nils-herrmann/clean_scirepeval huggingface dataset:
Human Character Recognition by Handwriting using Fuzzy Logic Ms .

Handwritten characters recognition is one of the most challenging & burning topic in the field of image processing & pattern recognition. The most prominent problem in handwriting recognition is the vast variation in personal writing styles. There are also a lot of variations within the writing style of person to person. These variations depend on things like the context of the writing, the writing equipment, the writing situation, and the mood of the writer. The writing style may also evolve with time or practice. Thus, the performance of the automatic recognition of handwriting with their behavior heavily depends on how well the different personal writing styles and their variations are modeled with base of fuzzy rules. Moreover this application can be used in image processing & pattern recognition. Proposed system is used to identify human behavior based on the styles of handwriting, digits & signature.
The adoption of electronic tax filing systems: an empirical study

This paper discusses the factors affecting the adoption of electronic tax-filing systems. Using the technology acceptance model (TAM) as a theoretical framework, this study introduces “perceived credibility” as a new factor that reflects the user’s intrinsic belief in the electronic tax-filing systems, and examines the effect of computer self-efficacy on the intention to use an electronic tax-filing system. Based on a sample of 260 users from a telephone interview, the results strongly support the extended TAM in predicting the intention of users to adopt electronic tax-filing systems. The results also demonstrate the significant effect that computer self-efficacy has on behavioral intention through perceived ease of use, perceived usefulness, and perceived credibility. Based on the findings of this study, implications for electronic tax filing in particular and for e-government services in general are discussed. Finally, this paper concludes by discussing limitations that could be addressed in future studies.
Inverse reinforcement learning for interactive systems

Human machine interaction is a field where machine learning is present at almost any level, from human activity recognition to natural language generation. The interaction manager is probably one of the latest components of an interactive system that benefited from machine learning techniques. In the late 90's, sequential decision making algorithms like reinforcement learning have been introduced in the field with the aim of making the interaction more natural in a measurable way. Yet, these algorithms require providing the learning agent with a reward after each interaction. This reward is generally handcrafted by the system designer who introduces again some expertise in the system. In this paper, we will discuss a method for learning a reward function by observing expert humans, namely inverse reinforcement learning (IRL). IRL will then be applied to several steps of the spoken dialogue management design such as user simulation and clustering but also to co-adaptation of human user and machine.
Low complexity photo sensor dead pixel detection algorithm

Although the number of pixels in image sensors is increasing exponentially, production techniques have only been able to linearly reduce the probability that a pixel will be defective. The result is a rapidly increasing probability that a sensor will contain one or more defective pixels. The defect pixel detection and defect pixel correction are operated separately but the former must employ before the latter is in use. Traditional detection scheme, which finds the defect pixels during manufacturing, is not able to discover the spread defect pixels years late. Consequently, the lifetime and robust defect pixel detection technique, which identifies the fault pixels when camera is in use, is more practical and developed. The paper presents a two stages dead pixel detection technique without complicated mathematic computations so that the embedded devices can easily implement it. Using six dead pixel types are tested and the experimental result indicates that it can be accelerated more than four times the detection time.
Improved Forms for Controlling the Acrobot with Motors of Atypical Size Using Artificial Intelligence Techniques

An acrobot is a planar robot with a passive actuator in its first joint. The control problem of the acrobot tries to make it rise from the rest position to the inverted pendulum position. This control problem can be divided in the swing-up problem, when the robot has to rise itself through swinging up as a human acrobat does, and the balancing problem, when the robot has to maintain itself on the inverted pendulum position. We have developed three controllers for the swing-up problem applied to two types of motors: small and big. For small motors, we used the SARSA controller and the PD with a trajectory generator. For big motors, we propose a new controller to control the acrobot, a PWM controller. All controllers except SARSA are tuned using a Genetic Algorithm.
Sleep quality and academic performance of nursing students

Quality of sleep is one of the important elements of the learning process and memory. However, sleep problems are prominent among college students, which could affect their academic performance. The aim of this study wasto identify the association between quality of sleep and its impact towards academic performance among nursing students at the Faculty of Nursing in International Islamic University, Malaysia (IIUM). A quantitative, cross-sectional study was conducted in the Facultyof Nursing at Jalan Hospital Campus. There were 105 nursing students involved as participants and they were selected by using the convenience sampling method. The questionnaires consisted of three parts; Socio-demographic (age, gender, level of study and participation in extracurricular activities), Pittsburgh Sleep Quality Index (PSQI) and Academic performance (GPA). About 48.6% out ofa total of 105 nursing students had a PSQI score of five and more which means ‘good sleep quality’ and 51.4% had a score of less than 5 which means ‘poor sleep quality’. The result showed that there was a significant association between sleep quality and academic performance. The findings provide information regarding sleep quality of students in the Faculty of Nursing and its impact towards academic performance. Thus, it is recommended for responsible parties to design and implement appropriate interventions to improve sleep quality for academic performance enhancement.
Computer Vision Based Novel Steering Angle Calculation for Autonomous Vehicles

