nils-herrmann/clean_scirepeval huggingface dataset:
Deviation-based and similarity-based contextual SLIM recommendation algorithms

Context-aware recommender systems (CARS) have been demonstrated to be able to enhance recommendations by adapting users' preferences to different contextual situations. In recent years, several CARS algorithms have been developed to incorporated into the recommender systems. For example, differential context modeling (DCM) was modified based on traditional neighborhood collaborative filtering (NBCF), context-aware matrix factorization (CAMF) coupled contextual dependency with the matrix factorization technique (MF), and tensor factorization directly models contexts as additional dimensions in the multi-dimensional space, etc. CAMF works well but it is difficult to interpret the latent features in the algorithm. DCM is good for explanation but it may only work well on data sets with dense contextual ratings. Recently, we successfully incorporate contexts into Sparse LInear Method (SLIM) and develop contextual SLIM (CSLIM) recommendation algorithms which take advantages of both NBCF and MF. CSLIM are demonstrated as more effective and promising context-aware recommenders. In this work, we provide the introduction on the framework of the CSLIM algorithms, present the current state of the research, and discuss our ongoing future work to develop and improve our CSLIM models for context-aware recommendations.
A Low-Profile Unidirectional Printed Antenna for Millimeter-Wave Applications

By combining a printed reflector-backed one-wave-length bowtie antenna and a printed double loop antenna, a new wideband high-gain antenna element is demonstrated. Due to its low-profile structure of ~ 0.05λ0, it is attractive to be used in an array environment. Experimentally, a series of antenna arrays operated at 60 GHz are designed and fabricated. They achieve wide impedance bandwidths covering the 57-64 GHz unlicensed frequency band. Over this band, the measured antenna gains are ranged from 14.5-15.5 dBi, 18.3-20.1 dBi and 22.5-25.2 dBi for 4-element, 14-element and 50-element antenna arrays, respectively. The measured radiation pattern has low cross-polarization level and low back radiation. The proposed low-profile antenna and arrays are low-cost in fabrication as they are simply made on a single-layer printed circuit board.
Six steps to the "perfect" lip.

Full lips have always been associated with youth and beauty. Because of this, lip enhancement is one of the most frequently requested procedures in a cosmetic practice. For novice injectors, we recommend hyaluronic acid (HA) as the filler of choice. There is no skin test required; it is an easily obtainable, "off-the-shelf" product that is natural feeling when skillfully implanted in the soft tissues. Hyaluronic acid is easily reversible with hyaluronidase and, therefore, has an excellent safety profile. While Restylane® is the only FDA-approved HA filler with a specific indication for lip augmentation, one can use the following HA products off-label: Juvéderm® Ultra, Juvéderm Ultra Plus, Juvéderm Ultra XC, Juvéderm Ultra PLUS XC, Restylane-L®, Perlane®, Perlane-L®, and Belotero®. We present our six steps to achieve aesthetically pleasing augmented lips. While there is no single prescription for a "perfect" lip, nor a "one size fits all" approach for lip augmentation, these 6 steps can be used as a basic template for achieving a natural look. For more comprehensive, global perioral rejuvenation, our 6-step technique can be combined with the injection of neuromodulating agents and fractional laser skin resurfacing during the same treatment session.
Personality classification based on Twitter text using Naive Bayes, KNN and SVM

Personality is a fundamental basis of human behavior. Personality affects the interaction and preferences of an individual. People are required to take a personality test to find out their personality. Social media is a place where users express themselves to the world. Posts made by users of social media can be analyzed to obtain their personal information. This experiment uses text classification to predict personality based on text written by Twitter users. The languages used are English and Indonesian. Classification methods implemented are Naive Bayes, K-Nearest Neighbors and Support Vector Machine. Testing results showed Naive Bayes slightly outperformed the other methods.
Shielding-cancellation technique for suppressing common mode EMI in isolated power converters

In an isolated power converter, the inter-winding capacitances of the power transformer are critical parasitic capacitances for the generating of common mode (CM) noise. To suppress the CM noise in isolated power converters, shielding-cancellation (SC) technique is proposed in this paper. The SC technique is realized by introducing noise cancellation on the basis of shielding, and it is easy to be implemented, suitable for various isolated power converters and independent of the transformer inter-winding capacitance. To verify the effectiveness of the SC technique on suppressing the CM noise, a flyback converter prototype is built, and the CM noise of the converter is measured and compared using three different transformers. It is revealed that the CM noise of the converter, which utilizes the transformer with SC technique, is lower than that using the transformer without shielding or with traditional shielding layers.
Detection of phishing emails using data mining algorithms

