Reviewerly/exHarmony huggingface dataset:
Parametric Narrow‐Band InISAR 3D Imaging Based on Compressed Sensing

For muti-scatter point target and undersampled data, tradintional imaging method has a poor precision for imaging result and spin angular velocity. In view of the above problems, this paper proposes a narrow-band Interferometric inverse synthetic aperture radar(InISAR) 3-dimensional(3D) Compressed sensing imaging method based on the joint spin angle velocity error parameter estimation. First, a sparse model of narrow-band spin target is constructed. Then, the image entropy is used as the criterion function to search the optimal angle velocity by the joint reconstruction iteration. Finally, the image of the target is obtained by interference processing. The simulation results show that compared with the traditional method, the estimation of spin angular velocity and the imaging result are more accurate in proposed method.
Gamified Flow and the Sociotechnical Production of AI

Recent advances in AI, computer algorithms, and automation applications across industries have generated hyperbolic discourses about disruptive technologies. Futurists envision fleets of driverless cars delivering human bodies, armies of robots taking over jobs, and advanced AI systems outgrowing their superfluous masters. Extending into science fiction, such predictions distract from scrutinizing contexts in which lesser versions of these technologies already proliferate and appreciating subtler, long-term implications. Particularly the interfaces of a rapidly expanding attention capitalism and its gamified operations warrant closer analysis. Here, demands for frictionless services and coordinated mobilities necessitate strict surveillance protocols and continued engagement with platforms that transform attention into revenue. More than the formalized and singular manifestation, for instance, DeepMind’s AlphaGo, AlphaGo Zero, and most recently AlphaStar, the current logic of accumulation desires the continued sociotechnical production of active participants in evermore data networks. The most lucrative and transformative AI systems of the future will rest on a gamified subjectivity, whose datafied claims to entertainment, movement, and income coincide with increasingly vertical corporate network structures.Attention capitalism appeals to sensibilities of entertainment and, in no small part, competition. Applications therefore feature score-based systems, monetary and nonmonetary rewards, and certain privileges of access. Habit-forming interface design represents a crucial strategy whereby corporate platforms inject their on-demand services, automations, and AIs with life. To guarantee uninterrupted consumer experiences and efficient processing of goods and people, service environments are increasingly designed around concept emulating “flow,” a state that psychologist Mihaly Csikszentmihalyi (2009) describes as an “optimal experience” in which the constraints of the inner and outer world are suspended. Csikszentmihalyi derives his ideas primarily from athletes and artists, but anybody losing themselves in an enjoyable and challenging activity can relate. In Csikszentmihalyi hands, however, flow remains largely a phenomenological account, abstracted from social and historical context. A more critical concept of flow might follow Natasha Dow Schüll’s (2012a) “machine zone,” a space in which addictive algorithms, ergonomics, and built environments capture gamblers’ attention. Dow Schüll grasps rising figures of machine gambling in Las Vegas and elsewhere not merely for flow’s own sake, but rather as a result of bankrupt states betting on casinos to fill their cashboxes. In other words, flow must be theorized as a priced commodity, a history of deregulation, and a market that continues to show immense potentials for global capital.
Ketersediaan Data dalam Mendukung Smart City Readiness di Kota Surakarta

Data Availability in Supporting Smart City Readiness in Surakarta City&#x0D; The smart city concept is one of the developing concepts in overcoming various urban problems. The concept must be supported by mature implementation guidelines. The preparation of smart city guidelines is based on the readiness of each region. The readiness measurement is carried out with smart city readiness measurements that have been developed by several experts. This study will use compilation of several smart city readiness measurement models to measure smart city readiness in Surakarta City, in order to understand data required and available in Surakarta City Government, data required and available outside Surakarta City Government, and data required but not yet provided by both the City Government and other agencies. The method used in this study is case study with a qualitative approach. Measurement results show that the availability of data and the quality of available data in Surakarta City is quite good. This shows that Surakarta City is ready to develop the smart city concept to overcome various city problems faced.
Personality-dependent content selection in natural language generation systems

Abstract This paper focuses on the computer side of human-computer interaction through natural language, which is the domain of natural language generation (NLG) studies. From a given (usually non-linguistic) input, NLG systems will in principle generate the same fixed text as an output and in order to attain more natural or human-like interaction will often resort to a wide range of strategies for stylistic variation. Among these, the use of computational models of human personality has emerged as a popular alternative in the field and will be the focus of the present work as well. More specifically, the present study describes two machine learning experiments to establish possible relations between personality and content selection (as opposed to the more well-documented relation between personality and surface realisation), and it is, to the best of our knowledge, the first of its kind to address this issue at both macro and micro planning levels, which may arguably pave the way for the future development of more robust personality-dependent systems of this kind.
State-public administration of education as the main direction of democratization

