Reviewerly/exHarmony huggingface dataset:
The Workforce of the Future - Projects and Initiatives to Overcome the Challenges Enacted by the Digital Transformation

Changes brought by the 4th Industrial Revolution and digitalization impact directly in the way we live, shape the organizations and change the way we work. This article explores and anticipates the scope and depth of the impacts that current and emerging technologies are imposing. Under the scope of the global digital transformation, some possible challenges enacted by the technologies as well as some projects and initiatives that are already being carried out to address them are presented. The aim of this paper is to subsidize to a reflection about this complex environment and bring together the contribute of trainers, teachers and pedagogues as the possible solution to prepare students to thrive in this complex world of work which will need the intervention of all actors and stakeholders.
Print It To Me Development System

This paper addresses the project where, by the end of the project, the web-based system is able to provide an online printing service system to any party or individual who are staying in-campus to make money with their personal printer. In-campus student and staff are allowed to register as service provider (SP) and they can view and accept order via this webbased system. The system are able to display and show requests by customers while the service providers can select the requests and provide proper service to them. Furthermore, the system should have limitless availability of access, compared to the current printing request process.
Noisy Data Collection Towards Diversity Maximization

In the big data era, we can take advantages of the big data by machine learning, knowledge discovery and so on. A dataset with good quality can promote the performance of the aforementioned applies. The dataset quality can be assessed from many aspects, for example, completeness, consistency, diversity, etc. In this paper, we will investigate diversity-driven data collection. Most previous works focused on the data collection only consider the accurate data without any noise. However, from the surveys and experiments, we find out that the data generally has noise with a certain probability distribution. Based on this discovery, we take account of the distribution of the data noise in the data space. We construct a comprehensive model to calculate the probability density distribution (abbreviated to PDF) of the distance between two noisy data points. Using the mainstream diversity metric, i.e., the average distance, we propose a more time-saving data collection method compared to the existing generic greedy algorithm.
Perancangan Sistem Informasi Akademik Berbasis Website Pada SMK Bina Medika Jakarta

A technology creation starts from the world of education, then the world of education should implement a technology-oriented information system, but in SMK Bina Medika every school academic system procedure is done manually, student data processing, absenteeism, student data search related to academics still must be open the archive sheets in the student information value section, there is no integrated data storage media because student data storage, teacher data, grade data, class data and class schedules that are done now are still using an offline application without you a database, so the problem in SMK Bina Medika, thus slowing down performance in presenting information quickly and precisely. This research aims to design a web-based academic information system. The research method used in this study is the System Development Life Cycle (SDLC) method. The design system in making academic websites uses some software namely Sublime Taxt, Xamp which is a combination of Apache Web Server, PHP, MySQL. Designing an academic information system to facilitate students, teachers and the Bina Medika Vocational High School (SMK) which was previously not available, student data, teacher data and the school is still separate so as to find out full information for quite a long time, with its website-based information system online is expected to make it easier for students, teachers and the Bina Medika Vocational High School (SMK), so that it can be more effective and efficient.
A Study of a Trajectory Synthesis Method for a Cyclic Changeable Target in an Environment with Periodic Dynamics of Properties

Trajectory planning in a large dynamic environment is a computationally complex cyber-physical task. The chapter considers an environment with periodic dynamics that simulates the rhythm of the day and night. Robots move between two target points cyclically. To optimize the trajectory planning process, it is possible to use pre-calculated paths. The pre-calculated state space consists of the planned paths for environmental states that can be considered static for a given period of time. The planning of robot movement in such the state space is carried out using parts of the pre-calculated optimal trajectories for a certain time and criteria for the transition between them. The method and criteria are studied by simulating the robot movement on two fundamentally different realistic maps. The method allows to plan the trajectories asynchronously with the time of the beginning of the movement of the robot, as well as to estimate the energy costs of overcoming the route.
GPU-enabled design of an adaptable pattern recognition system for discriminating squamous intraepithelial lesions of the cervix

The aim of the present study was to design an adaptable pattern recognition (PR) system to discriminate low- from high-grade squamous intraepithelial lesions (LSIL and HSIL, respectively) of the cervix using microscopy images of hematoxylin and eosin (H&E)-stained biopsy material from two different medical centers. Clinical material comprised H&E-stained biopsies of 66 patients diagnosed with LSIL (34 cases) or HSIL (32 cases). Regions of interest were selected from each patient's digitized microscopy images. Seventy-seven features were generated, regarding the texture, morphology and spatial distribution of nuclei. The probabilistic neural network (PNN) classifier, the exhaustive search feature selection method, the leave-one-out (LOO) and the bootstrap validation methods were used to design the PR system and to assess its precision. Optimal PR system design and evaluation were made feasible by the employment of graphics processing unit (GPU) and Compute Unified Device Architecture (CUDA) technologies. The accuracy of the PR-system was 93% and 88.6% when using the LOO and bootstrap validation methods, respectively. The proposed PR system for discriminating LSIL from HSIL of the cervix was designed to operate in a clinical environment, having the capability of being redesigned when new verified cases are added to its repository and when data from other medical centers are included, following similar biopsy material preparation procedures.
The Journey of Cloud Computing with Open Source