This paper proposes an intelligent model for detection of phishing emails which depends on a preprocessing phase that extracts a set of features concerning different email parts. The extracted features are classified using the J48 classification algorithm. We experimented with a total of 23 features that have been used in the literature. Ten-fold cross-validation was applied for training, testing and validation. The primary focus of this paper is to enhance the overall metrics values of email classification by focusing on the preprocessing phase and determine the best algorithm that can be used in this field. The results show the benefits of using our preprocessing phase to extract features from the dataset. The model achieved 98.87% accuracy for the random forest algorithm, which is the highest registered so far for an approved dataset. A comparison of ten different classification algorithms demonstrates their merits and capabilities through a set of experiments.
Ca.U.M.Ha. robotic hand (Cassino-Underactuated-Multifinger-Hand)

The mechatronic design of Ca.U.M.Ha.  and the analysis of some experimental grasping tests of a built prototype are presented in this paper. Ca.U.M.Ha. robotic hand shows an anthropomorphic design since provided of four articulated fingers and a simplified contrasting thumb, which are all joined to a rigid palm. The main characteristics of Ca.U.M.Ha. are the underactuation of each finger mechanism with three phalanxes and the common operation through PWM (pulse- width-modulation) modulated pneumatic digital valves of the four articulated fingers with pneumatic actuation. The actuation force control of Ca.U.M.Ha. is obtained by controlling the pressure in the pushing chambers of the pneumatic actuators.
Pulse-Modulated Intermittent Control in Consensus of Multiagent Systems

This paper proposes a control framework, called pulse-modulated intermittent control, which unifies impulsive control and sampled control. Specifically, the concept of pulse function is introduced to characterize the control/rest intervals and the amplitude of the control. By choosing some specified functions as the pulse function, the proposed control scheme can be reduced to sampled control or impulsive control. The proposed control framework is applied to consensus problems of multiagent systems. Using discretization approaches and stability theory, several necessary and sufficient conditions are established to ensure the consensus of the controlled system. The results show that consensus depends not only on the network topology, the sampling period and the control gains, but also the pulse function. Moreover, a lower bound of the asymptotic convergence factor is derived as well. For a given pulse function and an undirected graph, an optimal control gain is designed to achieve the fastest convergence. In addition, impulsive control and sampled control are revisited in the proposed control framework. Finally, some numerical examples are given to verify the effectiveness of theoretical results.
Perception-Based Evaluation of Projection Methods for Multidimensional Data Visualization

Similarity-based layouts generated by multidimensional projections or other dimension reduction techniques are commonly used to visualize high-dimensional data. Many projection techniques have been recently proposed addressing different objectives and application domains. Nonetheless, very little is known about the effectiveness of the generated layouts from a user's perspective, how distinct layouts from the same data compare regarding the typical visualization tasks they support, or how domain-specific issues affect the outcome of the techniques. Learning more about projection usage is an important step towards both consolidating their role in high-dimensional data analysis and taking informed decisions when choosing techniques. This work provides a contribution towards this goal. We describe the results of an investigation on the performance of layouts generated by projection techniques as perceived by their users. We conducted a controlled user study to test against the following hypotheses: (1) projection performance is task-dependent; (2) certain projections perform better on certain types of tasks; (3) projection performance depends on the nature of the data; and (4) subjects prefer projections with good segregation capability. We generated layouts of high-dimensional data with five techniques representative of different projection approaches. As application domains we investigated image and document data. We identified eight typical tasks, three of them related to segregation capability of the projection, three related to projection precision, and two related to incurred visual cluttering. Answers to questions were compared for correctness against `ground truth' computed directly from the data. We also looked at subject confidence and task completion times. Statistical analysis of the collected data resulted in Hypotheses 1 and 3 being confirmed, Hypothesis 2 being confirmed partially and Hypotheses 4 could not be confirmed. We discuss our findings in comparison with some numerical measures of projection layout quality. Our results offer interesting insight on the use of projection layouts in data visualization tasks and provide a departing point for further systematic investigations.
The KDD Process for Extracting Useful Knowledge from Volumes of Data

AS WE MARCH INTO THE AGE of digital information, the problem of data overload looms ominously ahead. Our ability to analyze and understand massive datasets lags far behind our ability to gather and store the data. A new generation of computational techniques and tools is required to support the extraction of useful knowledge from the rapidly growing volumes of data. These techniques and tools are the subject of the emerging field of knowledge discovery in databases (KDD) and data mining. Large databases of digital information are ubiquitous. Data from the neighborhood store’s checkout register, your bank’s credit card authorization device, records in your doctor’s office, patterns in your telephone calls, and many more applications generate streams of digital records archived in huge databases, sometimes in so-called data warehouses. Current hardware and database technology allow efficient and inexpensive reliable data storage and access. However, whether the context is business, medicine, science, or government, the datasets themselves (in raw form) are of little direct value. What is of value is the knowledge that can be inferred from the data and put to use. For example, the marketing database of a consumer U s a m a F a y y a d ,
The weight of author self-citations. A fractional approach to self-citation counting

