研究經費縮減、競爭者日益增加，以及出版物以量取勝的風氣，使衡量研究成果的標準日趨單一，科學研究人員的壓力指數也因此節節攀升，除此之外，監督不周的監管體系，更促使研究員冒險做出違反學術道德的行為。從每年遞增的期刊論文遭撤數量，和頻頻爆出的學術不端醜聞，便不難看出情況仍在惡化。醜聞爆發後，不少研究人員幽幽地辯解：「所有人都這麼做」、「我只是做這麼一次而已」，難道他們都不知道學術欺詐會有什麼樣的後果？
「僅此一次」的想法會將你推入深淵
最惡名昭彰的例子，莫過於美國能源產業巨頭 ― 安隆公司，所主導的史上最大企業舞弊案。安隆公司曾為了解決一起大額投資項目的無預警延遲，而竄改一個季度的財務帳目。此後，公司高層造假成習，竄改每個季度財務帳目以掩蓋虧損，並推高公司股價，最終導致公司宣布破產。
紐約時報於2013年4月特別報導的荷蘭蒂爾堡大學前任社會心理學教授Diederik Stapel，便是另外一起引發世界譁然的案例。在Diederik Stapel憑著博士研究走紅荷蘭學術界十餘年之後，遭舉發多次偽造他不滿意的研究數據，以維持他的明星教授地位和光環。暫且不論他在初犯時，是否因承受過多壓力，而決心鋌而走險，但在接下來的近十年間，他在無人監管的情況下，過度沉迷於受人仰慕的虛榮，而再三重複學術欺詐行為，最後總計影響遍及五十五件出版品，其中不乏國際知名期刊。
後果嚴重，可能危及生命
學術欺詐並非只是影響個人或團體名譽的行為而已，它也可能造成無法挽回的遺憾。Andrew Wakefield偽造MMR疫苗和自閉症的研究數據，刻意錯誤推論兩者之間的因果關係，並提倡施打單一麻疹疫苗，以圖利某疫苗公司。該消息傳出後，英國和愛爾蘭的MMR疫苗接種率大幅下滑，使得麻疹和腮腺炎的感染人數短期內急速飆升，不僅有孩童因此喪命，也有少數因感染麻疹而引發腦炎，造成永久性後遺症。Wakefield也自食惡果，不僅其研究論文遭英國醫學期刊《刺胳針》撤回，他的醫生執照也遭吊銷，職涯就此告終。
重獲職業尊嚴的重生計畫
美國衛生研究院（The National Institutes of Health – NIH）資助了一個名為「專業和誠信的研究計畫（Professionalism and Integrity in Research Program）」，簡稱為「PI計畫」，以協助學術欺詐情節較輕的研究人員重回職場、重獲職業尊嚴。此PI計畫的前身「RePAIR」，首次試行於2012年，由華盛頓大學的臨床研究倫理中心的主任James DuBois主持，主要是透過檢視研究人員當初觸犯既定學術規範的原因，並制定相關管理計畫，以保證學術欺詐行為不會重演，從而協助曾違反學術倫理的研究人員重回學術界。通過該計畫的研究人員會獲得相關證書，而該證書也會被轉交給該人員的原就職研究機構。
孰能無過，但有過能改則天下太平？
PI計畫本著給予研究人員第二次機會的初衷，乍聽之下十分合情理。但問題是，此計畫究竟能有多大的「改造」能力，能讓人洗心革面、轉念向善？又，原就職機構是否有義務要認可此證書？此外，此計畫運作於美國學術體制內，這表示在其他國家留有學術欺詐前科的研究人員，可能就無法輕易擺脫罪名。奉勸諸位學術先進，切莫以身試法，墮入「僅此一次」的無底深淵。
學術詐欺
Author : Meng-Che Wu
Assessment of Applying SSSC to Power Market for Carbon Trading
imgur.com/a/70lJ2
Author : Kai-Hung Lu
Assessment of Power Market for Carbon Trading by Modified Particle Swarm Optimization
http://www.iaeng.org/publication/IMECS2012/IMECS2012_pp1047-1051.pdf
學術詐欺
Author : Meng-Che Wu
Assessment of Applying SSSC to Power Market for Carbon Trading
imgur.com/a/70lJ2
Author : Kai-Hung Lu
Assessment of Power Market for Carbon Trading by Modified Particle Swarm Optimization
http://www.iaeng.org/publication/IMECS2012/IMECS2012_pp1047-1051.pdf
研究生: 李元輝
研究生(外文): Yuan-hui Li
論文名稱: 結合碳交易以價格為導向之機組排程研究
論文名稱(外文): A Study for Price-Based Unit Commitment with Carbon
In this thesis, the Hybrid Genetic Algorithm-Ant Colony Optimization (GACO) approach is presented to solve the unit commitment problem (UC), and comparison with the results obtained using literature methods. Then this thesis applied the ability of the Genetic Algorithm (GA) operated after Ant Colony Optimization (ACO) can promote the ACO efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence. The other objective of this thesis is to investigate an influence of emission constraints on generation scheduling. The motivation for this objective comes from the efforts to reduce negative trends in a climate change. In this market structure, the independent power producers have to deal with several complex issues arising from uncertainties in spot market prices, and technical constraints which need to be considered while scheduling generation and trading for the next day. In addition to finding dispatch and unit commitment decisions while maximizing its profit, their scheduling models should include trading decisions like spot-market buy and sell. The model proposed in this thesis build on the combined carbon finance and spot market formulation, and help generators in deciding on when these commitments could be beneficial.
