Reviewerly/exHarmony huggingface dataset:
EVALUATION OF THE NORMALISASI POLICY IN JAKARTA, INDONESIA USING SYSTEM DYNAMICS

Governance deficit in Jakarta, Indonesia is often associated to its pressing issues of too much, too little, and too dirty water. Although flood has become an important political issue and the government is pushing a landscape change in the riverbank areas, the public policy in Jakarta has yet to comprehend the complex linkages between the gap in water provisioning and flooding. Flood is one major issue that has affected Jakarta since as early as 1872. Subsequently, major flood events occurred with the most recent being in 2015. To solve this problem, the government has implemented several policies, with the most recent one named as “Normalisasi.” This policy focuses on increasing the flow capacity of the river to prevent it from overflowing during heavy rain events. Under this policy, the government claims eviction of informal settlements from the riverbank areas; widening rivers and canals; and dredging the river beds. Many scholars have criticized the overly technocratic framing of this policy, its covert agenda for attracting investments in infrastructure development in catchment areas, lack of empathy towards informal settlers, along with lack of vision for an inclusive and resilient socio-hydrological system. This study uses system dynamics modeling to illustrate the interplay of social and hydrogeomorphological factors leading to Jakarta’s vulnerability to flooding and to evaluate the policy response of Normalisasi against this vulnerability and future risk scenarios. The model is further used to test and compare two categories of policy strategies of increasing dredging efficacy and an integrated waterscape policy. Though the former seemed cost-efficient in short term and less complex in terms of governance, the latter will help in long-term resilience as it considers the Jakarta flooding issue more holistically with future climate risks. However, implementation of such an integrated waterscape policy requires the institutionalization of polycentric governance and also needs a boundary organization to increase participation of diverse actors across governance levels.
Determination of Heat and Momentum Fluxes Over Baghdad City

In this study heat and momentum fluxes have been determined at Al-Mustansiriyah University, Baghdad, Iraq, by using eddy correlation method. It is one of the methods which determines heat and momentum fluxes and it is considered direct and accurate. This method depends on high response instruments like Ultrasonic Anemometer (model: 1590- PK- 020) which is used in this study. Observation period is about 53 days for 24 hours in months June, July and August from 15/06/2016 to 06//08/2016 and the observations included wind speed and temperature every second. MATLAB program has been used to process huge data to calculate heat and momentum fluxes (H and ). The maximum value of H equals 127.6 Wm-2 in 10:30 at 26/07/2016 and minimum value equals -58.9 Wm-2 in 07:30 at 29/06/2016, as well, the maximum value of equals 0.134535 Nm-2 in 15:00 at 03/08/2016 and minimum value equals -0.4649 Nm-2 in 03:00 at 01/07/2016. It is found that there is an inverse relationship between H and. Also maximum frequency of friction velocity at unstable conditions.
CrowDevBot: A Task-Oriented Conversational Bot for Software Crowdsourcing Platform (S)

With the trends of developing software on the Internet, many software crowdsourcing platforms are emerging.They attract a lot of developers to bid for crowdsourced projects and develop software systems collaboratively.In this paper, we present CrowDevBot, a task-oriented conversational bot for software crowdsourcing platform, that aims to assist online users in completing crowdsourcing-related tasks in a more natural manner.The key idea of CrowDevBot is to: (1) combine a rulebased method and an SVM-NaiveBayes-C4.5 integrated learning method to discover users' intention; (2) employ an integrated CRF (conditional random field) method with novel features to improve the performance of slot filling; and (3) leverage a software service knowledge base to unify entity names and predefine the key slots of user query.We implement CrowDevBot and integrate it into JointForce, an IT software crowdsourcing platform in China.To the best of our knowledge, this is the first time that a task-oriented conversational bot is practically used in software crowdsourcing platform(s).We evaluated our approach on real data set from JointForce.The results show that our intention detecting method achieves F1-score of 87% on the limited training data.For the slot filling, the F1-score of our integrated CRF model reaches 82%, 8% higher than that of the normal CRF model.
The Effect of Contextual Teaching and Learning Model through Writing Poetry Ability in Eight Grade Students of SMP Negeri 2 Garoga in Academic Year 2018/2019

