Reviewerly/exHarmony huggingface dataset:
Loop Closure Detection of Visual SLAM Based on Point and Line Features

For traditional loop closure detection algorithm, only using the vectorization of point features to build visual dictionary is likely to cause perceptual ambiguity. In addition, when scene lacks texture information, the number of point features extracted from it will be small and cannot describe the image effectively. Therefore, this paper proposes a loop closure detection algorithm which combines point and line features. To better recognize scenes with hybrid features, the building process of traditional dictionary tree is improved in the paper. The features with different flag bits were clustered separately to construct a mixed dictionary tree and word vectors that can represent the hybrid features, which can better describe structure and texture information of scene. To ensure that the similarity score between images is more reasonable, different similarity coefficients were set in different scenes, and the candidate frame with the highest similarity score was selected as the candidate closed loop. Experiments show that the point-line comprehensive feature was superior to the single feature in the structured scene and the strong texture scene, the recall rate of the proposed algorithm was higher than the state-of-the-art methods when the accuracy is 100%, and the algorithm can be applied to more diverse environments.
PENGARUH MOTIVASI BELAJAR, SIKAP BAHASA, DAN KEBIASAAN MEMBACA TERHADAP PRESTASI BELAJAR BAHASA INDONESIA

This research aimed to know the effect of some variables, as followed : (1) learning motivation, (2) language attitude, (3) reading habit, and (4) learning motivation, language attitude, and reading habit (all together) toward Indonesian learning achievement on students in Junior High School grade IX in East Denpasar. This research was quantitative with ex post facto form of research. The population of this research were students in Junior High School grade IX in East Denpasar that amount of 1.846 students. This research used dual sampling techniques namely quota sampling and proportional simple random sampling. The data were collected using learning motivation questionnaire, language attitude, and reading habit within the documentation of test summative score in odd semester year 2019. The result of this research showed significant effect on Junior High School Students Grade IX in East Denpasar as followed (1) there was significant effect of learning motivation toward Indonesian learning achievement with correlation coefficient amount 0, 372 and effective contibution amount 9, 672%, (2) there was significant effect of language attitude toward Indonesian learning achievement with correlation coefficient amount 0, 437 and effective contribution amount 8, 390%, (3) there was significant effect of reading habit toward Indonesian learning achievement with correlation coefficient amount 0, 747 and effective contribution amount 41, 907%, and (4) there was significant effect of learning motivation, language attitude, and reading habit (all together) toward Indonesian learning achievement with dual correlation coefficient amount 0, 627 and effective contribution amount 59, 969%.
Genre analysis of artificial intelligence research article abstracts:Local versus international journal

The generic structure of research article (RA) abstracts has been studied across disciplines and cultures. Taking a different approach, the current study aimed to explore and compare the constituent moves of RA abstracts in a local and an international journal in the field of Artificial Intelligence. To this end, Bhatiaâ€™s model of four-move abstracts was applied to 30 RA abstracts, 15 from the local and 15 from the international journal, published in 2017. The results revealed that the Methods and Results moves were obligatory in both local and international abstracts while the Conclusion move was absent in most RA abstracts in both local and international journals. The findings unfolded the obligatory nature of the Purpose move in international abstracts as well. The results can carry some pedagogical implications for academic writing instructors in order to enhance their applicantsâ€™ understanding of the generic norms of academic discourse communities.&#x0D; Keywords: Academic writing, artificial intelligence, genre analysis, moves, research article abstracts.
An Ensemble Click Model for Web Document Ranking

Annually, web search engine providers spend a lot of money on re-ranking documents in search engine result pages (SERP). Click models provide advantageous information for re-ranking documents in SERPs through modeling interactions among users and search engines. Here, three modules are employed to predict users' clicks on SERPs simultaneously, the first module tries to predict users' click behaviors using Probabilistic Graphical Models, the second module is a Time-series Deep Neural Click Model which predicts users' clicks on documents and finally, the third module is a similarity-based measure which creates a graph of document-query relations and uses SimRank Algorithm to predict the similarity. After running these three simultaneous processes, three click probability values are fed to an MLP classifier as inputs. The MLP classifier learns to decide on top of the three preceding modules, then it predicts a probability value which shows how probable a document is to be clicked by a user. The proposed system is evaluated on the Yandex dataset as a standard click log dataset. The results demonstrate the superiority of our model over the well-known click models in terms of perplexity.
Analysis of the ‘Open Source Internet Research Tool’: A Usage Perspective from UK Law Enforcement