The discussion about how to treat author self-citations driven by policy application and quality measurement intensified in the last years. The definition introduced by Snyder and Bonzi has — in lack of any reasonable alternative — been used in bibliometric practice for science policy purposes. This method, however, does not take into account the weight of self-citing authors among coauthors of both the cited and citing papers. The objective of the present paper is to quantify the weight of self-citations with respect to co-authorship. The analysis is conducted at two levels: at the macro level, namely, for fifteen subject fields and the most active forty countries, and at the meso level, for a set of selected research institutions.
FHE over the Integers: Decomposed and Batched in the Post-Quantum Regime

Fully homomorphic encryption over the integers (FHE-OI) is currently the only alternative to lattice-based FHE. FHE-OI includes a family of schemes whose security is based on the hardness of different variants of the approximate greatest common divisor (AGCD) problem. The majority of these works is based on the noise-free variant of AGCD which is potentially weaker than the general one. In particular, the noise-free variant relies on the hardness of factoring and is thus vulnerable to quantum attacks. A lot of effort was made to port techniques from second generation lattice-based FHE (using tensoring) to FHE-OI. Gentry, Sahai and Waters (Crypto 13) showed that third generation techniques (which were later formalized using the “gadget matrix”) can also be ported. In this work, we propose a comprehensive study of applying third generation FHE techniques to the regime of FHE-OI. We present and analyze a third generation FHE-OI based on decisional AGCD without the noise-free assumption. We proceed to showing a batch version of our scheme where each ciphertext can encode a vector of messages and operations are performed coordinate-wise. We use a similar AGCD variant to Cheon et al. (Eurocrypt 13) who suggested the batch approach for second generation FHE, but we do not require the noise-free component or a subset sum assumption. However, like Cheon et al., we do require circular security for our scheme, even for bounded homomorphism. Lastly, we discuss some of the obstacles towards efficient implementation of our schemes and discuss a number of possible optimizations.
A particle swarm optimization algorithm for flexible job shop scheduling problem

The classical job shop scheduling problem (JSP) is the most popular machine scheduling model in practice and is well known as NP-hard. The formulation of the JSP is based on the assumption that for each part type or job there is only one process plan that prescribes the sequence of operations and the machine on which each operation has to be performed. Flexible job shop scheduling problem (FJSP) is an extension of the JSP, which allows an operation to be processed by any machine from a given set. Since FJSP requires an additional decision of machine allocation during scheduling, therefore it is much more complex problem than JSP. To solve such NP-hard problems, heuristic approaches are commonly preferred over the traditional mathematical techniques. This paper proposes a particle swarm optimization (PSO) based heuristic for solving the FJSP for minimum makespan time criterion. The performance of the proposed PSO is evaluated by comparing its results with the results obtained using ILOG Solver, a constraint-programming tool. The comparison of the results proves the effectiveness of the proposed PSO for solving FJSP instances.
UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems

We describe three semantic text similarity systems developed for the *SEM 2013 STS shared task and the results of the corresponding three runs. All of them shared a word similarity feature that combined LSA word similarity and WordNet knowledge. The first, which achieved the best mean score of the 89 submitted runs, used a simple term alignment algorithm augmented with penalty terms. The other two runs, ranked second and fourth, used support vector regression models to combine larger sets of features.
Penile septoplasty for congenital ventral penile curvature: results in 51 patients.

The technique most widely used to correct congenital ventral penile curvature is still corporoplasty as originally described by Nesbit. We present results in patients treated with a variation of Nesbit corporoplasty used specifically for congenital ventral penile curvature.



From June 2000 to June 2007 we treated 51 patients with congenital ventral penile curvature using modified corporoplasty (septoplasty), consisting of accessing the bed of the penile dorsal vein and excising 1 or more diamonds of tunica albuginea from it, extending in wedge-like formation 4 to 5 mm deep into the septum, until the penis is completely straightened. Patient history, clinical findings, self-photography results and the International Index of Erectile Function score were assessed. Curvature grade is expressed using the equation, 180 degrees - X, where X represents the deviation in degrees from the penis axis. Mean preoperative ventral curvature was 131.4 degrees (median 135, range 145 to 110). Of the patients 13 also had erectile dysfunction.



At followup postoperative mean ventral curvature was 178.3 degrees (median 179.1, range 180 to 175). A total of 49 stated that they were completely satisfied. Penile shortening was 5 to 15 mm. Compared to preoperative values there were marked improvements in the International Index of Erectile Function score in the various groups. No major postoperative complications developed. In 4 patients wound healing occurred by secondary intent.



