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"This undergraduate textbook on Linear Algebra and n-Dimensional Geometry, in a self-teaching style, is invaluable for sophomore level undergraduates in mathematics, engineering, business, and the sciences. These are classical subjects on which there are many mathematics books in theorem-proof style, but this unique volume has its focus on developing the mathematical modelling as well as computational and algorithmic skills in students at this level. The explanations in this book are detailed, lucid, and supported with numerous well-constructed examples to capture the interest and encourage the student to master the material."

"A thorough introduction to a burgeoning interdisciplinary field, with an emphasis on foundational material.Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming."

"The chest X-ray (CXR) or chest radiograph remains the most commonly ordered imaging study in medicine, yet paradoxically is often the most complex to learn, recall, and master effective and accurate interpretation. The chest radiograph includes all thoracic anatomy and provides a high yield, given the low cost and single source. This guide presents a structured lexicon for use by readers to reproducibly describe radiographic abnormalities of the chest detected on plain film CXRs. The lexicon is designed to provide readers with clinically significant differentiation of abnormalities detected. The content is structured to relate specific combinations of distinct radiographic findings to classes/groupings of pathological etiologies of those findings. Recognizing the individual findings and identifying their combination or lack of combination with other individual findings allows readers to create effective differential diagnoses that can then be further evaluated using other imaging procedures and/or non-radiographic clinical information. The book includes hundreds of images, including radiographs, CTs, graphics, and analogous models to help teach otherwise complex processes and radiographic principles."

"Algorithmic, or automatic, differentiation (AD) is a growing area of theoretical research and software development concerned with the accurate and efficient evaluation of derivatives for function evaluations given as computer programs. The resulting derivative values are useful for all scientific computations that are based on linear, quadratic, or higher order approximations to nonlinear scalar or vector functions. AD has been applied in particular to optimization, parameter identification, nonlinear equation solving, the numerical integration of differential equations, and combinations of these. Apart from quantifying sensitivities numerically, AD also yields structural dependence information, such as the sparsity pattern and generic rank of Jacobian matrices. The field opens up an exciting opportunity to develop new algorithms that reflect the true cost of accurate derivatives and to use them for improvements in speed and reliability. This second edition has been updated and expanded to cover recent developments in applications and theory, including an elegant NP completeness argument by Uwe Naumann and a brief introduction to scarcity, a generalization of sparsity. There is also added material on checkpointing and iterative differentiation. To improve readability the more detailed analysis of memory and complexity bounds has been relegated to separate, optional chapters.The book consists of three parts: a stand-alone introduction to the fundamentals of AD and its software; a thorough treatment of methods for sparse problems; and final chapters on program-reversal schedules, higher derivatives, nonsmooth problems and iterative processes. Each of the 15 chapters concludes with examples and exercises."

"Informasi memainkan pernanan yang penting dalam pasar modal, mengingat informasi merupakan salah satu faktor yang menggerakkan ekspektasi investor. Namun, beberapa dari informasi yang beredar di pasar tersebut sangat mungkin sengaja dimanipulasi oleh pihak-pihak tertentu, sehingga dikembangkan berbagai metode perdagangan yang dapat membantu investor untuk menghasilkan investasi terbaiknya, salah satunya adalah high-frequency trading. Meskipun penerapan praktik high-frequency trading mampu menghasilkan keuntungan yang lebih besar, efisien, dan cepat, namun di sisi lain, kelebihan yang dimiliki oleh algoritma yang digunakannya tersebut, justru kerap kali dimanfaatkan untuk dapat melaksanakan praktik-praktik yang dilarang dalam pasar modal, salah satunya adalah manipulasi pasar. Melalui skripsi ini, penulis akan melakukan perbandingan perspektif pengaturan tentang praktik high-frequency trading sehubungan dengan larangan praktik manipulasi pasar di Indonesia serta regulasi yang mengaturnya antara Indonesia dengan Amerika Serikat dan Uni Eropa. Selain itu, melalui skripsi ini, penulis melakukan analisis atas kesiapan Indonesia dalam penerapan highfrequency trading dalam perdagangan bursa. Metode yang digunakan di dalam Skripsi ini adalah Yuridis-Normatif yang didukung dengan bahan-bahan hukum primer, sekunder, dan tersier, serta menggunakan pendekatan konseptual dan komparatif terhadap hukum pasar modal yang berlaku di negara lain.