Internet Intelligence and Investigations (i3) are a fundamental investigative tool of the modern law enforcement official (LEO) in an always-connected online era. Ensuring LEOs follow good procedure for such investigations is critical for both law enforcement and society, as it ensures consistency, rigor and transparency. Procedural issues lie with online evidential capture, however. For example, it is not feasible to directly apply digital evidence methodologies one would for ‘offline’ digital forensics; instead, one must apply best practices and a consistent approach. How those best practices and consistent approaches apply will typically fall to individual forces. One such tool in the arsenal of law enforcement is the ‘Open Source Internet Research Tool’ (OSIRT), a free all-in-one browser that assists law enforcement in conducting i3 in a standardized manner. This paper analyses and discusses the results of 32 questionnaire responses from serving LEOs in the UK and their use of OSIRT. Results showed that LEOs found OSIRT to be helpful to them and compared to their previous method of conducting online investigations, OSIRT offered an improved system to conduct online investigations in many instances.
The Effect of Preprocessing on Short Document Clustering

Natural Language Processing has become a common tool to extract relevant information from unstructured data. Messages in social media, customer reviews, and military messages are all very short and therefore harder to handle than longer texts. Document clustering is essential in gaining insight from these unlabeled texts and is typically performed after some preprocessing steps. Preprocessing often removes words. This can become risky in short texts, where the main message is made of only a few words. The effect of preprocessing and feature extraction on these short documents is therefore analyzed in this paper. Six different levels of text normalization are combined with four different feature extraction methods. These setting are all applied on K-means clustering and tested on three different datasets. Anticipated results can not be concluded, however other findings are insightful in terms of the connection between text cleaning and feature extraction.
USING THE TECHNICAL EXPERIMENT IN THE COMPUTER SIMULATION TRAINING FOR PROSPECTING SOFTWARE ENGINEERS

In present work, a new technology of the prospective software engineers training in computer simulation is described. The technology provides carrying out comparative analysis of opportunities, productivity, and the accuracy of the reproduction of different computer simulation packages (CSP) on the basis of direct performance of the technical experiment results. Training process includes the principal stages: carrying out of the independent technical experiment; its simulation using of various CSP; comparison of the result of the tested CSP to the results of the experiment; models of debugging; detection of advantages and shortcomings of each involved CSP. As an example, in Open Modelica and Mathcad packages analysis of simulation opportunities of a problem of the motion of the body thrown at an angle to the horizon is carried out. As a result, assessment of the efficiency of each CSP used for the solution of an objective is made. When training prospective software developers the offered technology is the basis for further development of the modern standard in the field of computer simulation.
Fluid inclusion and isotope (O, H, C, Sr) constraints on the orogenic gold mineralization at the Enche Concha and Tunel prospects, Gurupi Belt, Brazil

The gold mineralization at the Enche Concha and Tunel prospects, northwestern portion of the Gurupi Belt, is hosted in dacites and phyllites that belong to the ca. 2160 Ma-old metavolcano-sedimentary Chega Tudo Formation. These host rocks are variably deformed, from a spaced cleavage to schistose and mylonitic varieties. The hosting structures have previously been defined as produced in the Paleoproterozoic. The hydrothermal alteration processes include carbonatization, sericitization, sulfidation, and quartz veining. These processes are both pervasive and fissure-filling in style. Pyrite is largely predominant over chalcopyrite and sphalerite and gold occurs as a refractory phase in pyrite. Fluid inclusion, stable (O, H, C) and Sr isotopes studies indicate that the hydrothermal alteration and gold mineralization occurred between 260 and 370°C (mostly ~328°C), and 0.85 to 2.8 kbar, from a low-salinity (~5% NaCl), aqueous-carbonic (XCO2 = 0.03-0.13), relatively reduced (log fO2 = -32.1), and near neutral (pH = 5.0-6.2) metamorphic fluid (d18O = +9.4 to +11.3‰, dD = -25 to -28‰). Contributions from deep-seated (lower crust and mantle) sources are suggested by a d13CCO2 value of -7.6‰, and 87Sr/86Sr ratios between 0.702699 and 0.705141, which are lower than those found in the country rocks. Gold was transported by the Au(HS)2- complex and precipitation occurred in response to phase separation, identified by fluid inclusions, and fluid-rock interactions, given by the lowering of the d13CCO2 values. The geological and genetic characteristics are equivalent to those of the orogenic gold system previously defined for the Gurupi Belt.
A Novel Method for Detection of Fraudulent Bank Transactions using Multi-Layer Neural Networks with Adaptive Learning Rate