This study dealt with the The Effect of Contextual Teaching and Learning Model through Writing Poetry Ability in Eight Grade Students of SMP Negeri 2 Garoga in Academic Year 2018/2019 .The aims of this study are a) to determine the average poetry writing ability in Eight grade students of SMP Negeri 2 Garoga Academic Year 2018/2019 using the Contextual Teaching and Learning learning model.b)To determine the average ability to write poetry by eighth grade students of SMP Negeri 2 Garoga Academic Year in 2018/2019 with expository methods.c) To explain the effect of using the Contextual Teaching and Learning learning model ability to write poetry by eighth grade students of SMP Negeri 2 Garoga Academic Year 2018/2019.The Result of the average value of student learning outcomes in eight grade students of SMPN 2 garoga to write poetry before getting benefits is 68.79 (good enough).77.06 (Good) Model of Teaching and Contextual Teaching have a significant (positive) influence on the ability to write texts by eighth grade students of SMPN 2 Garoga in Academic 2018/2019 with the hypothesis that 0> is 3,59 > 2,05 proven that the alternative hypothesis ( ) is accepted.
Premenstrual Syndrome- Prevalence, Severity and Effect on Academic Performance: A Comparative Study Between Students of Medicine and Literature

Premenstrual syndrome (PMS) is a common health problem in young women that affects their personal and professional lives.METHOD: This is a cross-sectional study, which was performed at Taibah University, Saudi Arabia, in 2015-2016.This study explores the determinants of PMS and its prevalence, severity and impact on students of medicine and literature respectively.RESULT: We find that medical students suffer less from PMS than literature students.The latter experience more severe symptoms and are highly affected in their routine chores, academic performance and self-care.CONCLUSION: Awareness and education about PMS and its risk factors should be considered for effective management of the syndrome and enhancement of the quality of daily life among Saudi women.
Specialists’ Training of in Industrial Internet of Things Systems Development

Training of qualified industrial Internet of Things systems developers is a key factor in the implementation of the program "Digital economy of the Russian Federation".In this paper the concepts "Internet of Things" and "industrial Internet of things" are compared.Competences of technical specialist in the development of Internet of things systems are defined.Experience of the Department of Intelligent control systems and automation (MTUCI) in training bachelors and masters in "Automation of technological processes and production" и "Management in technical systems".Laboratory workshops is aimed at providing the students with competences of the developers of It-systems are described.
The Blockchain Technology in State Institutions

The problems of building a distributed registry (blockchain) for state institutions are considered.The main tasks, the solution of which is necessary when creating the registry, are highlighted.The model of formation of registry blocks is given.Results can be useful to designers and administrators of the state institutions distributed registry .
Toward Cost-Effective Mobile Video Streaming through Environment-Aware Watching State Prediction

Mobile video applications are becoming increasingly prevalent and enriching the way people learn and are entertained. However, on mobile terminals with inherently limited resources, mobile video streaming services consume too much energy and bandwidth, which is an urgent problem to solve. At present, research on cost-effective mobile video streaming typically focuses on the management of data transmission. Among such studies, some new approaches consider the user’s behavior to further optimize data transmission. However, these studies have not adequately discussed the specific impact of the physical environment on user behavior. Therefore, this paper takes into account the environment-aware watching state and proposes a cost-effective mobile video streaming scheme to reduce power consumption and mobile data usage. First, the watching state is predicted by machine learning based on user behavior and the physical environment during a given time window. Second, based on the resulting prediction, a downloading algorithm is introduced based on the user equipment (UE) running mode in the LTE system and the VLC player. Finally, according to the corresponding experimental results obtained in a real-world environment, the proposed approach, compared to its benchmarks, effectively reduces the data usage (14.4% lower than that of energy-aware, on average) and power consumption (about 19% when there are screen touches) of mobile devices.
Human Ability Improvement with Wireless Sensors in Human Computer Interaction

Wireless sensors are nowadays engaged in almost every human endeavour and has made live more convenient and conducive.Human Computer interaction (HCI), which is about communication between human user and computer system or devices is a field of computer science that is gaining a lot of recognition in the improvement of human abilities.The communication between a person or user and the computer may involve certain device, medium or channel that has to be configured or programmed in a way that will facilitate an efficient interaction.Wireless sensors in HCI enhances and improves the way of life and the interaction in a wide variety of domains Therefore, it is important to know the specifications of these sensors and how they are being used in order to create human computer interfaces, which tackle complex tasks.This paper comprehensively carried out an overview of wireless sensors and HCI, security requirements and challenges of wireless sensors and how wireless sensors interrelate with HCI to improve human abilities in their daily activities.Finally, a brief discussion on the future of sensors in HCI is presented.
Efficient Network Representations Learning: An Edge-Centric Perspective

