8/7/2019 Writing Problem and Hypothesis Statements for Engineering Research(25)

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Writing Problem and Hypothesis

Statements for Engineering Research(25)工程問題描述 /假設描述 

柯泰德線 英文論文編修訓練服務 http://www.chineseowl.idv.tw 

工程英文 

8/7/2019 Writing Problem and Hypothesis Statements for Engineering Research(25)

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工程問題描述 

• Setting of work proposal工程提案建構 : 你提案的主題是什麼?你的讀者可以明瞭提案的內容嗎?

• Work problem工程問題 :你的提案裡有你試著要解決或是想更進一步瞭解的問題嗎?

• Quantitative specification of problem工程問題的量化 :你要如何量化問題來讓你的讀者明白之前文獻研究所遇到的量化限制 ?

•  Importance of problem工程問題的中心 :如果問題沒被解決或是充分瞭解,這對提案的讀者會有多大的負面衝擊?

• Project need工程計劃需求 : 根據以上問題,最迫切的計劃需求是什麼?

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工程假設描述 

• Work objective工程目標 :工程提案的目標 ?

• Methodology to achieve objective 達成目標

的方法 :你的計劃中達成目標的步驟?• Anticipated results希望的結果 :你希望達成

的結果?

• Contribution to field領域的貢獻 :你的提案對相關工程領域的貢獻?

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範例 (工程問題描述)

工程計劃建構  Effectively controlling traffic congestionduring Internet access is a timely issue, particularly with theenormous amounts of data available. Moreover,supporting new Internet applications, e.g., voice over IPand video on demand, requires designing effective

congestion control and queue management algorithms.工程計劃問題  However, designing effective congestioncontrol and queue management algorithms is extremelycomplex given the variety of services supported on theInternet and their various demands for Quality of Service

(QoS). 工程計劃問題的量化  For instance, the Internet canonly provide best effort service, in which traffic is processedas quickly as possible; however, timeliness or actualdelivery can not be ensured, necessitating QoS for newInternet services.

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範例 (工程問題描述)

工程計劃問題的中心  Active queue management is limitedin that is uses queue length as a congestion indicator.Such an indicator cannot reflect the severity of congestion.However, average queue length varies with the level ofcongestion and with the parameter settings, thus making

the queuing delay of random early detection (RED) toosensitive to traffic load and parameter settings. 工程計劃需求  Therefore, a novel TCP congestion control scheme,Fuzzy BLUE, i.e. an extension of the conventional BLUEmechanism, must be developed.

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範例 (工程假設描述)

工程計劃目標  A novel TCP congestion control scheme, Fuzzy BLUE,

i.e. an extension of the conventional BLUE mechanism, can be

developed. An integral part of Fuzzy BLUE is designing the Fuzzy

BLUE Controller (FBC), which functions as a congestion controller in

the routers. 達成目標的方法  To do so, a two-input-single-output fuzzy

logic controller can be implemented. The input linguistic variables are

packet loss and queue length. The output linguistic variable is the drop

probability (i.e. pm). Owing to their computational simplicity, triangular

and trapezoidal shaped membership functions can then be used for

packet loss and queue length, as well as for pm. Next, a rule base can

be designed by setting linguistic rules and, then, determining themembership functions of linguistic values. Additionally, the rule base

can be designed either by a trial-and-error approach or theoretical

approach. In the trial-and-error approach, a set of if-then fuzzy rules is

constructed based on experimental knowledge; the system is then

tested.

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範例 (工程假設描述)

Notably, rules are changed again if the desired behavior is not

observed. This process continues until the functionality of the controller

is satisfied. In the theoretical approach, rules are designed so that

specific functionality of a parameter (such as throughput) is ensured.

Here, both approaches can be combined to yield optimum results. 希望

的結果  As anticipated, applying the fuzzy control scheme to control

congestion control is feasible given difficulties in obtaining a precise

model using conventional methods. The proposed approach, Fuzzy

BLUE, functions more effectively and robustly than other approaches

such as BLUE. 領域的貢獻  In addition to achieving a nearly 100%

throughput, Fuzzy BLUE has a better loss performance and queuelength behavior than the conventionally adopted BLUE mechanism

does.