A key requirement in the development of intelligent and driverless vehicles is steering angle computation for efficient navigation. This paper presents a novel method for computing steering angle for driverless vehicles using computer vision based techniques of relatively lower computing cost. The proposed system consists of three major stages. The first stage includes Dynamic Road region extraction using Gaussian Mixture Model and Expectation Maximization algorithm. The second stage is to compute the steering angle based on the extracted roadregion. In addition, Kalman filtering technique is used to cancel spurious angle transition noises. The proposed algorithm was tested both on a simulator and real-time images and was found to give a good estimation of actual steering angle required for navigation. Further, it was also observed that this works in different lighting conditions as well as for both structured and unstructured road scenarios.
Rehabilitation robots assisting in walking training for SCI patient

We have been developing a series of robots to apply for each step of spinal cord injury (SCI) recovery. We describe the preliminary walking pattern assisting robot and the practical walking assisting robot, which will be applied to the incomplete type of SCI to Quadriplegia. The preliminary experimental results are performed by normal subjects to verify the basic functions of the robot assisting and to prepare the test by SCI patients.
Weakly Supervised Affordance Detection

Localizing functional regions of objects or affordances is an important aspect of scene understanding and relevant for many robotics applications. In this work, we introduce a pixel-wise annotated affordance dataset of 3090 images containing 9916 object instances. Since parts of an object can have multiple affordances, we address this by a convolutional neural network for multilabel affordance segmentation. We also propose an approach to train the network from very few keypoint annotations. Our approach achieves a higher affordance detection accuracy than other weakly supervised methods that also rely on keypoint annotations or image annotations as weak supervision.
Analysis and modelling of broad-band ferrite-based coaxial transmission-line transformers

The work presented in the paper focuses on accuracy of models for broad-band ferrite based coaxial transmission-line transformers. Soft-ferrites are largely used in VHF/UHF components allowing band enlargement on the low-edge side. Degradation of frequency performance on the high-edge side are produced both by ferrite losses, and by parasitic capacitance due to connection to the thermal and electrical ground in high power applications. Both a circuital model for low-power applications and a scalable e.m. model for high-power applications are presented and discussed.
Comparative Analysis of Intelligent Transportation Systems for Sustainable Environment in Smart Cities

In recent works on the Internet of Vehicles (IoV), “intelligent” and “sustainable” have been the buzzwords in the context of transportation. Maintaining sustainability in IoV is always a challenge. Sustainability in IoV can be achieved not only by the use of pollution-free vehicular systems, but also by maintenance of road traffic safety or prevention of accidents or collisions. With the aim of establishing an effective sustainable transportation planning system, this study performs a short analysis of existing sustainable transportation methods in the IoV. This study also analyzes various characteristics of sustainability and the advantages and disadvantages of existing transportation systems. Toward the end, this study provides a clear suggestion for effective sustainable transportation planning aimed at the maintenance of an eco-friendly environment and road traffic safety, which, in turn, would lead to a sustainable transportation system.
Mathematical Modeling of Hexacopter

The purpose of this paper is to present the basic mathematical modeling of microcopters, which could be used to develop proper methods for stabilization and trajectory control. The microcopter taken into account consists of six rotors, with three pairs of counter-rotating fixedpitch blades. The microcopter is controlled by adjusting the angular velocities of the rotors which are spun by electric motors. It is assumed as a rigid body, so the differential equations of the microcopter dynamics can be derived from both the Newton-Euler and Euler-Lagrange equations. Euler-angle parametrization of three-dimensional rotations contains singular points in the coordinate space that can cause failure of both dynamical model and control. In order to avoid singularities, the rotations of the microcopter are parametrized in terms of quaternions. This choice has been made taking into consideration the linearity of quaternion formulation, their stability and efficiency.
Knowledge-Based Distant Regularization in Learning Probabilistic Models

Exploiting the appropriate inductive bias based on the knowledge of data is essential for achieving good performance in statistical machine learning. In practice, however, the domain knowledge of interest often provides information on the relationship of data attributes only distantly, which hinders direct utilization of such domain knowledge in popular regularization methods. In this paper, we propose the knowledge-based distant regularization framework, in which we utilize the distant information encoded in a knowledge graph for regularization of probabilistic model estimation. In particular, we propose to impose prior distributions on model parameters specified by knowledge graph embeddings. As an instance of the proposed framework, we present the factor analysis model with the knowledge-based distant regularization. We show the results of preliminary experiments on the improvement of the generalization capability of such model.
Microstrip Patch Antenna With Defected Ground Structure for Cross Polarization Suppression

