10个试次,这个样本不算少了吧,即使使用机器学习分类也够了吧。结果花了两个月大改了2次,他又来了一句话样本太少强烈拒稿。我也是醉了,欲哭无泪!期刊再好,运气不好遇到个极品审稿人,不仅劳民伤财,最后也是遭罪。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=105, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1e295414102, createdName=ms4512939187244456, createdTime=Thu Dec 12 15:30:37 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=855743, encodeId=faaf855e437f, content=期刊编辑很好,审稿速度也挺快的,就是有的审稿专家比较较真。投了一篇关于新型熵方法区分和识别某种神经信号。三个审稿人,两个审稿人给的意见非常正面而且同意接收,最后一个审稿人非常较真和固执,提了一大堆意见,硬是让我加入他的特征选择算法,并要求增加其他三个特征选择算法进行对比。我按照他的要求认认真真地修改,文章基本上重新写了一遍,硬生生从开始的14页增加到20页。提交之后,他又说svm不够精确,要我再加入随机森林、lda算法,和“留一法”与之前的“十折交叉验证”对比。我又按照要求文章增加到26页。 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=94, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=d2bd5414155, createdName=ms4729674192825029, createdTime=Thu Dec 12 15:30:06 CST 2019, time=2019-12-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=852889, encodeId=6f96852889d9, content=received date 14 may 2019<br> revised date 6 july 2019<br> accepted date 10 july 2019<br> published date 13 july 2019 , beContent=null, objectType=tool_impact_factor, channel=null, level=null, likeNumber=100, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=87eb5414016, createdName=ms4817431182430527, createdTime=Tue Jul 30 13:23:16 CST 2019, time=2019-07-30, status=1, ipAttribution=)]
    2019-07-30 ms4817431182430527

    received date 14 may 2019
    revised date 6 july 2019
    accepted date 10 july 2019
    published date 13 july 2019

    0

共32条页码: 1/4页10条/页
分享您的投稿经验,提升MI经验值,获取更多积分