Reviewerly/exHarmony huggingface dataset:
Aid, Inflation, And Exchange Rate In Sub-Saharan Africa: Empirical Insights from Panel Vector Error Correction Model (PVECM) Approach

The quests for aid arise when developing economies lack inadequate fund to embark on long-term development projects that will promote growth. Generally, aid inflow is expected to lead to capital formation and growth in the sub-Saharan African countries (SSA). The high unemployment rate, poverty rate, and weak growth still witnessed in the region, questioned the exact role of aid. This paper investigates the effect of aid on inflation and exchange rate in 35 sub-Saharan African countries (SSA) between the periods 2000 to 2016 by employing the panel vector error correction model (PVECM) approach following the co-integration properties of the variables. The variables used in the study are aid (official development assistance), inflation rate (INF), and real effective exchange rate (REXR). Control variables such as import as a percentage of GDP (IMPORT), investment as a percentage of GDP (INV) and export as a percentage of GDP (EXPORT) was also employed in the study. Findings from the study revealed that the variables are cointegrated i.e. has a long-run relationship. The outcome of the study also revealed that aid flow is associated with the depreciation of the real exchange rate in the region (SSA). In addition, the study showed that a shock in aid flows would cause a rise in the inflation rate in the region. The study also revealed that a rise in aid would lead to an increase in investment and export in the region (SSA). Furthermore, the study revealed that a shock in aid would cause a rise in import. Based on the result of the study, the study recommends the need for government in the region to determine the optimal aid that will ensure growth and eradicate/reduce poverty in the SSA region. Also, the development partners should assess the monetary conditions of the recipient's economy before the disbursement of aid. Furthermore, the governments in the region are encouraged to utilize the inflow of aid in the importation of capital goods so as to increase the competitiveness of their export in a bid to improve the standard of living of the populace, eradicate poverty and foster growth in the region.
Bayesian Heterogeneity Pursuit Regression Models for Spatially Dependent Data

Most existing spatial clustering literatures discussed the cluster algorithm for spatial responses. In this paper, we consider a Bayesian clustered regression for spatially dependent data in order to detect clusters in the covariate effects. Our proposed method is based on the Dirichlet process which provides a probabilistic framework for simultaneous inference of the number of clusters and the clustering configurations. A Markov chain Monte Carlo sampling algorithm is used to sample from the posterior distribution of the proposed model. In addition, Bayesian model diagnostic techniques are developed to assess the fitness of our proposed model, and check the accuracy of clustering results. Extensive simulation studies are conducted to evaluate the empirical performance of the proposed models. For illustration, our methodology is applied to a housing cost dataset of Georgia.
CX-ST-RNM at SemEval-2019 Task 3: Fusion of Recurrent Neural Networks Based on Contextualized and Static Word Representations for Contextual Emotion Detection

In this paper, I describe a fusion model combining contextualized and static word representations for approaching the EmoContext task in the SemEval 2019 competition. The model is based on two Recurrent Neural Networks, the first one is fed with a state-of-the-art ELMo deep contextualized word representation and the second one is fed with a static Word2Vec embedding augmented with 10-dimensional affective word feature vector. The proposed model is compared with two baseline models based on a static word representation and a contextualized word representation, separately. My approach achieved officially 0.7278 microaveraged F1 score on the test dataset, ranking 47th out of 165 participants.
The Design of Building Management Platform Based on Cloud Computing and Low-Cost Devices

The Design of Building Management Platform Based on Cloud Computing and Low-Cost Devices Li-Te Huang, Yi-Yang Chiu and Ying-Chieh Chan Pages 407-414 (2019 Proceedings of the 36th ISARC, Banff, Canada, ISBN 978-952-69524-0-6, ISSN 2413-5844) Abstract: Indoor environment monitor and control are important aspects of reducing building energy consumption and maintaining occupants visual and thermal comforts. Previous research showed that the lots of buildings were not able to provide designed service level in the daily operation and the feedback from occupants showed that the predetermined service level sometimes did not match occupants desire. However, most of existing buildings and residential buildings did not have building management systems that can systematically monitor the indoor environment, collect occupants feedback, and fine-tune built-in control logic when the occupants needs could not be met. An easy-to-build and easy-to-use build management system can help researchers, engineers, and occupants themselves to identify the issue. The goal of this study was to develop a building management platform with the functions of indoor environment data collection (temperature, relative humidity, solar radiation, etc.), remote control (air conditioner, window, shading), occupants feedback collection (set point, status of building components, etc.), and user interface for retrieving the data and modifying control logic. The platform was developed using Arduino-based and Raspberry Pi-based microcontroller board, low-cost sensors, 3D printing technology, and cloud computing technology. The stored data can serve for personal behavior/comfort analysis, components efficiency analysis, and advanced control logic development. This last part of this paper demonstrated the ability of the developed platform and exhibited the potential application. In the end, we provided further discussion about the potential challenges we might face when developing building management systems in other existing spaces/buildings. Keywords: Building Management Platform; Cloud Computing; Low-Cost Devices DOI: https://doi.org/10.22260/ISARC2019/0055 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
Emergent Trends and Research Topics in Language Testing and Assessment