Cloud computing is changing from a buzz word to a common technology nowadays. Though there is clarification for cloud computing for three types/layers: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), generally people talk about IaaS and PaaS when they talking about cloud computing. There are already several giant players, like AWS, Azure and GoogleCloud, in the market and it's a 100+ billions USD market[1],but it's a competitive market and there are new players coming in. And on the other hand, people can see big demand for private cloud as well.
State Preparation and Measurement Tomography via Unitary Transformations

We describe a technique for simultaneously determining both the state of a quantum system and the positive value operator measure that describes a detector, while making a minimum of assumptions about each of them.
Complexity verification through design and analysis of computer experiments

This research article is a systematic study towards exploring the parameterised behaviour of smart sort, a comparison based sorting algorithm. Our observation for quick sort led us to conjecture that for sufficiently large samples of fixed size, the average case runtime complexity is: yavg(n, td) = Oemp(td), where yavg denotes the average complexity with parameters n and td denoting the input size and frequency of an element (tie density) respectively. The notation Oemp (also called empirical-O) is the statistical bound estimate obtained by running computer experiments. Performance of heap sort is better for discrete inputs with low k values (or equivalently high td values) and the runtime reaches to maximum beyond a threshold k. These two observations are opposite in their behaviour. The smart sort, which is designed by combining the key functions of standard quick and heap sort algorithms, is expected to behave optimally with respect to the different input parameters. The robustness of average case Oemp(nlog2n) complexity for smart sort is conjectured as result of study for various regression models and factorial design experiments.
Timestamp Anomaly Detection Using IBM Watson IoT Platform

Anomaly disclosure is an issue of finding startling precedents in a dataset. Amazing precedents can be described as those that do not agree to the general direct of the dataset. Irregularity revelation is basic for a couple of use spaces; for instance, cash related and correspondence organizations, general prosperity, and environment contemplates. In this paper, we base on revelation of irregularities in month-to-month temperature, weight, and significance data on IBM Watson organize for timestamp peculiarity area. IBM Watson features to make chronicled dataset dependent nervous qualities that are gotten from the time plan informational collection. With these principles, we can prepare create informing system for customers IoT devices when a sporadic examining is recognized by the DSX acknowledgment data science experience. In this examination, we took a gander at the results IBM Watson IoT organize and fuzzy rationale abnormality acknowledgment. IBM Watson IoT organize features to deliver alert/caution to the customer. On IBM Watson organize, the z-score is processed to distinguish characteristics in the real-time series data using the IBM Data Science Involvement in direct advances. Also, showed up, how one can deduce the edge a motivating force for the given chronicled data and set the administer as requirements be in IBM Watson IoT Platform to make continuous alerts.
The Analysis Of Hydrology In Comal River

This research was conducted to find out the availability of water to the requirements of water and also predict flood plan discharge for return period based on hydrological analysis in Comal River. Calculations are carried out using rainfall data obtained from PUSDATARU of Pemali - Comal from 1999 - 2017.Used the rainstation in the region of Comal Watershed, there are 7 rain stations. Catchment area of rain station used Thiessen Polygon Method to know value of catchment area of each rain station. The Gumbel distribution (Generalized Extreme Value distribution Type-I) is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions. The calculation of the flood discharge design is using the Nakayasu, Rational, Weduwen, Weduweden, and Haspers method. Based on the result of this research it can be concluded that the biggest water potential occurs in January is 199.60 m3/s and the smallest in August is 0.84 m3/s. Cropping pattern carried out with one year there are three cropping patterns, namely paddy - paddy - secondary crops. For the water requirements, enough can be fulfilled, but in August and September, where the planting period III for the secondary crops experiences a deficit. The method used to design flood discharge is the Nakayasu method. For the embankment construction and normalization is profitable. Keywords : River, Flood, Embankment, Thiessen, Comal
Usage of Information and Communication Technologies among Agrarian Youths of Manipur, India