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範例二(工程問題描述)

工程計劃建構  Computers and the Internet have becomean integral part of daily life activities, including work,communication, commerce, retrieval of new informationand entertainment. Given the increasing diffusion ofcomputers in society, human-computer interaction (HCI) is

increasingly relevant in order to ensure that human-computer communication is as natural as human-humancommunication. In addition to verbal cues, emotions arevital to human intelligence and profoundly impact humancommunication. These findings, together with recent

advances in sensing, tracking, analysis, and animation ofhuman nonverbal communicative signals, have fueledinterest among advanced HCI researchers in affectivecomputing. This emerging field focuses on computationalmodeling of human perception of affective states, synthesisof affective expressions, and design of affect-sensitive HCI.

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範例二(工程問題描述)

工程計劃問題  Affective computing attempts to ensure that a device candetect and effectively respond to emotions of its user in HIS. Approximately 80% to 90% of all human-to-human communication isnonverbal and emotional, necessitating that developers emphasizeaffective computing to ensure success in HCI. Given this capacity, acomputing device accumulates cues from user ’s emotions from a

variety of sources, e.g., facial expressions, posture, gestures, speech,force or rhythm of key strokes and temperature changes of the userhand on a mouse. Such sources can signify changes in the emotionalstate of users, and can be detected and interpreted via a computer. Abuilt-in camera that retrieves images of the user and algorithms can beused to process data in order to yield meaningful information. Speechrecognition and gesture recognition are among other promisingtechnologies for affective computing applications. 工程計劃問題的量化 For instance, in e-learning, the computer can sense from available cueswhen the user is having difficulty and offers expanded explanations oradditional information.

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範例二(工程問題描述)

 Although beneficial for various research and application areas, tacklingthese problems is a complex task. Research involving affectivecomputing problems has heavily stressed how to recognize and modelthe affectivity. However, such approaches fail to cope with emotionsthat are dynamically changeable and highly fuzzy owing to only theinability of pattern recognition approaches to recognize emotional

states and treat each emotional state as a static and not fuzzy one.Evaluating affective computing in HCI is often subjective, subsequentlyrelying on various application domains. 工程計劃問題的中心  Despitethe recent emergence of affective computing in HCI, many researchersbelieve that successfully dealing with emotional states in HCI wouldenhance the recognition accuracy of various modalities, e.g., speechrecognition. Affective computing can assist individuals in becomingmore comfortable with computer use. Capable of detecting whether ahuman user is under stress or confused, a computer could alter theenvironment to positively affect the emotional state of users. 工程計劃需求  Therefore, an efficient affective modeling scheme must bedeveloped that incorporates fuzzy emotional measurement of users.

 An evolutionary learning algorithm must also be developed to model

and learn emotions from users.

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範例二(工程假設描述)

工程計劃目標  An efficient affective modeling scheme can bedeveloped that incorporates fuzzy emotional measurement of users. An evolutionary learning algorithm can also be developed to model andlearn emotions from users.達成目標的方法  To do so, a user behaviorvideo corpus can be constructed. Appropriate member functions of thefuzzy-logic model can then be completed by analyzing the corpus.

Next, events and emotional states can be mapped, and inductivelearning algorithms can be used to understand the context of eventsand emotional states. The context consists of patterns of events,associations among objects, and expectations. Moreover, affectivemodeling can be adapted using a learning classifier systems approach.希望的結果  As anticipated, the proposed affective modeling schemecan increase the accuracy of emotional recognition in educationalgame problems by 10%. Additionally, inductive learning algorithms canfacilitate semi-automatic learning of how events and emotional statesare related, thus reducing human efforts by 30%. Moreover,adaptations to new environments can be performed as well.

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範例二(工程假設描述)

領域的貢獻  Importantly, the proposed scheme can contribute to effortsto further enhance HCI to be affect-sensitive HCI by facilitating affectivesenses with computers. The affective computing scheme can reducethe intrusiveness of HCI, possibly making individuals more receptive toHCI applications given their more natural interactions. Corporationscould learn more about their employees through affective computers,

with this knowledge used to maximize work productivity. For instance,affective computers can help to determine when employees are notcompletely focused on completing their tasks or determining the mostproductive situations for each individual. Additionally, affectivecomputing can enhance customer services, e.g., enhanced call-centerservices, phone-free access or data mining. Such efforts can help tomonitor consumer reactions towards television advertisements throughfacial-recognition networked software embedded in televisions; suchknowledge can ultimately enhance marketing campaigns. Given thevast array of human emotions, the proposed affective modeling schemecan also provide a valuable reference for efforts underway to model theemotions of users.

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