A defected ground structure (DGS) is proposed to reduce the cross-polarized (XP) radiation of a microstrip patch antenna. The proposed DGS pattern is simple and easy to etch on a commercial microstrip substrate. This will only reduce the XP radiation field without affecting the dominant mode input impedance and co-polarized radiation patterns of a conventional antenna. The new concept has been examined and verified experimentally for a particular DGS pattern employing a circular patch as the radiator. Both simulation and experimental results are presented.
Foofah: A Programming-By-Example System for Synthesizing Data Transformation Programs

Advancements in new data analysis and visualization technologies have resulted in wide applicability of data-driven decision making. However, raw data from various sources must be wrangled into a suitable form before they are processed by the downstream data tools. People traditionally write data transformation programs to automate this process, and such work is cumbersome and tedious.
 We built a system called FOOFAH for helping the user easily synthesize a desired data transformation program. Our system minimizes the user's effort by only asking for a small illustrative example comprised of the raw input data and the target transformed output; FOOFAH then synthesizes a program that can perform the desired data transformation. This demonstration showcases how the user can apply FOOFAH to real-world data transformation tasks.
Lessons from Hereditary Colorectal Cancer

that demonstrated tight linkage of the disease to markers on chromosome 5q21 (Bodmer et al., 1987; Leppert *The Johns Hopkins Oncology Center † Howard Hughes Medical Institute et al., 1987). Following the path demarcated by germline alterations in FAP patients and somatic alterations in 424 North Bond Street Baltimore, Maryland 21231 sporadic colorectal tumors, it became possible to identify the adenomatous polyposis coli (APC) gene and to prove that it caused FAP by demonstrating cosegrega-A large body of evidence supports the idea that accumu-tion of mutant APC alleles in affected kindreds (Groden lated genetic changes underlie the development of neo-et al., 1991; Nishisho et al., 1991). plasia. This multistep process is well illustrated by colo-rectal cancers, which typically develop over decades and appear to require at least seven genetic events for Rate-Limiting Events in Tumorigenesis completion. Even so, inheritance of a single altered gene Patients with germline mutations of APC do not neces-can result in a marked predisposition to colorectal can-sarily develop colorectal cancer; they simply are at much cer in two distinct syndromes, Familial Adenomatous greater risk to do so than the general population. In Polyposis (FAP) and Hereditary Nonpolyposis Colo-order for tumors to form, additional genetic alterations rectal Cancer (HNPCC). Recent evidence suggests that are apparently required. Thus, although FAP patients the genetic defect in FAP affects the rate of tumor initia-each develop numerous colorectal tumors, only about tion by targeting the gatekeeper function of the APC 1 of every 10 6 colorectal epithelial stem cells gives rise gene. In contrast, the defect in HNPCC largely affects to such a tumor. Studies in humans with FAP, as well tumor progression by targeting the genome guardian as in mice with analogous mutations of the murine ho-function of DNA mismatch repair. Studies of these syn-molog of APC, have suggested that the rate-limiting dromes have provided unique insights into both inher-step in tumor initiation is a somatic mutation of the wild-ited and sporadic forms of human tumors.  APC allele inherited from the unaffected parent The small fraction of colorectal epithelial stem cells that Introduction become neoplastic is in reasonable accord with the low At least 50% of the Western population develops a colo-rate of somatic mutation of APC expected in normal rectal tumor by the age of 70, and in about 1 in 10 of colon cells. Thus, the study of FAP provides strong sup-these individuals, progression to malignancy ensues. …
A Survey of Utility-Oriented Pattern Mining

The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge. For identifying and evaluating the usefulness of different kinds of patterns, many techniques/constraints have been proposed, such as support, confidence, sequence order, and utility parameters (e.g., weight, price, profit, quantity, etc.). In recent years, there has been an increasing demand for utility-oriented pattern mining (UPM). UPM is a vital task, with numerous high-impact applications, including cross-marketing, e-commerce, finance, medical, and biomedical applications. This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods of UPM. First, we introduce an in-depth understanding of UPM, including concepts, examples, and comparisons with related concepts. A taxonomy of the most common and state-of-the-art approaches for mining different kinds of high-utility patterns is presented, including Apriori-based, tree-based, projection-based, vertical-/horizontal-data-format-based, and other hybrid approaches. A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons. Finally, we present several well-known open-source software packages for UPM. We conclude our survey with a discussion on open and practical challenges in this field.
Modelling and control of a 2-DOF planar parallel manipulator for semiconductor packaging systems