The present study aimed at analysing the usage of ICTs by the agrarian youths of state Manipur, India. The locale of study was Imphal-West district of Manipur, from where 120 respondents have been randomly selected from six villages of the two sub-divisions viz., Patsoi and Wangoi. The study delved into examining whether the socio-economic profiles of youths have any significant dependence with the utilization of different ICT tools viz., Radio, T.V., Mobile Phone, PC/Laptop, Internet and Information Kiosk. The major findings of the analysis reveal that ‘Attitude towards ICTs’ has significant dependence at 5% level of significance with the utilization of Radio. The variable ‘Education’ has significant dependence with the utilization of television at 10% level of significance. The utilization of PC/laptop by respondents had significant dependence with ‘Education’, ‘Attitude towards ICTs’, ‘Cosmopoliteness’ and ‘Social participation’ at 1% level of significance. With respect to utilization of Internet by agrarian youths, the variables, namely ‘Education’, ‘Attitude towards ICTs’, ‘Cosmopoliteness’ and ‘Social Participation’ have significant dependence at 1% level of significance. Pertaining the utilization of information kiosks by respondents, the variable ‘Age’ has significant dependence at 1% level of significance. Lack of infrastructural facilities to access ICTs was the most profound constraints faced by agrarian youths of Manipur.
Design and Evaluation of an Automatic Speech Recognition Model for Clinical Notes in Spanish in a Mobile Online Environment.

Clinical documentation in healthcare institutions is one of the daily tasks that consumes most of the time for those involved. The adoption of mobile devices in medical practice increases efficiency among healthcare professionals. We describe the design and evaluation of an automatic speech recognition system that enables the transcription of audio to text of clinical notes in a mobile environment. Our system achieved 94.1% word accuracy when evaluated on pediatrics, internal medicine and surgery services.
Rough fuzzy cuckoo search for triclustering microarray gene expression data

Analyzing time series microarray gene expression data is a computational challenge due to its three-dimensional characteristics. Triclustering techniques are applied to three-dimensional data for mining similarly expressed genes under a subset of conditions and time points. In this work, a novel rough fuzzy cuckoo search algorithm is proposed for triclustering genes across samples and time points simultaneously. By applying the upper and lower approximation of rough set theory and the objective function of fuzzy k-means, rough fuzzy k-means was incorporated into a cuckoo search to handle the uncertainty of the data. The proposed method was applied to three real-life time series gene expression datasets. This work was evaluated using four validation indices and correlation analysis was performed to indicate the cluster quality. The proposed work was also compared with the existing triclustering algorithms and it outperformed the other methods.
Iterative Face Detection from the Global to Local

To balance between accuracy and speed is a dilemma in face detection, and scale variance problem is one of the main causes. In this paper we propose fast and accurate iterative face detection method processing from the global to local. We define a class of object called “probable regions” which contain small faces. “Probable regions” are detected iteratively in order to enlarge the small face parts. Thus small faces turn into large faces after several iterations. We design a strategy of training samples augmentation to meet the requirement for two object classes, so that extra annotation is unneeded. Our method is simple and clear to deploy. Experiments show that our method achieves competitive accuracy with real time speed. Detection time consumption will not explicitly grow when resolution of sample image increases. The speed is merely related to actual amount of faces, which adapts to real world applications.
Analisis Kualitas Layanan E-Government dengan Pendekatan E-GovQual Modifikasi

E-Government Quality (E-GovQual) is a method for measuring the quality of electronic-based information systems in providing services to the public. The Modified E-GovQual Approach uses the overall assessment of the SIMSARPRAS website (Infrastructure Management Information System) based on the user's perception of the SIMSARPRAS website, so that the analysis of service quality becomes more accurate and precise in its assessment. Overall assessment of the E-GovQual Modification approach aims to determine the quality of service based on the level of influence of the 6 independent variables of E-GovQual, namely the ease of use, trust variable, function variable and form interaction (functionality of the interaction environment), variable reliability (reliability), variable content and display information (content and appearance of information) and supporting variables (citizen support) to the dependent variable, namely user satisfaction. This study uses the modified E-GovQual method by conducting validity, reliability testing, multiple linear regression analysis, t test and F test on the results of the questionnaire on 500 respondents, with 6 independent variables and 1 dependent variable. The results obtained in this study note that the quality of SIMSARPRAS website services has an effect of 61.7% on user satisfaction, and the correlation coefficient value is 78.5%. With these results, it was concluded that the SIMSARPRAS website has good service quality as an application that performs public services, and there is a strong relationship between the quality of E-Government services and the satisfaction of E-Government users. The results of this study also become a reference or evaluation material to the Ministry of Religion as the owner of the SIMSARPRAS website and can also be used as a reference for similar research.
On the Tour Towards DPLL(MAPF) and Beyond.