Learning succinct/effective representations is of essential importance to network modeling. Network embedding is a popular approach to this end, which maps each vertex of a network to a fixed-length, low-dimensional vector. Previous efforts on network embedding mainly fall into two categories: (1) link based and (2) link + node feature based. In this paper, we provide an edge-centric view where features are associated with edges, in addition to the network structure. The edge-centric view provides a fine-grained characterization of a network, where the dynamic interactions between vertices are considered instead of the static property of vertices. Methodology-wise, we propose an efficient network representations learning approach called the NEEF (network embedding with edge features) model. In particular, the NEEF model seamlessly incorporates the edge features when considering the proximity of a pair of vertices. The model is then trained to maximize the occurrence probability of the neighboring vertices conditioned on the edge features. In our experiments, we show that many of the real-world networks can be abstracted as network with edge features, among which we choose the DBLP coauthor network, the Reddit review network, and the Enron email network for evaluations. Experimental results show that our proposed NEEF model outperforms the other state-of-the-art baselines on tasks such as classification and clustering. We also visualize the learned representations, and show intuitive interpretations of the NEEF model.
THE BLOCKCHAIN TECHNOLOGY AND CLOUD COMPUTING IMPACT FOR CRYPTOECONOMY CONTEXT

In the human evolution, the man evolved alongside society in a series of revolutions that led to great improvements on all domains: cultural, social, industrial, etc.Today we are living what futurologist as Alvin Toffler in "Future Shock" and more recently Michael Dertouzos in "What Will Be: How the New World of Information Will Change Our Lives" anticipated more than 20, respectively 50 years ago.They imagined a world in which the information technology is based on learning.Today, technological singularity is no longer just a concept, it's a reality.The technical and scientific progress that has materialized in real revolutions has recorded not only a one-way amplification movement, but perhaps even an acceleration.Today, on the 30th anniversary of the World Wide Web, Information and Communication Technology (ICT) has become not only a neo-factor of production for most businesses but the indispensable factor of any activity.This is the context in which a new technological revolution -the Blockchain revolution -takes place in the face of an "apparent financial crisis" in 2008-2009 and a lower level of confidence.The advantages of this technology, coupled with another relatively modern development (as an implementation, not as a concept) of ICT, namely cloud computing, are now leading to increasingly spectacular solutions in the digital economy, electronic money, e-Government, or electronic citizen (e-citizen).In this paper we will be able to deal with the impact of the two technologies in the context of the digital economy, materialized in at least two paradigms: Blockchain as a Service (BaaS) and Blockchain as a Cloud (BaaC).
STUDYING CH. AITMATOV, WORKS AS A CONDITION FOR DEVELOPING UNIVERSAL HUMAN VALUES

Introduction. The article deals with the problem of educating a new generation of pedagogues on the basis of studying the works by Ch. Aitmatov in the process of globalization. The purpose of the article is to analyze the works by Ch. Aitmatov and, using the method of content analysis, to prove that the development of universal human values in future teachers is very effective when studying with students the novel “Axeman’s Block” by Ch.Aitmatov. The research methodology. The author used the method of content-analysis in order to reveal whether the choice of this work by Ch. Aitmatov is really effective for the formation of proper value orientations during the educational process. The results of the study. Making use of the method mentioned above, it was shown which of the universal human values contained in the book by Ch. Aitmatov are particularly characteristic of it and, thus, can facilitate the formation and upbringing of today’s generation of students as well as the future ones. The analysis of the book “Axeman’s Block” revealed that the belief in the eternal moral values of religious origin is the most characteristic value-orientation feature of this novel. Conclusion. The data obtained showed that the content of the works by Ch. Aitmatov is rich in obvious and hidden moral values ​​that can be developed in future teachers in the process of studying the works by Ch. Aitmatov. Moreover, the results of the research can serve as a basis for more effective professional training of future pedagogues and for developing in them important value orientations.
Foreshadow-VMM: Feasibility and Network Perspective

On August 14, 2018, a new set of vulnerabilities collectively named “L1 terminal fault” were announced. Systems with microprocessors utilizing out-of-order execution could allow unauthorized disclosure of information residing in the L1data cache, by tweaking the virtual memory abstraction. The vulnerability was therein mentioned for three different scenarios. In this demo-paper, we provide practical evidence about the feasibility of the most complex “VMM” case of an attacker residing in a Virtual Machine (VM), and targeting information leakage from the host OS and other independent VMs.
TouchGlass: Raycasting from a Glass Surface to Point at Physical Objects in Public Exhibits

Physical objects such as natural items or fine art pieces are often placed behind glass cases to protect them from dust and damage. Generally, interacting with such objects is indirect, based for example on an adjacent touch interface detracting users’ attention from the object. In this paper, we explore whether the glass case could be used as an input surface to point and select distant physical objects. With such an approach, the glass case offers a physical delimiter for interaction to avoid unintended activations. We explore this innovative approach through a two steps approach. First, we carry an informative study with 46 participants to validate the most appropriate “walk-up and use” technique. Our results show that using a ray orthogonal to the glass surface is the most natural approach in a public setting. Next, we further explore this orthogonal raycasting technique and conduct a target acquisition experiment to evaluate the impact on target selection performance of the target size, target distance, presence of spatial references and user’s head position with regards to the glass case. Results reveal that using the glass as touch surface allows to easily select targets as small as 3 cm up to 35 cm away from the glass. From these results, we provide a set of guidelines to design interactive exhibits using a touch glass case.
PROGRAM OF FUTURE ENGINEERS ADAPTATION TO EDUCATIONAL AND PROFESSIONAL ACTIVITIES IN THE UNIVERSITY