Public administration of the education system is a productive activity of the society, which contains an active manifestation of civic position, social initiative and social responsibility in the management of the education system.The purpose of the article is to emphasize the issues of state-public administration of education as the main direction of democratization in the field of education. There are three levels of state administration in the educational sphere: the national level; regional level; district level.
IMM-UKF based airborne radar and ESM data fusion for target tracking

A fusion filtering model based on the Interacting Multiple Model (IMM) is proposed in this paper, to solve the fusion tracking problem of two kinds of heterogeneous sensors, airborne radar and electronic support measures (ESM). Firstly, the motion model of the maneuvering target and the observation model of these two sensors are established. Under the premise that the radar and ESM spatial coordinate system have been unified, the time registration and measurement fusion of the observation data are performed, and the fusion observation data is used as the input of the filter. The simulations compare the effect of two filtering models based on IMM on the tracking results, which are EKF and UKF. The simulation results show that the radar and ESM fusion tracking model on the basis of IMM-UKF algorithm has better tracking effect and achieve tracking of strong maneuvering target.
QUALITY ASSESSMENT IN SCRUM SOFTWARE DEVELOPMENT THROUGH METRICS: A CONCEPTUALIZATION USING CONCEPT MAPS

In Scrum software development projects, plenty of quality metrics may be measured and used for quality assessment.Selecting the required metrics thus becomes a critical step.Scrum projects are fundamentally conducted around three elements: team, artifacts and events.These elements can be helpful for guiding the involved stakeholders in selecting the most pertinent ones.Hence, in this paper we propose concept maps that promote quality assessment through a classification of Scrum quality metrics based on the three aforementioned elements.These Concept Maps will guarantee that all considered elements would be controlled and thus facilitate the improvement of the quality process.Their adoption in the quality assurance approach will certainly be advantageous.
Handling Failures in Semantic Web Service Composition Through Replacement Policy in Healthcare Domain

Consistency of web service composition is a challenge for developing business applications. As web services are naturally changeable, the way to deliver consistent web services composition over unreliable web services could pose a significant problem. We propose a framework for semantic web services in healthcare domain that automatically performs web service discovery, composition and quality of service assurance, and, performs error handling through the replacement policy and fault-tolerant composition of web services that mixes both exception managing and transaction approaches. The framework enables the development of personalized healthcare systems.
MATERIALizing Cross-Language Information Retrieval: A Snapshot

At about the midpoint of the IARPA MATERIAL program in October 2019, an evaluation was conducted on systems’ abilities to find Lithuanian documents based on English queries. Subsequently, both the Lithuanian test collection and results from all three teams were made available for detailed analysis. This paper capitalizes on that opportunity to begin to look at what’s working well at this stage of the program, and to identify some promising directions for future work.
A Study on The Influnene of Consulting Paticipation of The Consulted Firm on Consulting Repurchase Intention

This study suggests that even if the consulting is started by the consulting of the company, it is difficult for the consulting firm to operate the consulting firm Consulting performance differs depending on the degree of understanding of consulting. Although consulting firms have been studying various prior research papers in view of the fact that there are many cases where they proceed with the sales strategy of repurchasing in mind, most of them deal with research on consulting performance on the supplier side, The purpose of this study is to investigate whether a company has a high level of participation in consulting in the event of a situation or situation and consequently influences the intention to purchase consulting. In order to find out whether they are visible, the reliability of the measured values and the fit of the measurement model by CFA were obtained through the exploratory factor analysis. The results were as follows: The results of this study are as follows. As a result of the study, it is necessary for the consultant to improve the participation of the consulting company and the understanding of the consulting in order to increase the intention of the consulting repurchase intention. Since the consultant shows the result in an empirical way, the consulting company participates in the role and process The results of this study are as follows. First, it is suggested that firms should be very careful about the participation and consulting understanding because they affect the repurchase intention of consulting firms.
PENGEMBANGAN SIMULASI “STRESS TEST” MENGGUNAKAN TES KRAEPELIN PADA TES PSIKOLOGI