Fraud refers to earn wealth including property, goods and services through immoral and non-legal channels. Fraud has always been in action and experiences an increasing trend worldwide. Fraud in financial transactions not only leads to losing huge financial resources, but also leads to reduction in trust of customers on using modern banking systems and hence, reduction in eﬀiciency of the systems and optimal management of financial transactions. In recent years, by emerging new technologiesofbankingindustry,newmeansoffraudarediscovered. Althoughanewinformationsystem carry advantages and benefits, new opportunities are made for fraudsters. The applications of fraud detection methods encompasses detection of frauds in an organization, analysis of frauds and also user/customer behavior analytics in order to predict future behavior and reduce the fraud risks. In recentdecades, employingnewtechnologiesinmanagementofbankingtransactionshasrisen. Banks and financial institutions inevitably migrated from traditional banking to modern online banking to provide effective services. Although, the use of online banking systems improves the management of financial processes and speeds up services to customers of institutions, but some issues would also be carried. Financial frauds is one of the issues which organizations seek to prevent and reduce effects. Inthispaper, anovelmachinelearningbasedmodelispresentedtodetectfraudinelectronic banking transactions using profile data of bank customers. In the proposed method, transactional data from banks are leveraged and a multi-layer perceptron neural network with adaptive learning rate is trained to prove the validity of a transaction and hence, improve the fraud detection in electronicbanking. Theproposedmethodshowspromisingresultscomparedwithlogisticregressionand support vector machines.
Developing Interactive Android-Based E-Learning Media as a Virtual Laboratory for the Students of Office Administration Education

The industrial revolution 4.0 leads to an increase in job competition. It should eventually be prepared with personal competence, especially for students in the Department of Office Administration Education. The study aims to develop an interactive e-learning media as a virtual laboratory on a meeting organization course. This study aimed to examine the eligibility of the media and to know the response of the students. This study applied a research and development (R &amp; D) model which developed by Borg and Gall. This virtual laboratory is designed with some attractive features such as (1) meeting schedule, (2) start the meeting, (3) meeting minutes, (4) content sharing, (5) chat, (6) meeting materials, (7) record the meeting, (8) and contact. The current research product is E-Learning media, an interactive virtual laboratory worth applying in the learning activities developed by the researchers. It is made based on the validation of the experts and the positive response of the students.
Pose and Visual Attention: Exploring the Effects of 3D Shape Near-Isometric Deformations on Gaze

Recent research in 3D shape analysis focuses on the study of visual attention on rendered 3D shapes investigating the impact of different factors such as material, illumination, and camera movements.In this paper, we analyze how the pose of a deformable shape affects visual attention.We describe an eye-tracking experiment that studied the influence of different poses of non-rigid 3D shapes on visual attention.The subjects free-viewed a set of 3D shapes rendered in different poses and from different camera views.The fixation maps obtained by the aggregated gaze data were projected onto the 3D shapes and compared at vertex level.The results indicate an impact of the pose for some of the tested shapes and also that view variation influences visual attention.The qualitative analysis of the 3D fixation maps shows high visual focus on the facial regions regardless of the pose, coherent with previous works.The visual attention variation between poses appears to correspond to geometric salient features and semantically salient parts linked to the action represented by the pose.
Geo-environmental Hazards Associated with Lead-Zinc Mining in Ishiagu Ebonyi State Nigeria

IntroductionGeo-environmental hazard assessment; a prerequisite to mine design and development is being neglected in some parts of the world, resulting to environmental degradation and food insecurity.Degree of geo-environmental hazards (Geo-hazards) that may be associated with mining activity varies with what is mined, applicable technology, location of mining site and knowledge of the operators.For example, the degree of geo-hazards associated with limestone mining would be less to that of Pb-Zn mining.The degree of geo-hazards resulting from mining with advanced environmental friendly technology would not equate with that due to poor technology.Geo-hazard consequences of a mine located in urban vicinity would not equate to that of a mine located in a remote area.Finally, geo-hazard resulting from mining activity operated by well-established company would not equate with that operated by illegal poorly established mining operators.Geo-hazard associated with Pb-Zn mining activity in Ishiagu over the past 40 years is of great concern to environmentalists and the community.Discharge of mine waste to farm lands and consequent drainage to nearby stream is environmental crime that calls for investigation in Ishiagu and in other communities along the Benue Trough of Nigeria.Ishiagu is a semi-urban community with moderate population density located in the lower Benue trough of Nigeria (Figure 1a).Presence of Pb-Zn mines and hard rock quarries in the area is responsible to the influx of people from different parts of Nigeria and beyond, making Ishiagu a business vibrant area.Traditionally, Ishiagu people are typically farmers who take advantage of the surface clayey topsoil resulting from weathering of the exposed diabase to excel in the cultivation of tubers such as yam and cassava, and grains, particularly rice.It is possible that Ishiagu community, predominantly the poor farmers are ignorant of the environmental degradation and the obvious health implications.Several Pb-Zn mining companies have operated Ishiagu over the past 40 years, whereas the government office responsible for inspection of mines may not have been forthcoming.The community spokes persons who could have taken up the environmental matter with the operators are probably compromised or incapable.
Leadership in Academic Libraries Trends: Bibliometric Analysis