研究生: 李元輝
研究生(外文): Yuan-hui Li
論文名稱: 結合碳交易以價格為導向之機組排程研究
論文名稱(外文): A Study for Price-Based Unit Commitment with Carbon
In this thesis, the Hybrid Genetic Algorithm-Ant Colony Optimization (GACO) approach is presented to solve the unit commitment problem (UC), and comparison with the results obtained using literature methods. Then this thesis applied the ability of the Genetic Algorithm (GA) operated after Ant Colony Optimization (ACO) can promote the ACO efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence. The other objective of this thesis is to investigate an influence of emission constraints on generation scheduling. The motivation for this objective comes from the efforts to reduce negative trends in a climate change. In this market structure, the independent power producers have to deal with several complex issues arising from uncertainties in spot market prices, and technical constraints which need to be considered while scheduling generation and trading for the next day. In addition to finding dispatch and unit commitment decisions while maximizing its profit, their scheduling models should include trading decisions like spot-market buy and sell. The model proposed in this thesis build on the combined carbon finance and spot market formulation, and help generators in deciding on when these commitments could be beneficial.
Author(s)
Ting-Chia Ou
Inst. of Nucl. Energy Res., Taoyuan, Taiwan
Kai-Hung Lu ; Whei-Min Lin ; Chih-Ming Hong
A study for price-based unit commitment with carbon trading by DI&C simulation
In this paper, the Hybrid Genetic Algorithm-Ant Colony Optimization (GACO) approach is presented to solve the unit commitment problem, and comparison with the results obtained using literature methods by nuclear-grade Digital Instrumentation and Control (DI&C) simulation. Then this paper applied the ability of the Genetic Algorithm (GA) operated after Ant Colony Optimization (ACO) can promote the ACO efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence. The other objective of this paper is to investigate an influence of emission constraints on generation scheduling. The motivation for this objective comes from the efforts to reduce negative trends in a climate change. In this market structure, the nuclear power plants (NPPs) and independent power producers (IPPs) have to deal with several complex issues arising from uncertainties in spot market prices, and technical constraints which need to be considered while scheduling generation and trading for the next day. In addition to finding dispatch and unit commitment decisions while maximizing its profit, their scheduling models should include trading decisions like spot-market buy and sell. The model proposed in this paper build on the combined carbon finance and spot market formulation, and help generators in deciding on when these commitments could be beneficial.
Author(s)
Ting-Chia Ou
Inst. of Nucl. Energy Res., Taoyuan, Taiwan
Kai-Hung Lu ; Whei-Min Lin ; Chih-Ming Hong
A study for price-based unit commitment with carbon trading by DI&C simulation
In this paper, the Hybrid Genetic Algorithm-Ant Colony Optimization (GACO) approach is presented to solve the unit commitment problem, and comparison with the results obtained using literature methods by nuclear-grade Digital Instrumentation and Control (DI&C) simulation. Then this paper applied the ability of the Genetic Algorithm (GA) operated after Ant Colony Optimization (ACO) can promote the ACO efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result, because the ants produced randomly by pheromone process are not necessary better. This method can not only enhance the neighborhood search, but can also search the optimum solution quickly to advance convergence. The other objective of this paper is to investigate an influence of emission constraints on generation scheduling. The motivation for this objective comes from the efforts to reduce negative trends in a climate change. In this market structure, the nuclear power plants (NPPs) and independent power producers (IPPs) have to deal with several complex issues arising from uncertainties in spot market prices, and technical constraints which need to be considered while scheduling generation and trading for the next day. In addition to finding dispatch and unit commitment decisions while maximizing its profit, their scheduling models should include trading decisions like spot-market buy and sell. The model proposed in this paper build on the combined carbon finance and spot market formulation, and help generators in deciding on when these commitments could be beneficial.