A novel direct-drive planar parallel manipulator for high-speed and high-precision semiconductor packaging systems is presented. High precision kinematics design, significant reduction on moving mass and driving power of the actuators over traditional XY motion stages are the benefits of the proposed manipulator. The mathematical model of the manipulator is obtained using the Newton-Euler method and a practical model-based control design approach is employed to design the PID computed-torque controller. Experimental results demonstrate that the proposed planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY stages. This shows that the proposed planar parallel manipulator can provide a superior alternative for replacing traditional XY motion stages in high precision low-payload applications
EssayCritic: Writing to Learn with a Knowledge-Based Design Critiquing System

This article presents a study of EssayCritic, a computer-based writing aid for English as a foreign language (EFL) that provides feedback on the content of English essays. We compared two feedback conditions: automated feedback from EssayCritic (target class) and feedback from collaborating peers (comparison class). We used a mixed methods approach to collect and analyze the data, combining interaction analysis of classroom conversations during the writing process and statistical analysis of students’ grades. The grades of students in both classes improved from pre-test to post-test but in different ways. The students in the target class included more ideas (content) in their essays, whereas the students in the comparison class put more emphasis on the organization of their ideas. We discuss our findings to identify strengths and weaknesses of our approach, and we end the paper by suggesting some directions for further research.
Implementing the "GrabCut" segmentation technique as a plugin for the GIMP

Image segmentation requires a segmentation tool that is fast and easy to use. The GIMP has built in segmentation tools, but under some circumstances these tools perform badly. "GrabCut" is an innovative segmentation technique that uses both region and boundary information in order to perform segmentation. Several variations on the "GrabCut" algorithm have been implemented as a plugin for the GIMP. The results obtained using "GrabCut" are comparable, and often better than the results of all the other built in segmentation tools.
Parents ’ Intelligence Mindsets Relate to Child Internalizing Problems : Moderation Through Child Gender

Parental belief systems can strongly influence children’s affect, behavior, and mental health. However, associations between specific kinds of parental beliefs and children’s mental health have not been thoroughly explored. One relevant belief system is parental intelligence mindset: beliefs about the malleability of intelligence. Children of parents who view intelligence as static (known as a fixed intelligence mindset), rather than malleable through effort (known as a growth intelligence mindset), experience more academic, self-regulatory, and motivational difficulty. However, associations between parental intelligence mindset and child mental health problems are unclear. Accordingly, we tested whether parents’ intelligence mindsets related to internalizing problems in their children (N= 131, ages 5–8). Overall, parents with stronger fixed intelligence mindsets had children with greater internalizing problems, particularly social anxiety (characterized by fear of negative evaluation). Results further revealed that parents’ fixed intelligence mindsets were associated with overall internalizing problems and depressive symptoms in boys, but not girls. Results are the first to suggest and parse direct links between parents’ intelligence mindsets and youth internalizing problems.
REVIEW OF PROVEN TECHNOLOGIES AVAILABLE FOR THE REDUCTION OF RAW SUGAR COLOUR

Colour removal is the chief cost centre of sugar re fineries, hence, by reducing the colour of the raw sugar to be processed, the level of process ing and costs incurred by a refinery are also reduced. A lower colour raw sugar is thus highly ma rketable. There are a number of proven technologies that can be applied in raw sugar mills to control and reduce raw sugar colour. These mechanisms are r eviewed in order to identify effective and economically viable means of reducing the colou r f South African raw sugars to a reasonable level, ca 1 000 ICUMSA units. The technologies include: • syrup flotation clarification • juice and syrup sulphitation • alternative boiling schemes • double curing of C-massecuites • additional washing in centrifugals • the use of specialised chemicals and flocculants du ring clarification • hydrogen peroxide in wash water during centrifugati on.
A practical approach for content mining of Tweets.

Use of data generated through social media for health studies is gradually increasing. Twitter is a short-text message system developed 6 years ago, now with more than 100 million users generating over 300 million Tweets every day. Twitter may be used to gain real-world insights to promote healthy behaviors. The purposes of this paper are to describe a practical approach to analyzing Tweet contents and to illustrate an application of the approach to the topic of physical activity. The approach includes five steps: (1) selecting keywords to gather an initial set of Tweets to analyze; (2) importing data; (3) preparing data; (4) analyzing data (topic, sentiment, and ecologic context); and (5) interpreting data. The steps are implemented using tools that are publically available and free of charge and designed for use by researchers with limited programming skills. Content mining of Tweets can contribute to addressing challenges in health behavior research.