Academic library in disruption era faces uncertain and unpredictable conditions, therefore a leader who is quick in adapting to changes is needed. This article is aimed to identify studies on academic library leadership which was made by researchers in library and information science. The researcher uses a quantitative descriptive method by using data which were taken from Scopus database (www.scopus.com) by using keyword “leader* academic library” limited only to the title. The researcher then processed and described those data. Abstract from those articles in Scopus analyzed by using content analysis to obtain the most discussed research topics. The results show that among 71 articles on leadership from 1981 to 2019, there are 27 articles which are results of research. Leadership style and capability building in academic libraries are the most discussed topics. This research limitations are: this research only uses 1 database, and the search only applied to the title of the articles. Further research can study more databases and the search is not only applied to the title of the articles only; it can be applied to the abstract or the keyword, thus the research can be generalized more.
Firm Performance And Environmental Munificence: Perspectives Of Differential Performance

Why some firms perform well in natural resource-poor countries (NRPC) and others perform poorly in natural resource-rich countries (NRRC) has become significant in this era of resource booms and heavy natural resource dependence of emerging economies. Drawing from political economy and strategic management theoretical perspectives I use longitudinal multilevel and differential prediction techniques to examine the question. Data from 3,425 firms in 46 countries during the period 2007-2016 show that firms in NRPCs tend to perform better than those in NRRCs. Three factors each from political economy and strategic management account for the differential prediction. I discuss the theoretical and practical implications of the findings for organization scholarship in strategic management.
Preventing Route Leaks using a Decentralized Approach

In the inter-domain routing infrastructure, a route leak is defined as a violation of the routing policy agreed between two Autonomous Systems (AS). Specifically, one AS leaks a route from another AS. There are many examples where route leaks have resulted in large-scale outages on the Internet, taking down several services. Although route leaks seem a simple problem, the solution is complex because: (i) ASes consider -partiallyrouting policy private, (ii) lack of a formal and standard language to express routing policy and (iii) BGP lacks adequate cryptographic-based security. In this paper, we present a novel architecture that provides a solution to route leaks by addressing these three key issues. We define a formal language to express routing policy and we design a blockchain-based architecture to securely communicate it. Our decentralized architecture allows having private policies and interfaces with the current BGP infrastructure seamlessly.
Achieving Optimal Edge-based Congestion-aware Load Balancing in Data Center Networks

Load balancing is the key to improve the performance of data center networks (DCN). The de facto scheme, Equal Cost MultiPath (ECMP) is well-known for its inferior performance due to the coarse-grained and congestion-oblivious nature. As such, more fine-grained and congestion-aware schemes recently emerge. However, current network-based schemes require special modifications to existing switch hardware that makes them hard to deploy. In addition, current edge-based schemes can not achieve optimal load balancing performance due to the lack of accurate in-network congestion information. We propose EMAN, as the first step to achieve optimal load balancing in DCN at the edge. Instead of trying to get the exact network congestion condition (hard to be done at the edge), EMAN directly distributes outbound traffic from a sending endhost proportional to bandwidth of each path, to balance the path utilization. By dynamically updating each path’s available bandwidth using feedback from the receiver, EMAN can gracefully react to network asymmetries caused by failure and flow competition. Both testbed and simulation results show that EMAN can improve the performance by up to 80% (testbed) compared to ECMP, and 66% (simulation) compared to the latest edge-based congestion-aware schemes. EMAN has been implemented as a hot-pluggable Linux kernel module which is transparent to existing applications and kernel TCP stack.
Arsitektur Enterprise Data Management Untuk Unit Kegiatan Mahasiswa &amp; Organisasi Mahasiswa di STMIK Komputama Majenang

The development of Private Universities from year to year is growing. This is directly proportional to the development of student organizations and student activity units. One of the private universities is STMIK Komputama Majenang. STMIK Komputama consists of several Student Activity Units and Student Organizations. STMIK Komputama also has 3 campuses in which each campus has several Student Activity Units and the same Student Organization. With the existence of these 3 campus units, STMIK Komputama Majenang has difficulty in terms of coordination and also the synchronization of the Activities Agenda of the Student Activity Units and Student Organizations. The Enterprise Data Management Architecture is used to connect 3 campuses belonging to STMIK Komputama Majenang. Enterprise Data Management Architecture is the application of architecture used to carry out data management in a Student Activity Unit and Student Organization. In this research, an architecture that is able to synchronize and also produce a good planning of activities in 3 campus of STMIK Komputama Majenang