Psychology test is intended to measure the differences between individuals to determine the reaction of the individual for a different situation which aims to assess someone's behavior. One of the most common psychological tests is the kraepelin test or newspaper test. Generally, this test uses several sheets of papers with numbers written in it. In this research, a web-based kraepelin test simulation was developed in order to accessible via computer or smartphone. User can do the test by selecting the kraepelin test menu, and then do the kraepelin test by adding two numbers. If the result of a sum was tens, write the last digit only within the specified time. The waterfall method is used to developed this system, where the stages consist of requirements analysis, design, implementation, and black box testing. The results of the black box test showed 80.88%. From this research, “stress test” simulation using kraepelin test on psychology has been developed to someone who will take a kraepelin test.
Research on Management Accounting Teaching Based on Cloud Accounting System under Big Data Background

With the advent of the era of big data, the market economy has also developed rapidly under the cumulative growth of data.All circles of society have begun to pay close attention to the problem of big data.In the era of big data and cloud computing, management accounting is also facing new opportunities and challenges.This paper introduces the concept of big data and cloud computing and their great role in management accounting, and points out the opportunities and challenges faced by management accounting teaching in the era of big data.On this basis, the paper points out how to effectively integrate management accounting and cloud accounting system based on big teaching background, so as to promote the rapid development of management accounting teaching. Characteristics of big dataAccording to the point of view of western scholars, the characteristics of large data can be summed up into "4V", that is "volume", "variety", "velocity" and "value".
Impact of COVID-19 on human resource management

The current situation regarding necessary intervention to avoid spreading the COVID-19 virus significantly affect numerous of areas of working life. It is possible to see significant movement towards home offices and distant work of teams. It is not possible to perceive current change only negatively. Research by Beno (2018) shows that home office has a positive influence on the personal work experience. But there are other impacts that we can see and will affect organizations in the future. The situation, when some kind of new virus or new wave of infection arises is likely to happen again. Organizations should be ready to respond quickly and have their action plans prepared. According to Yildirim and Korkmaz (2017), effectiveness of human resources management and team development is the determinant of project success. To be able to efficiently manage and to adapt appropriate approaches of employees, managers need to understand also employees´ perspective.
Evaluasi Kesesuaian Data Tropical Rainfall Measuring Mission (TRMM) dengan Data Pos Hujan Pada Das Temef di Kabupaten Timor Tengah Selatan

The construction of the Temef Dam in Oenino Village, Oenino District, and Konbaki Village, Polen District, South Central Timor Regency requires long and reliable rainfall data. To overcome the minimum data or the unavailability of automatic rainfall (ARR) and discharge data in the past decades, the use of Tropical Rainfall Measuring Mission (TRMM) satellite data is foreseen. The accuracy of TRMM data is obtained when the parameters of suitability and compatibility of TRMM are in a good agreement with the ARR. For the Temef watershed, there are six rainfall stations that were reviewed, namely Fatumnasi, Oeoh, Noelnoni, Polen, Nifukani, and Batinifukoko rainfall stations. Direct comparisons of rainfall data were conducted for 20 years (1998-2018) with temporal resolution on a monthly and daily basis. The results of the study show that the rainfall patterns in the TRMM data product (version 3B42V7) tend to be consistent with 3 rainfall stations in the Temef watershed namely Noelnoni, Fatumnasi, and Batinifukoko. A correlation coefficient of 0.505 â€“ 0.813 was obtained from TRMM data calibration at monthly basis while a correction factor level of 0.0056 - 0.0129 was obtained for daily.Â The calibration on the annual maximum daily rainfall data resulted in a correction factor of 0.0298 - 0.2516. Monthly and daily TRMM data fit well with the data of 3 rainfall stations. However, the Noelnoni rainfall station showed poor results on the annual maximum daily rainfall.Keywords: TRMM data, ARR data, correction factor, correlation coefficient
Awareness and Usage of Reference Management Software: Perspectives of Faculty Members of University of Ilorin Nigeria

This study examined the awareness and usage of reference management software by faculty members of the University of Ilorin. Descriptive survey method was adopted for the study. The Web-based questionnaire was used to collect data for the study. The total population of the study is 1,496 people. From which the sample size of 306 was selected using Raosoft sample size calculator and total responses of 98 was returned, which represents the unit of analysis. Hence, the response rate for the study is 32%. The findings of the study revealed that EndNote and Mendeley are the most used reference management software by faculty members of the University of Ilorin (UNILORIN). Results show that faculty members were aware of EndNote and Mendeley to great extent. It was found that there is low usage of reference management software among faculty of the University of Ilorin; and that most of the faculty members have never used ProCites, Bookends, Papers and Qiqqa. It was concluded that there is a positive significant relationship between awareness and usage of reference management software by faculty members. It was recommended that faculty members should be trained on how to make use of the most used reference management software.
The Analysis Of Richard A Vias Never On Wednesday Based On Brown And Levinson's Politeness Strategies

