Reviewerly/exHarmony huggingface dataset:
Pencarian Rute Tercepat Mobil Ambulance Menggunakan Algoritma Ant Colony Optimization

One of the services provided by the hospital to patients is an ambulance team that is used as a transport to deliver patients or bodies to hospitals and funeral homes. In the service of ambulance teams requires speed and timeliness in minimizing patient risks. The fastest route is generally based on the shortest distance another point to point. In fact the best route should pay attention to road conditions such as road capacity, many vehicles passing through and so on. The method used for the research is the Ant Coloby Optimization algorithm, the method used is quite easy because it searches in depth with a better quality solution than using conventional conventional search methods so that it aims to design an ambulance route that can minimize the distance to patients and hospitals as a route who most likely have the fastest time.
Inferring Students’ Emotions Using a Hybrid Approach that Combine Cognitive and Physical Data

There are nowadays a strong agreement in the research community that emotions directly impact learning. Then, an important feature for a software that claim to be useful for learning is to deal with students’ affective reactions. These software should be able to adapt to the users’ affective reactions, trying to get a more natural human-computer interaction. Some priors works achieved relative success in inferring students’ emotion. However, most of them, rely on intrusive, expensive or little practical sensors that track students’ physical reactions. This paper presents as its main contribution the proposal of a hybrid model for emotion inference, combining physical and cognitive elements, using cheaper and little intrusive method to collect data. First experiments with students in a traditional classroom demonstrated the feasibility of this proposal and also indicated promising results for inference of learning centered emotions. In these experiments we achieve an accuracy rate and Cohen Kappa near to 65% and 0.55, respectively, in the task of inferring five classes of learning centered emotion. Even though these results are better than some related work, we believe they can be improved in the future by incorporating new data to the model.
Quasi-Automated Firmware in E-Automobiles: Structural Integration

Intelligent transit mechanism has become the need of the hour. The topical panacea seems to centre on the development of labyrinthine Automated Vehicles. With the inevitable boom in areas like Machine Learning, Industrial Automation coupled with highly convergent heuristics and the advent of highly efficient low latency communication devices, the idea of Automated Vehicles inches closer to practical realization every passing day. Design for any vehicle can be described as a function of various interdependent parameters, which are generally defined by the level of convolution and the level of automation defined for a system.This study explores the controller system design of Quasi-Automated Electric Vehicles. Categorically, this paper is an attempt at examining novel and innovative ways of designing a schematic for control of speed and navigation subsystems along with an exhaustive feedback capability designed to give users a real time virtual emulation of the vehicle. A wide ranging discussion on possible topologies for effective implementation of feedback have also been depicted in this paper. A column-type power steering system has been investigated as a control system for navigation of direction while an inverter based speed control mechanism has also been proposed. Furthermore, the discussed control algorithms have been rigorously tested and consequently proved capable of providing 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> level of autonomy, as defined by Society of Automotive Engineers standards while also reflecting a potential schematic for integration of intelligent learning firmware in the near future.
An Efficient Date-constraint Hierarchical Key Management Scheme with Fast Key Validation Checking for Mobile Agents in E-Medicine System

A hierarchical key management scheme for mobile agents in e-medicine system enables users, such as patients, doctors, nurses and health visitors, to conveniently and securely access a remote hierarchical medical database system via public networks. Efficient hierarchical key management schemes do not require heavy computations even if the hierarchical structure has too many levels and participants. Chen et al. recently developed a hierarchical key management scheme with date-constraint for mobile agents. The key management scheme of Chen et al. is based the Elliptic Curve Cryptosystem and allows each secret key to be partnered with a validity period by using one-way hash chains. However, the scheme of Chen et al. fails to execute correctly, violates authenticated key security, and requires hundreds of hash functional operations. This investigation discusses these limitations, and proposes an efficient date-constraint hierarchical key management scheme for mobile agents in e-medicine system, which provides a fast key validation and expiration check phase to rapidly check whether the secret keys are valid and time-expired or not. The proposed key management scheme not only provides more security properties and rapidly checks the validation of secret keys, but also reduces the computational cost..
PENERAPAN DISCOVERY LEARNING TERINTEGRASI STEM UNTUK MENINGKATKAN HASIL BELAJAR PESERTA DIDIK SMP NEGERI 26 PALEMBANG