Problem and goal. The article analyses the extent of the problem of adaptation of students to the educational and professional activities in the University and the influence of adaptation on the quality of training. In pedagogical theory and practice are insufficiently addressed the problem of adaptation of future engineers to educational and professional activities in the University, in particular, for specialists in the field of electronic systems. It is shown that for efficient adaptation of students – future engineers need to pedagogical support of process of adaptation on the basis of the developed programs adapting future engineers to educational and professional activities in the University and the conditions for its implementation. Material and Methods. Research methodology comprise analysis of psychological-pedagogical literature on the problem support of process of adaptation, normative documents, State educational standards, methodical, professional literature, synthesis of pedagogical experience with training of specialists in the field of electronic systems. Results. The proposed programs take into account the orientation of educational and professional activities and is implemented in the following areas: engineering, socio-professional and personality-oriented. In each area of the identified factors that affect the adaptation process, defined tasks of pedagogical support of process of adaptation, justified the organizational and pedagogical conditions, designed forms and methods of ensuring the effectiveness of future engineers to adapt to the educational and professional activities at the University. Conclusion. Adaptation program future engineers to educational and professional activities in the University and organizational and pedagogical conditions conducive to: supplement the content of the educational and professional activities of material, developing digital technology in the training of future engineers; the involvement of future engineers to practical activity, including safe professional activities; mainstreaming the needs of future engineers in mastering the techniques of self-organization, self-development and self-realization, in understanding the meaning, values and priorities of the educational and professional activities.
Jointing Knowledge Graph and Neural Network for Top-N Recommendation

Currently, neutral networks attract much attention and show great potential in recommendation systems. The existing works mainly aim at leveraging neural network to model the nonlinear representations of users and items. However, they only use historical interaction sequence of user-items to learn the latent features of users and items, while ignoring the rich self-attributes of items. Recent methods utilize knowledge graphs as auxiliary information to learn the latent features between users and items, but they fail to represent the relevance and similarity of attributes among items. Based on this observation, we propose a novel model named JKN that incorporates knowledge graph and a neural network for item recommendation. The key point of JKN is to learn accurate latent representations of item attributes through knowledge graph, then to integrate them into a feedforward neural network to model user-item interactions in nonlinear. Empirical results on a real-world dataset demonstrate the superior performance of our model in Top-n recommendation task.
Deep discriminative correlation tracking based on adaptive feature fusion

Discriminative Correlation Filter (DCF) is a fashionable method to treat with the challenges in visual tracking tasks. Recently, the integration of DCF and Convolutional Neural Network (CNN) obtains a favorable tracking performance. However, how to make full use of the CNN features under the DCF tracking framework is still a challenging problem. In this paper, we designed an uncertainty measurement of the correlation response map, and based on this measurement, we proposed an adaptive feature fusion strategy to fuse the correlation response maps of different CNN features. Finally, a deep discriminative correlation tracking (DDCT) algorithm based on this adaptive feature fusion strategy is proposed. Meanwhile, the separate scale correlation filters based on scale pyramid and HOG feature are also introduced to further treat with the scale estimation. Moreover, in order to solve the problem of tracking drifts due to the severe occlusion or serious appearance changes of the target, we present a new adaptive and selective update mechanism to update the discriminative correlation filters and scale correlation filters effectively. Extensive experimental results on OTB2013, OTB2015 and Temple Color 128 benchmark datasets show that the proposed algorithm achieves a better overall performance compared with the state-of-the-art methods.
Geology, Geomorphology and Tectonics of India: Introduction

The earth crustal growth since its formation still need in depth research is the conclusion of the three International Conferences on Precambrian Continental Growth and Tectonism, in 2005, 2009 and 2013, organised at the Institute of Earth Sciences of Bundelkhand University, Jhansi, India and its proceedings have valuable source for advance research published the great ideas and achievements from scientists (Chandra et al. 2007; Singh and Chandra, 2011 and Singh et al., 2015). Therefore, this thematic issue planned for consider of crustal growth and tectonic evolution of Indian shield which include 7 research articles on geodynamic evolution of earth, geomorphology, structural, petrologic, isotopic, tectonic, and geochemistry investigations related to the Indian shield and its economic importance (Figure 1).