We discuss milestones on the tour towards DPLL(MAPF), a multi-agent path finding (MAPF) solver fully integrated with the Davis-Putnam-Logemann-Loveland (DPLL) propositional satisfiability testing algorithm through satisfiability modulo theories (SMT). The task in MAPF is to navigate agents in an undirected graph in a non-colliding way so that each agent eventually reaches its unique goal vertex. At most one agent can reside in a vertex at a time. Agents can move instantaneously by traversing edges provided the movement does not result in a collision. Recently attempts to solve MAPF optimally w.r.t. the sum-of-costs or the makespan based on the reduction of MAPF to propositional satisfiability (SAT) have appeared. The most successful methods rely on building the propositional encoding for the given MAPF instance lazily by a process inspired in the SMT paradigm. The integration of satisfiability testing by the SAT solver and the high-level construction of the encoding is however relatively loose in existing methods. Therefore the ultimate goal of research in this direction is to build the DPLL(MAPF) algorithm, a MAPF solver where the construction of the encoding is fully integrated with the underlying SAT solver. We discuss the current state-of-the-art in MAPF solving and what steps need to be done to get DPLL(MAPF). The advantages of DPLL(MAPF) in terms of its potential to be alternatively parametrized with MAPF$^R$, a theory of continuous MAPF with geometric agents, are also discussed.
Enhancing the Children’s Learning Experience of Mexican Traditions through Augmented Reality

During the &ldquo;Day of the Dead&rdquo; celebration in M&eacute;xico, altars are installed to commemorate the dead in different places, such as schools&rsquo; libraries. To preserve this cultural tradition, students visit them to know about the meaning of the altars&rsquo; elements. In a similar way to museums, children can perceive altars as boring places where they should see objects passively or listen to historical accounts of the past. To address these challenges, we propose using augmented reality to make this cultural tradition a more engaging learning experience. We implemented an augmented reality (AR) prototype which recognizes the altar&rsquo;s elements/objects to present narrative information through video, text, and images. We evaluated it through a within-subjects experiment to test two conditions: (A) A teacher explaining the altar (the usual method), and (B) Using the AR application. For collecting data, we used the User Engagement Scale (UES), a questionnaire to assess children&rsquo;s perception about the learning experience, and observations. From twenty-nine students, only nine perceived that condition A was more engaging than B (augmenting reality). A Wilcoxon Signed-ranks test indicated a significant difference between both conditions (W = 124.5; Z = &minus;2.012; p &lt; 0.05). Our results helped us identify new design features in order for AR support learning experiences about this tradition, such as including narratives through multimedia.
RANCANG BANGUN WEBSITE MARKETPLACE “E-SALON”

Salon is a form of business associated with beauty care, face, hair, and others for both men and women. Salon became the type of business in the interest of business by utilizing social networking, ads, brochures, and websites to promote the salon. E-salon is a marketplace website which facilitates the salon in terms of delivery the salon promotion and salon service sales. Salon provides a salon service to come home and can open many new jobs. To solve this problem, a website was developed using programming language such as HTML 5, CSS, JavaScript, Bootstrap 3, and PHP, and using MySQL or known as MariaDB for data storage. The website was developed using Rapid Application Development (RAD) methodology approach. The result of this website development is able to assist the salon in terms of promotion and sales of salon services, create new jobs, and make it easier for customers to find their desired salon.Keywords: salon, website, Rapid Application Development (RAD), marketplace
Syntactic Generation of Similar Pictures

In visual password systems it is important to display distractor pictures along with the user’s password picture on the authentication screen. These distractors should be similar to the password picture to make it difficult for shoulder surfers to easily identify the true password picture. In this work, we present approaches to generating similar pictures using bag context picture grammars (BCPGs). We describe how these approaches are implemented and present galleries of pictures that have similar characteristics. We then determine the mathematical similarity of the generated pictures, using the spatial colour distribution descriptor (SpCD). The spatial colour distribution descriptor has been shown to be effective in determining the similarity of computer-generated pictures in previous research, and so was seen as a good similarity measure for this research. We then describe an online survey that was conducted to determine the perceptual similarity of the pictures generated by the picture grammars. This is followed by a comparison of perceptual similarity from the survey with mathematical similarity to determine if the results are consistent. The results show that we can easily generate galleries of pictures that we feel are similar (they have common characteristics) using BCPGs; that SpCD can be used to determine the mathematical similarity of the pictures; and that there is a good correlation between SpCD and perceptual similarity, although in some instances humans do make different judgements. In terms of the desired goal of generating pictures that are similar to a selected picture, we found that controlling the level of refinement of the pictures and limiting the number of refinements of subpictures are important factors.