In the present time, the development of information technology, especially in Indonesia, is growing. With the existence of information and communication technology can make it easier for us to learn and get information that we need from anywhere, anytime, and from anyone. In the education world, the development of information technology has begun to have a positive impact because the development of information technology in the education world has begun to show significant changes. Nowadays distance and time are not significant problems to gain knowledge, various applications are created to facilitate them. Information technology is a technology used to process data, including processing, obtaining, compiling, storing, manipulating data in various ways to produce quality information that is relevant, accurate, and timely information, which is used for personal, business, and government and is strategic information for decision making.
Making Agents’ Abilities Explicit

Alternating-time temporal logics (ATL/ATL*) represent a family of modal and temporal logics for reasoning about strategic abilities of agents in multiagent systems. These logics are usually interpreted over concurrent game structures (CGSs), and their interpretations may vary depending on the abilities of agents, such as perfect versus imperfect information and perfect versus imperfect recall. These different abilities lead to a variety of variants that have been studied extensively in the literature. However, all of these variants are defined at the semantic level, which may restrict modeling flexibility, or even give counter-intuitive interpretations. For example, an agent may have different abilities when achieving two different goals on the same CGS. To mitigate these issues, in this paper, we propose to extend CGSs with agents’ abilities, resulting in Abilities Augmented CGSs, where concrete abilities can be defined at the syntactic level. We study ATL/ATL* over this new model. We give formal definitions of the new semantics and present model-checking algorithms for ATL/ATL*. We also identify the computational complexity of ATL/ATL* model checking problem, i.e., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta _{3}^{\sf P}$ </tex-math></inline-formula> -/2EXPTIME-complete. The model-checking algorithms are implemented in a prototype tool. The experimental results show the practical feasibility and effectiveness of our approach.
Application of Directed Recommendation in Text Manual Annotation

With the increase of network bandwidth and the rapid development of Internet technology, information carriers gradually transition from text to video images. In order to facilitate people to access and retrieve video images faster and better, it is too cumbersome and time-consuming for current manual labeling, the system hopes that through the popular recommendation system and reCAPTCHA system, we can get and the preference of each user with the accumulation of the number of annotations, at the same time, based on the tolerance of the human body, and some of the images are difficult to label that Loaded in an easily labeled images, reduce the number of unlabelable images, shorten the labeling time.
A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement

The measurements of the diameter of different layers, the thickness of different layers and the eccentricity of insulation layer in the cross-section of power cables are important items of power cable test, which currently depend on labor-intensive manual operations. To improve efficiency, automatic measurement methods are in urgent need. In this paper, a monocular vision-based framework for automatic measurement of the diameter, thickness, and eccentricity of interest in the cross-section of power cables is proposed. The proposed framework mainly consists of three steps. In the first step, the images of cable cross-section are captured and undistorted with the camera calibration parameters. In the second step, the contours of each layer are detected in the cable cross-section image. In order to detect the complete and accurate contours of each layer, the structural edges in the cross-section image are firstly detected and divided into individual layers, then unconnected edges are connected by arc-based method, and finally contours are refined by the proposed break detection and grouping (BDG) and linear trend-based correction (LTBC) algorithm. In the third step, the monocular vision-based cross-section dimension measurement is accomplished by placing a chessboard coplanar with the power cable cross-section plane. The homography matrix mapping pixel coordinates to chessboard world coordinates is estimated, and the diameter, thickness and eccentricity of specific layers are calculated by homography matrix-based measurement method. Simulated data and actual cable data are both used to validate the proposed method. The experimental results show that diameter, minimum thickness, mean thickness and insulation eccentricity of simulated image without additive noise are measured with root mean squared error (RMSE) of 0.424, 0.103 and 0.063 mm, and 0.002, respectively, those of simulated image with additive Gaussian noise and salt and pepper noise are measured with RMSE of 0.502, 0.243 and 0.058 mm and 0.001. Diameter, minimum thickness and mean thickness of actual cable images are measured with average RMSE of 0.768, 0.308 and 0.327 mm. The measurement error of insulation eccentricity of actual cable image is comparatively large, and the measurement accuracy should be improved.
Petrology, Geochemistry and Economic Aspects of the Alkaline Dyke in Anta Gorda Region, Doutor Ulysses, Paran&amp;#225;, Brazil

