Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective

The current boom of learned query optimizers (LQO) can be explained not only by the general continuous improvement of deep learning (DL) methods but also by the straightforward formulation of a query optimization problem (QOP) as a machine learning (ML) one. The idea is often to replace dynamic programming approaches, widespread for solving QOP, with more powerful methods such as reinforcement learning. However, such a rapid "game change" in the field of QOP could not pass without consequences - other parts of the ML pipeline, except for predictive model development, have large improvement potential. For instance, different LQOs introduce their own restrictions on training data generation from queries, use an arbitrary train/validation approach, and evaluate on a voluntary split of benchmark queries. In this paper, we attempt to standardize the ML pipeline for evaluating LQOs by introducing a new end-to-end benchmarking framework. Additionally, we guide the reader through each data science stage in the ML pipeline and provide novel insights from the machine learning perspective, considering the specifics of QOP. Finally, we perform a rigorous evaluation of existing LQOs, showing that PostgreSQL outperforms these LQOs in almost all experiments depending on the train/test splits

Laparoscopic and Other Intrafascial Hysterectomy Techniques or Mucosal Ablation—A Choice for Maximum Organ Conservation

The operative methods of total uterine mucosal ablation (TUMA) as well as new abdominal and vaginal hysterectomy techniques are described. Classic intrafascial serrated edged macro-morcellator (SEMM) hysterectomy (CISH) by pelviscopy or laparotomy and intrafascial vaginal hysterectomy (IVH) are techniques that allow the nerve and the blood supply of the pelvic floor to remain intact, mainly because only the ascending branches of the uterine arteries are ligated. TUMA avoids the removal of the uterus altogether and is reserved for hypermenorrhea or menorrhagia without major enlargement of the uterus. Both CISH and IVH reduce the physical trauma of hysterectomy considerably and have the advantages of the supravaginal technique. Prophylaxis against cervical stump carcinoma is assured by coring out the cervix with the SEMM. In patients in whom both procedures are possible, IVH is preferred because it combines the minimal trauma and short operative time of vaginal hysterectomy. The decreased diameter of the cervix after coring out greatly simplifies this type of vaginal hysterectomy, the technique that has always been favored because of its short operative times and minimal trauma

Sonographic and Histological Morphometry of the Uterine Cervix—An Assessment of Laparoscopic and Other lntrafascial Hysterectomy Techniques

New abdominal and vaginal hysterectomy techniques, such as classic intrafascial serrated edged macro-morcellator (SEMM) hysterectomy (CISH), by pelviscopy/laparoscopy or laparotomy, and intrafascial vaginal hysterectomy (IVH), are both essentially supravaginal techniques. It has been claimed that they give a prophylaxis against cervical stump carcinoma by coring out the cervix with the SEMM. We set out to answer two questions: 1) How can vaginosonography help to choose an adequate SEMM diameter so that the cervical mucosa and transformation zone are completely removed, and 2) How often do cervical glands remain after the coring out procedure? We were able to show a good correlation between sonographic and histological morphology by giant and serial sections. In 253 CISH operations, resection of both endocervix and transformation zone was complete in 92.9%. Dysplasias were always removed completely; only 18 cervical cores exhibited healthy glands (retention cysts) in the resection margin. Therefore, CISH procedures should be able to prevent most of the cervical stump carcinomata that follow traditional supravaginal hysterectomy, but only long-term follow-up will give the final proof

Algebras of Measurements: the logical structure of Quantum Mechanics

In Quantum Physics, a measurement is represented by a projection on some closed subspace of a Hilbert space. We study algebras of operators that abstract from the algebra of projections on closed subspaces of a Hilbert space. The properties of such operators are justified on epistemological grounds. Commutation of measurements is a central topic of interest. Classical logical systems may be viewed as measurement algebras in which all measurements commute. Keywords: Quantum measurements, Measurement algebras, Quantum Logic. PACS: 02.10.-v.Comment: Submitted, 30 page

Urinary incontinence-85: an expanded prostate cancer composite (EPIC) score cutoff value for urinary incontinence determined using long-term functional data by repeated prospective EPIC-score self-assessment after radical prostatectomy