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Information plays an essential role in the capital market, considering that information is one factor that drives investors' expectations. However, some of the information circulating in the market is very likely to be deliberately manipulated by certain parties. Various trading methods have been developed to help investors make the best investment, one of which is high-frequency trading. Although the application of high-frequency trading practices can generate greater, efficient, and faster profits, on the other hand, the advantages possessed by the algorithm it uses are often used to carry out practices that are prohibited in the capital market, one of which is market manipulation. This thesis will compare perspectives on highfrequency trading practices concerning the prohibition of market manipulation practices in Indonesia and the regulations governing it between Indonesia, United States, and European Union. In addition, through this thesis, the author analyzes Indonesia's readiness to implement high-frequency trading in stock exchange trading. The method used in this thesis is Juridical-Normative which is supported by primary, secondary, and tertiary legal materials. It uses a conceptual and comparative approach to capital market law applicable in other countries."

"Algorithmic Trading (AT) telah menjadi salah satu alternatif strategi berinvestasi yang telah banyak digunakan di berbagai pasar finansial di dunia. Salah satu dampak yang muncul terhadap penggunaan AT ini adalah meningkatnya likuiditas pasar modal yang ditunjukkan dengan tren meningkatnya frekuensi dan value perdagangan. Pada penelitian ini, dilakukan analisis terhadap karakteristik perdagangan dari member Bursa Efek Indonesia yang telah menerapkan AT. Ternyata, value perdagangan yang ditunjukkan oleh member AT tersebut menunjukkan telah meliputi hampir 50% dari value total perdagangan. Tren ini berlaku baik secara harian, pada setiap sesi perdagangan, dan untuk 15 menit awal dan 15 menit akhir perdagangan. Selain itu, AT juga berdampak negatif terhadap turnover value market dan market return. Penerapan AT juga berdampak terhadap terhadap semakin meningkatnya efisiensi pembentukan price. Hal ini dibuktikan dengan korelasi positif antara penerapan AT dengan komponen permanen price dan berkorelasi negative dengan komponen transitory price.

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Algorithmic trading (AT) has become one of most popular of investment strategy that has been used in many stock exchange in the world. Because of its implementation, liquidity in many stock exchanges has increased dramatically. It has been found that the value and frequency of trading has increased as the proof of liquidity growth. With this thesis, it is proved that the value of AT in IDX has become 50% of total value of trading. It happens in daily trading, in every session, in critical time of trading, that is 15 menit in the beginning and 15 menit befor closing. Beside that, the implementation of AT has negative impact on turnover value market and market return. In term of price discovery, AT has contributed through the permanent component of price, but in the opposite direction of transitory price."

"This thesis presents an accurate and advanced numerical methodology to remedy difficulties such as direct numerical simulation of magnetohydrodynamic (MHD) flow in computational fluid dynamics (CFD), grid generation processes in tokamak fusion facilities, and the coupling between the surface tension force and Lorentz force in the metallurgical industry. In addition, on the basis of the numerical platform it establishes, it also investigates selected interesting topics, e.g. single bubble motion under the influence of either vertical or horizontal magnetic fields. Furthermore, it confirms the relation between the bubble’s path instability and wake instability, and observes the anisotropic (isotropic) effect of the vertical (horizontal) magnetic field on the vortex structures, which determines the dynamic behavior of the rising bubble.The direct numerical simulation of magnetohydrodynamic (MHD) flows has proven difficult in the field of computational fluid dynamic (CFD) research, because it not only concerns the coupling of the equations governing the electromagnetic field and the fluid motion, but also calls for suitable numerical methods for computing the electromagnetic field. In tokamak fusion facilities, where the MHD effect is significant and the flow domain is complex, the process of grid generation requires considerable time and effort. Moreover, in the metallurgical industry, where multiphase MHD flows are usually encountered, the coupling between the surface tension force and Lorentz force adds to the difficulty of deriving direct numerical simulations."

"Algorithmic trading (AT) sebagai fenomena mutakhir di pasar keuangan, khususnya pasar di Amerika dan wilayah Eropa, masih menjadi kontroversi. Ada yang menganggap (dan menunjukkan) AT memberi pengaruh positif terhadap market quality, ada juga yang menunjukkan hal sebaliknya. Menggunakan proxy aktivitas perdagangan, penelitian ini mengidentifikasi tren penggunaan AT dan dampaknya terhadap market quality di BEI. Adanya peningkatan aktivitas perdagangan (trading) yang dibarengi perubahan strategi perdagangan (nature of trading) menjadi petunjuk kuat tren penggunaan AT di BEI, meskipun dengan intensitas yang relatif lebih rendah dibandingkan pada pasar-pasar negara maju. Secara umum AT meningkatkan bid-ask spreads dan effective spreads, menurunkan bid-ask depth, serta mengurangi volatilitas harga saham. Hal ini menjadi indikasi bahwa AT memberi dampak negatif dengan menurunkan likuiditas pasar namun di saat yang sama justru memberi dampak positif dengan mengurangi volatilitas harga saham di BEI.