The rock types of the alkaline dyke from Anta Gorda region, in the township of Doutor Ulysses (State of Paraná), encompass three lithological groups that have been individualized for their distinct textural, structural, mineralogical and/or geochemical characteristics: phonolites s.s., amygdaloidal phonolites and trachyphonolites.These are rocks with magmatic derivation, in which the most important differentiation processes interpreted were immiscibility and fractional crystallization from the ultrabasic mantellic source with primary magma.Fenite epidotes were also classified in the study area, probably product of fenitization of the granitic wall rock.Due to the geographical proximity, some similarities between the phonolites and the rocks from the Barra do Teixeira alkaline plug or the Banhadão Alkaline Complex were expected.However, the results of the petrographic and geochemical analysis point to major resemblance between the phonolites and the lithotypes of the Mato Preto Alkaline Complex.The studied rocks contain concentrations of economic interest of important chemicals elements, mainly Rare Earth Elements-REE, trace elements and mineral substances, such as zeolites and fluorites.
The making of "Age of Sail"

"Age of Sail" tells the story of William Avery, an old sailor adrift and alone in the North Atlantic. When Avery rescues Lara, who has mysteriously fallen overboard, he finds redemption and hope in his darkest hours. In this production talk we'll go behind the scenes in the making of this multi-platform immersive animated short. Some of the unique challenges we'll discuss: bringing a 2D illustrated style to life in the medium of 6DoF VR with new non-photorealistic rendering techniques; immersing the viewer in a storm-tossed ocean without making them seasick; adapting a single story to multiple mediums (desktop/mobile VR, 360° video, and 2D film); creating a better sounding and more responsive sound mix with multiple surround formats and a new spatialization model; and optimizing it all to run at 60fps on a mobile phone.
A Usage-Based Mechanism for Securing Systems Via Blockchains

The costs of operating a secure system are not always shared proportionately to the benefits that participants receive, which often hinders the adoption of security solutions. Blockchains provide us with an economic framework to distribute costs through cryptographic contracts, however, existing work in building secure applications using blockchains does not take advantage of this framework to align costs and benefits for system participants. One such application is the security of the domain name system. Past attempts to secure the DNS using blockchains suffer from a common problem: the costs of security are not shared proportionately to the benefits that participants receive, because benefits are tied to reading the secured content, while costs are tied to writing it into the blockchain. In this paper, we outline a new blockchain model for supporting secure systems in which users pay for the system at a rate proportionate to the benefits they receive. This is achieved by charging participants based on the frequency with which their content is securely retrieved and used by others, rather than the frequency with which they post or update content. The resulting model provides a flexible way to control the compensation and transaction rates of miners, and has applications to security in numerous problem domains.
A Pedestrian Detection Model Based on Binocular Information Fusion

Pedestrian detection, as a special kind of target detection, is a research hotspot in the field of image processing and computer vision. Because monocular vision cannot obtain the depth information of the image, it cannot meet the accuracy requirements of pedestrian detection. In order to solve these problems, a new cascading pedestrian detection model based on PSMNet binocular information fusion and improved faster R-CNN pedestrian detection model is proposed. Firstly, binocular images are fed into the original PSMNet binocular information fusion module to get the disparity map, and then left and right images are fused by the disparity map to get the fusion image. Secondly, in the improved faster R-CNN pedestrian detection module, the left, right and fusion image of one frame are as separate inputs, and pedestrian detection is carried out respectively. Finally, the detection results of the three channels are passed through the target consistency validation module, and the verified pedestrian detection target is as the final output detection result. The simulation results show that the accuracy and recall rate of the cascading model are improved, the missed detection rate is reduced to 13.42%, and the accuracy rate is 88.58%.
Superconducting parametric devices

Superconducting parametric amplifier, originally developed more than half a century ago, gained renewed interests in some experiments of superconducting quantum electronics about a decade ago, and now has become an indispensable tool in the field of superconducting quantum information processing. More recently, there are several proposals, where a parametric oscillator, which is a parametric amplifier pumped above the threshold, is used as a quantum bit and the network of the parametric oscillators solve some computational tasks. Here, we briefly introduce the research activity on the development of the superconducting parametric devices, including our results, with some historical backgrounds.
A time-indexed mereology for SUMO