PURPOSE: To determine an objective cutoff value (COV) for urinary incontinence (UI) using the Expanded Prostate Cancer Composite (EPIC) score after radical prostatectomy (RP). METHODS: From 2004-2013, all RP patients at our institution completed the EPIC urinary domain (EPIC-UD) questionnaire preoperatively and 6 weeks; 3, 6, 9, 12, and 18 months postoperatively; and yearly thereafter. The EPIC-UD is composed of several questions, 4 of which address UI qualitatively (EPIC-UI). Furthermore, patients were asked to complete a global quality of life (QoL) questionnaire regarding continence. The EPIC COV was calculated using receiver operating characteristic (ROC) analysis. Correlations between the EPIC-UI and quantitative QoL were evaluated using the Kendall-Tau test. RESULTS: We analyzed 239 patients with a median age of 63 years (interquartile range [IQR], 59-66 years), a median follow-up of 48 months (IQR, 30-78 months) and a median preoperative EPIC-UI score of 100 (IQR, 91.75-100). The ROC analysis for the distinction between EPIC-UI and the use of ≤1 pad/day yielded an EPIC-UI COV of >85, which we termed the UI-85, with an area under the curve of 0.857 (P<0.0001). A stronger correlation was seen between QoL scores and the UI-85 (1 year postoperatively: correlation coefficient [CC], 0.592; P<0.0001) than between QoL and not using a pad (CC, 0.512; P<0.0001). CONCLUSIONS: The calculated COV of the EPIC-UI for continence was 85. UI is a multidimensional condition that cannot be adequately characterized by a single piece of information, such as pad usage only. Hence, the UI-85 represents a nuanced and straightforward tool for monitoring and comparing continence between different time points and cohorts in a multidimensional and objective manner

Intrafascial Supracervical Hysterectomy Without Colpotomy and Transuterine Mucosal Resection by Pelviscopy and Laparotomy

Between September 1991 and December 1993, 253 patients were operated on using the Classical Intrafascial SEMM (Serrated Edged Macro Morcellator) Hysterectomy (CISH) technique. One hundred fifty-two patients were assigned to pelviscopic CISH and 101 to laparotomic CISH. Uterine leiomyomas with menstrual disorders and pressure symptoms topped the list of indications with 61%. In all cases, initially transuterine mucosal resection and coring of the cervicouterine cylinder were carried out followed by the intrafascial supracervical dissection of the uterus. The size of the uterus played a decisive role in selecting the cases for CISH technique either by pelviscopy or laparotomy. The cervicouterine mucosal cylinders were cored using the Calibrated Uterine Resection Tool (CURT). Cervical thickness and diameters were measured preoperatively by transvaginal sonography for facilitating the use of a specific-sized CURT. After removal of this cylinder, hemostasis in the area was secured by coagulating with an endocoagulation device. The advantage of this technique is that the pelvic floor integrity remains intact, and because uterine arteries and ureters were not touched, the so called “complication zone” is thus avoided

Towards a classification framework for approaches to enterprise architecture analysis

Analysis is an important part of the Enterprise Architecture Management Process. Prior to decisions regarding transformation of the Enterprise Architecture, the current situation and the outcomes of alternative action plans have to be analyzed. Many analysis approaches have been proposed by researchers and current Enterprise Architecture Management tools implement Analysis functionalities. However, few work has been done structuring and classifying Enterprise Architecture Analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for Enterprise Architecture Analysis classification. For evaluation, a collection of Enterprise Architecture Analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for Enterprise Architecture Analysis classification has been derived and suggestions for further development are drawn

Evaluation of algorithms for interaction-sparse recommendations : neural networks don’t always win

In recent years, top-K recommender systems with implicit feedback data gained interest in many real-world business scenarios. In particular, neural networks have shown promising results on these tasks. However, while traditional recommender systems are built on datasets with frequent user interactions, insurance recommenders often have access to a very limited amount of user interactions, as people only buy a few insurance products. In this paper, we shed new light on the problem of top-K recommendations for interaction-sparse recommender problems. In particular, we analyze six different recommender algorithms, namely a popularity-based baseline and compare it against two matrix factorization methods (SVD++, ALS), one neural network approach (JCA) and two combinations of neural network and factorization machine approaches (DeepFM, NeuFM). We evaluate these algorithms on six different interaction-sparse datasets and one dataset with a less sparse interaction pattern to elucidate the unique behavior of interaction-sparse datasets. In our experimental evaluation based on real-world insurance data, we demonstrate that DeepFM shows the best performance followed by JCA and SVD++, which indicates that neural network approaches are the dominant technologies. However, for the remaining five datasets we observe a different pattern. Overall, the matrix factorization method SVD++ is the winner. Surprisingly, the simple popularity-based approach comes out second followed by the neural network approach JCA. In summary, our experimental evaluation for interaction-sparse datasets demonstrates that in general matrix factorization methods outperform neural network approaches. As a consequence, traditional well-established methods should be part of the portfolio of algorithms to solve real-world interaction-sparse recommender problems