The purpose of this study was to identify politeness strategies found in the script of a play, Never On Wednesday, written by Richard A. Via. This analysis was based on Brown and Levinson's theory about politeness strategies. The subject of this study was the exchange between the character Fred, Father, and Mother. Based on the findings, it was found that there are four politeness strategies in this play, namely bald on record, positive politeness, negative politeness, and off-record strategy. There is no don't-do-the-act strategy in this play because each character keeps talking and not being silent. Further research about politeness strategies in drama needs elaborating more.nnn
State and Strategy of Production, Market and Integrated Management of Mineral Water, South Korea

In this study, the state of the production, market, and integrated management of mineral water in South Korea was assessed and a strategy was established to improve the competitiveness of mineral water with respect to foreign brands. Diverse data, including a number of mineral water manufacturers, daily permitted volume, daily production amounts, sales volume, and sales amounts, were used to clarify the state of mineral water and establish a strategy. Real-time data transmitted from the mineral water manufacturers were analyzed and managed in an integrated management system (IMS). Chemical characteristics of mineral water were analyzed to assess water quality and identify problems related to contamination. This study shows that specialization plans according to geological characteristics should be established, rather than focusing on quantitative growth by a low-cost sales method. The establishment of contamination management plans was found to be needed for wells with potential pollution due to sub-surface inflow into the wells. We suggest that an independent editing system of the attribute information needs to be designed based on the analysis and management of the IMS.
Real Time Object Detection and Tracking using Deep Learning

Efficient Object Recognition and Tracking are main challenging assignments in computer vision techniques. A very big challenge in many object detection techniques using deep learning may lead to slow and non-accurate performance. This Project Aims to detect and tracking of objects efficiently and accurately in real time .Detecting any object is important in understanding object activities. Here we completely used deep learning networking techniques .The network is trained on most used and challenging dataset COCO. The result is very fast and accurate where object recognition is required.
Breast Cancer and Prostate Cancer Detection using Classification Algorithms

It is a known fact that, cancer rates have increased to great heights in the recent times.The only way to completely cure cancer is to detect its presence at an early stage, for which appropriate diagnosis is available.The main plot of this paper is the detection, and classification of such cancerous cells in the patient's genome expression, on detection of which he/she can be provided rightful treatment.Modern day techniques have evolved that can help to detect the presence of cancer, such as Deep Learning, Artificial Neural Networks, Deep Convolution Networks, and Data Mining etc.In this paper we have dealt mainly with two types of cancer.Breast cancer and Prostate cancer in females and males respectively.We have implemented Machine Learning to find out signs of cancer, and what type of cancer, if seen.The reason being, physicians are capable of diagnosing a patient with cancer, with an accuracy of 71%, according to a latest research, on the other hand Machine Learning techniques can show up to 91% accuracy for rightful classification.Since, the primary focus is to detect and classify the type of cancer in the patient, we have used classification techniques/algorithms under Machine Learning such as Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR) and Naïve Bayes (NB).Effort has been made, to identify the best techniques providing the highest accuracy for both the cancers, and enhancing them with stratified K-fold and dimensionality reduction.
No Escape: A 2D Top-Down Shooting Roguelike Game Embedded with Drunkard Walk Algorithm

Video Game is a part of the entertainment that grows rapidly every year along with the development of content and demand from players.To enhance the development of content, the game must be able to create a non-boring game atmosphere such as increasing Replay-ability, which is repeatedly and unique content produced to increase long-term enjoyment.One genre of games that can achieve Replay-ability is the Roguelike game, where the game relies on Procedural Content Generation as a container for games and permadeath systems.By providing Procedural Content Generation, game content that is created automatically and randomly can increase the value of Replay-ability.One algorithm that is part of the Procedural Content Generation algorithm is the Drunkard Walk, where this algorithm creates space and content from a game based on the direction the algorithm is going.Uncertain movements can produce random space and content.However, this method does not have much research in the development of procedural content generation games.Based on this problem, a Roguelike game was built that applied the traditional method of Top-Down Shooting and implemented the Drunkard Walk algorithm to increase the level of player satisfaction with the game they were playing.This game was successfully built and tested on 30 respondents to find out the level of satisfaction of respondents with the game that was made.The tested game is then evaluated with the Game User Experience Satisfaction Scale (GUESS) and gets a 71% (Good) result in its level of satisfaction.