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Algorithmic trading (AT) as a fairly new phenomenon in financial markets, especially in the American and European markets, still have controversy and discourse with respect to its impact on market quality. Using normalized measure of Indonesia Stock Exchange (IDX) electronic message traffic as proxy for AT, this paper investigates AT and its impact on market quality in IDX. Significant increase in trading activity as well as change of trading strategy have become evidence of an increase in the use of AT in IDX, with relatively lower than both US and European markets. In general, AT wide bid-ask spreads and effective spreads, reduces bid-ask depth, as well as reduces volatility. These findings indicate that AT has negative impact on liquidity and positive impact on volatility in IDX."

"Perkembangan artificial intelligence serta implementasi komersialnya yang cepat telah menghasilkan banyak manfaat dan nilai ekonomi bagi produsen dan konsumen di seluruh dunia. Salah satu manfaat tersebut adalah kemampuan bagi perusahaan untuk terlibat dalam penetapan harga yang dipersonalisasi, atau personalized pricing, yang merupakan bentuk strategi first-degree price discrimination yang sangat akurat, di mana perusahaan menetapkan harga yang berbeda untuk setiap pelanggan individu berdasarkan data pribadi mereka dan ditentukan oleh algoritme yang kompleks. Meskipun hal ini juga menghasilkan banyak manfaat yang meningkatkan efisiensi pasar, seperti membebankan harga yang lebih rendah untuk konsumen yang tidak mampu membeli produk tertentu, hal ini juga dapat membebankan harga yang terlalu tinggi kepada konsumen yang oleh algoritme dianggap sesuai untuk mereka. Dengan demikian, penetapan harga yang dipersonalisasi menimbulkan masalah antimonopoli yang serius, karena berpotensi membahayakan consumer welfare. Melalui tinjauan pustaka yang sistematis, makalah penelitian ini bertujuan untuk menguji kelayakan penggunaan Pasal 102 TFEU sebagai alat utama untuk mengatasi potensi dampak merugikan dari penetapan harga yang dipersonalisasi dengan menganggapnya sebagai penyalahgunaan dominasi yang eksploitatif jika dilakukan oleh perusahaan dengan dominasi yang dominan. posisi. Hasil penelitian menunjukkan bahwa hal ini dapat dicapai dengan dua cara, pertama dengan secara eksplisit menangani pembebanan harga yang berlebihan sebagai pengenaan “harga yang tidak wajar”, ​​dan kedua, jika pembebanan harga yang berlebihan dibarengi dengan adanya biaya pencarian dan switching yang tinggi. biaya, maka dapat dianggap sebagai pengenaan "kondisi perdagangan yang tidak adil" oleh perusahaan dominan, jika pendekatan pertama tidak cukup untuk campur tangan otoritas persaingan nasional (NCA). Selain itu, makalah penelitian menyarankan alternatif hukum lain untuk Pasal 102 TFEU untuk mengatasi dampak buruk dari personalized pricing.

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The recent acceleration in the development of artificial intelligence and its rapid commercial implementation has yielded a great number of benefits for producers and consumers around the world. One such benefits is the ability for firms to engage in personalized pricing, which is a form of highly accurate first-degree price discrimination strategy, whereby firms charge different prices for each individual customer based on their personal data and determined by complex algorithms. While this, too, yields many benefits in regard to market efficiency, such as charging lower prices for consumers who are otherwise unable to afford certain products, it can also charge excessively high prices to consumers that the algorithms deem to be appropriate for them. Thus, personalized pricing raises serious antitrust concerns, as it may potentially harm consumer welfare.

Through a systematic literature review, this research paper aims to examine the feasibility of using Article 102 TFEU as a key tool for addressing the potential adverse effects of personalized pricing by deeming it an exploitative abuse of dominance if it is conducted by a firm with a dominant position. The results show that this can be achieved in two ways, first by explicitly addressing the charging of excessive prices as an imposition of “unfair prices”, and second, if the charging of excessive prices is coupled with the presence of high search costs and switching costs, then it can be deemed as an imposition of “unfair trading conditions” by the dominant firms, should the first approach not suffice for national competition authorities (NCAs) to intervene. Moreover, the research paper suggests other legal alternatives to Article 102 TFEU to address the adverse effects of personalized pricing."