This technique provides excellent straightening of the curved penis. By avoiding isolation of the whole dorsal neurovascular bundle there is no risk of neurovascular lesions. Suture perception is minimized.
3D Pose tracking of walker users' lower limb with a structured-light camera on a moving platform

Tracking and understanding human gait is an important step towards improving elderly mobility and safety. Our research team is developing a vision-based tracking system that estimates the 3D pose of a wheeled walker user's lower limbs with a depth sensor, Kinect, mounted on the moving walker. Our tracker estimates 3D poses from depth images of the lower limbs in the coronal plane in a dynamic, uncontrolled environment. We employ a probabilistic approach based on particle filtering, with a measurement model that works directly in the 3D space and another measurement model that works in the projected image space. Empirical results show that combining both measurements, assuming independence between them, yields tracking results that are better than with either one alone. Experiments are conducted to evaluate the performance of the tracking system with different users. We demonstrate that the tracker is robust against unfavorable conditions such as partial occlusion, missing observations, and deformable tracking target. Also, our tracker does not require user intervention or manual initialization commonly required in most trackers.
A Software Defined Networking architecture for the Internet-of-Things

The growing interest in the Internet of Things (IoT) has resulted in a number of wide-area deployments of IoT subnetworks, where multiple heterogeneous wireless communication solutions coexist: from multiple access technologies such as cellular, WiFi, ZigBee, and Bluetooth, to multi-hop ad-hoc and MANET routing protocols, they all must be effectively integrated to create a seamless communication platform. Managing these open, geographically distributed, and heterogeneous networking infrastructures, especially in dynamic environments, is a key technical challenge. In order to take full advantage of the many opportunities they provide, techniques to concurrently provision the different classes of IoT traffic across a common set of sensors and networking resources must be designed. In this paper, we will design a software-defined approach for the IoT environment to dynamically achieve differentiated quality levels to different IoT tasks in very heterogeneous wireless networking scenarios. For this, we extend the Multinetwork INformation Architecture (MINA), a reflective (self-observing and adapting via an embodied Observe-Analyze-Adapt loop) middleware with a layered IoT SDN controller. The developed IoT SDN controller originally i) incorporates and supports commands to differentiate flow scheduling over task-level, multi-hop, and heterogeneous ad-hoc paths and ii) exploits Network Calculus and Genetic Algorithms to optimize the usage of currently available IoT network opportunities. We have applied the extended MINA SDN prototype in the challenging IoT scenario of wide-scale integration of electric vehicles, electric charging sites, smart grid infrastructures, and a wide set of pilot users, as targeted by the Artemis Internet of Energy and Arrowhead projects. Preliminary simulation performance results indicate that our approach and the extended MINA system can support efficient exploitation of the IoT multinetwork capabilities.
Exact clothing retrieval approach based on deep neural network

In recent years, the trend of shopping for clothing on an onscreen character has been raising. Unfortunately, clothes that appear on screen could be difficult to track down, much less to purchase directly. It is a challenging task to find out exactly what the clothing in a TV show is from massive amounts of clothing items in online clothing retails due to the clearly noticeable visual discrepancies of the same clothing in video and in online shop photos. In order to tackle the problem, we adopt the deep neural network to learn recognizable clothing-specific feature for finding the exact clothing item in the video scenario among a large collection of online shop images. The experiments shows the clothing-specific feature is more effective in retrieval task and color filtering improve the retrieval performance.
Fluid animation with dynamic meshes

This paper presents a method for animating fluid using unstructured tetrahedral meshes that change at each time step. We show that meshes that conform well to changing boundaries and that focus computation in the visually important parts of the domain can be generated quickly and reliably using existing techniques. We also describe a new approach to two-way coupling of fluid and rigid bodies that, while general, benefits from remeshing. Overall, the method provides a flexible environment for creating complex scenes involving fluid animation.
The contribution of peer and media influences to the development of body satisfaction and self-esteem in young girls: a prospective study.

This study aimed to prospectively examine the role of peer and media influences in the development of body satisfaction (incorporating the desire for thinness and satisfaction with appearance) in young girls, as well as the relationship between body satisfaction and self-esteem. A sample of 97 girls 5-8 years of age completed individual interviews at Time 1 and 1 year later at Time 2. Linear panel analyses found that Time 1 perception of peers' desire for thinness was temporally antecedent to girls' desire for thinness, appearance satisfaction, and self-esteem 1 year later. In addition, the watching of appearance-focused television programs was temporally antecedent to appearance satisfaction. Finally, girls' desire for thinness was found to temporally precede low self-esteem. Thus, as early as school entry, girls appear to already live in a culture in which peers and the media transmit the thin ideal in a way that negatively influences the development of body image and self-esteem.