兩篇資工paper做基礎單字與文法檢查 - 潤稿

[必]我已經讀過置底版規、參考費率、發文必讀公告，並願意遵守規定：YES

* 如已讀過，請填 YES
* 如未讀過，請讀過再重新發文。未填視為未讀，一律刪文處理並警告。

──────────────────────────────────────
[必]工 作 量： 一篇4200字上下，一篇4000字上下。
（請載明字數或估算大約總字數。違者直接刪文）
[必]工作報酬：0.6/字
（無預算或預算過低，都會被直接刪除。*請註明以中文或外文計價。）
[必]涉及語言：英文
[必]所屬領域：資訊 (例：教育/醫學/法律）
[必]文件類型：論文
（例：論文摘要/期刊/書信。* 專業文類必須符合對應最低費率要求）
[必]截 稿 日：談妥後3日處理時間
（若為急件，請加乘急件費率。計算方式請見置底公告）
[必]應徵期限：8/20
[必]聯絡方式：站內信
[必]付費方式：跟潤稿者協調，以您方便為主。
（例：預付OO元訂金，交稿後XX天內付清餘額，完稿後YY天內付清。
案主跟譯者需協定何時及如何付款，以避免日後爭議。）
──────────────────────────────────────
[選]工作要求：只需檢查基本文法與單字，不需管整體意思，不過我們需要你PO相關的
工作經驗，這部份我們比較重視，文章潤稿部分就還好。
[選]參考段落：
1. With the rapid advance of communication and networking technologies, many
devices connect to the Internet. That leads to the concept of IoT. To develop
different IoT applications, many web cloud platforms are proposed to provide
data col- lection, aggregation, and application. For example, IoTtalk [1],
IoT Core (Amazon Web Services), Cloud IoT Core (Google Cloud) are the web
platforms for IoT. However, cloud-based web services cannot apply to all IoT
situations. In addition, the academia and the industry pay much attention to
security issues of IoT with the growth of IoT. The paper proposes the IoT
Framework to deal with the problems.
2. With recent changes in wireless communication ecosystem,
the demand for using web services continues to increase,
Cisco’s technical white paper [1] predicts that future mobile
data traffic has been growing explosively in recent years, in
other words, users are increasingly unable to tolerate low QoE
(Quality of Experience). Besides, nearly 50% of mobile data
traffic will belong to video streaming applications. In typical
mobile video streaming of the existing 4G infrastructure,
users’ packets must be transmitted through the base station,
backbone network and then to the core network. The inherent
4G architecture cannot tolerate such a large amount of video
traffic in the future. To address this challenge, European
Telecommunications Standards Institute (ETSI) has proposed
a promising technological paradigm, mobile edge computing
(MEC) [2], which can be combined with the 4G network
architecture to effectively reduce latency and network traffic
congestion by providing computation and storage capacity
from core network to edge network. In particular, MEC
server, which operates as local content delivery node and
serves cached contents. In this paper, we build the MEC
architecture for video streaming, and deploy our proposed
machine learning models for video popularity prediction in
the MEC server.
[選]試 譯 文：（100-200字，並不超過全文1/10。嚴禁私下試譯。若未提供請勿刪除）
[選]其他事項：（若未提供請勿刪除）

──────────────────────────────────────

--