While the period of time during which a subprocess occurs is precisely the time during which the part-whole relation with its main process takes place, part-whole relations between objects do not obey such a rule. The parts of an object can exist before the object is conformed as such, and can survive its dismantlement. In fact, there are no means for knowing when, during the existence of the part and the whole, their parthood relation holds unless an explicit account of time is represented. A time-indexed mereology characterizes how objects gain and lose parts over time by associating a time index to their part-whole relations. Keeping an account of when objects lose or gain parts is necessary for the correct representation of their spatial location and their participation in processes. Upper-level ontologies characterize the properties of the most basic, domain-independent entities, such as time, space, objects and processes. Two upper-level ontologies broadly used are The Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) and The Suggested Upper Merged Ontology (SUMO). However, while DOLCE provides a first-order time-indexed mereology for structuring its entities over time, SUMO provides a weaker axiomatization that does not represent the rules that determine how the mereological structure of objects evolve through time in the real world. This work proposes a first-order logic time-indexed mereology for SUMO based on its current representation of objects, time, and temporal location, thereby characterizing how objects gain and lose parts over time. The proposed theory sets the stage for the development of a time-indexed theory of spatial location, and for the representation of temporal restrictions on the participation of objects in processes. The time-indexed mereology of DOLCE and the proposed theory are formally compared, and their relative strength established by using ontology mapping. In order to achieve such a comparison, the representations of time, and temporal location of both upper-level ontologies are also formally compared.
Enabling Scalability, Adaptivity, and Resilience in Cloud Applications by Software-defined M-Task-based Programming

Software implementing computational science and engineering applications to be executed in cloud environments becomes increasingly complex so that issues considered in software engineering, such as design, validation and verification, and maintenance are more and more important. However, there are additional challenges to be considered, including scalability, resilience, and adaptivity to the underlying cloud structure, which have not been considered in classical software engineering, since they play a less significant role in software areas such as business information or accounting systems. In this article, we pursue the use of an M-task based software development and discuss how the specific challenges for cloud environments can be implemented through software-defined principles. The M-task-based approach has also the advantage that it supports systematic and extendable software development, thus also addressing issues of classical software engineering.
A Novel Approach for Parameter Estimation Of Discrete Dynamical Systems Using Self-Organizing Maps

In this paper, a novel approach towards parameter estimation of discrete dynamical systems with strange attractors is proposed which relies on parameter estimator self-organizing maps (PESOM). Theoretical justifications and a computational complexity analysis are presented regarding the efficiency of PESOM based cost function. Furthermore, experimental results demonstrating PESOM's superior performance compared to previously proposed cost functions such as Gaussian Mixture Model (GMM), Mean-Squared Error (MSE) and Return Map Fingerprint (RMF) are presented.
College Students’ Attitude towards the Internet as Communication Medium and Level of Utilization of English Language in the Classroom

This descriptive-correlational study attempted to determine how college students' attitude towards the internet as communication medium influences their level of utilization of the English language in the classroom at the University of Perpetual Help System Laguna-Philippines during the second semester of AY 2017-2018.The respondents were the fifty (50) college students who took Technical Writing and Philippine Literature courses during the aforesaid term.The researcher employed simple random sampling technique in selecting the respondents.The findings revealed that there was no significant relationship between the students' attitude towards the Internet as communication medium and level of utilization of the English language in the classroom considering the obtained p value of 0.211 which was greater than the significance level @ 0.05.This comprehensive study concludes that although there are many pluses, students have diverse estimations and attitudes towards this contemporary process of learning using the internet as communication medium.Likewise, teachers play a very bulging part in enticing the student's attention to maximize the use of English language in the classroom which can be possibly acquired by creating interest among them through the employment of media platforms particularly the Internet which nowadays is undeniably inseparable from teaching and learning of the English language.
Multi-view Navigation in a Personalized Scientometric Retrieval System

Given the large number of scientific productions, it becomes difficult to select those that meet the needs of researchers in scientific information and from certain sources of trust. One of the challenges facing researchers is finding quality scientific information that meets their research needs. In order to guarantee a quality result, a research method based on scientific quality is required. The quality of scientific information is measured by scientometrics based on a set of metrics and measures called scientometric indicators. In this paper we propose a new personalized information retrieval approach taking into account the researcher quality requirements. The proposed approach includes a scientometric document annotator, a scientometric user model, a scientometric ranking approach and different results visualization methods. We discuss the feasibility of this approach by performing different experimentations on its different parts. The incorporation of scientometric indicators into the different parts of our approach has significantly improved retrieval performance which is rated for 41.66% in terms of F-measure. An important implication of this finding is the existence of correlation between research paper quality and paper relevance. The revelation of this correlation implies better retrieval performance.
Scale-variant traffic sign detection

Accurate detection of traffic signs is vital in many applications, such as driving assistance systems and autonomous vehicles. However, since urban scenes are often cluttered with confusing objects, the signs may appear scale-variant (from large to small sizes) in a single image or image sequences of traffic scenes, when autonomous vehicles are moving fast; traffic signs therefore need to be detected early and accurately when they appear small in the images, and tracked for timely recognition and decision.