This study, which is of descriptive nature, aims to explore the emergent trends and research topics in language testing and assessment that have attracted increasing attention of language testing and assessment researchers. To this end, 300 articles published within the last seven years (2012-2018) in two leading journals of the field were analyzed by using thematic analysis method. Overall, the results demonstrated that the assessment of language skills still constitute the backbone of language testing and assessment research. While the term communicative has become the established norm in language testing and assessment, the field has grown more interested in professionalization, understanding the dynamics that underlie test performance and validation. Moreover, the results revealed that even though the latest advancements in the fields of computer, cognitive sciences and information/communication technologies seem to make their way into language testing and assessment, more research is needed to make the most of these advancements and keep up with the rapidly changing nature of communication and literacy in the 21st century. The results are discussed and the implications are made.
Application of Building Integrated Photovoltaic in Hot Humid Climate. Case Study: Office Building in Indonesia

This study investigated application of photovoltaic (PV) panels for office building. Bandung, Indonesia is chosen as case study due to its hot and humid climate. To conduct this study, first, site selection was evaluated, followed by load evaluation using standard requirement for energy-efficient office building. Then, design and size of the system was defined. Feasibility of this study was evaluated from technical and economic indicators, i.e. energy delivered, energy export and import to the grid, yearly savings, and payback period. Simulation of this study was performed with various scenarios on the design electricity load. This study shows that solar PV panels are feasible to be installed in flat roofs and western façade. With 365 m2 of solar panel in total, it can generate 66 MWh electricity per year. If PV provide electricity for lighting inside the building, the payback period is 12 years. This payback period become faster, i.e. 6.24 years, if all the electricity is sold to the grid.
HATEMINER at SemEval-2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier

This paper describes our participation in the SemEval 2019 Task 5 - Multilingual Detection of Hate. This task aims to identify hate speech against two specific targets, immigrants and women. We compare and contrast the performance of different word and sentence level embeddings on the state-of-the-art classification algorithms. Our final submission is a Multinomial binarized Naive Bayes model for both the subtasks in the English version.
DiPETrans: A Framework for Distributed Parallel Execution of Transactions of Blocks in Blockchain.

Contemporary blockchain such as Bitcoin and Ethereum execute transactions serially by miners and validators and determine the Proof-of-Work (PoW). Such serial execution is unable to exploit modern multi-core resources efficiently, hence limiting the system throughput and increasing the transaction acceptance latency. The objective of this work is to increase the transaction throughput by introducing parallel transaction execution using a static analysis technique. We propose a framework DiPETrans for the distributed execution of the transactions in a block. Here, peers in the blockchain network form a community to execute the transactions and find the PoW parallelly, using a leader-follower approach. During mining, the leader statically analyzes the transactions, creates different groups (shards) of independent transactions, and distributes them to followers to execute them in parallel. After the transaction executes, the community's compute power is utilized to solve the PoW concurrently. When a block is successfully created, the leader broadcasts the proposed block to other peers in the network for validation. On receiving a block, validators re-execute the block transactions and accept the block if they reach the same state as shared by the miner. Validation can also be done as a community, in parallel, following the same leader-follower approach as mining. We report experiments using over 5 Million real transactions from the Ethereum blockchain and execute them using our DiPETrans framework to empirically validate the benefits of our techniques over traditional sequential execution. We achieve a maximum speedup of 2.2x for the miner and 2.0x for the validator, with 100 to 500 transactions per block. Further, we achieve a peak of 5x end-to-end block creation speedup using a parallel miner over a serial miner when using 6 machines in the community.
Learning to network

Provides personal anectdotes on the startup of the ARPANET.
Parameter-Free Outlier Scoring Algorithm Using the Acute Angle Order Difference Distance

An anomaly scoring algorithm assigns the anomalous rating to an instance in a dataset which provides a large value for an outlier. In 2013, one of the parameter-free techniques called the Ordered Difference Distance Outlier Factor algorithm is proposed. It calculates a score using an ordered difference distance among all instances which derives from the distance matrix sorted in each row before computing the difference. The score contribution from other instances must be compared with the global minimum distance to avoid misdetecting boundaries. However, this degrades the performance of the detection rate. To avoid the use of the global minimum distance term, the new technique is proposed using the ordered difference distance along the appropriate direction based on the acute angle. This technique is called the acute angle ordered difference distance outlier factor (AOF) algorithm. Three collections of ten synthesized datasets are designed to show the performance of AOF. The AOF algorithm reports very high scores for anomalies in synthetic datasets and has better performance than OOF when the anomalies are close together.
TokyoTech_NLP at SemEval-2019 Task 3: Emotion-related Symbols in Emotion Detection

This paper presents our contextual emotion detection system in approaching the SemEval2019 shared task 3: EmoContext: Contextual Emotion Detection in Text. This system cooperates with an emotion detection neural network method (Poria et al., 2017), emoji2vec (Eisner et al., 2016) embedding, word2vec embedding (Mikolov et al., 2013), and our proposed emoticon and emoji preprocessing method. The experimental results demonstrate the usefulness of our emoticon and emoji prepossessing method, and representations of emoticons and emoji contribute model’s emotion detection.
Professional personal potential and the parameters of evaluation of its development

Е. В. Суворова, О. В. Андреева, Т
Reinforcement Learning for Robots Path Planning with Rule-based Shallow-trial

A key skill for mobile robots is the ability to navigate efficiently through their environment, and reinforcement learning is widely used in path planning for mobile robots. However, this algorithm has a slow convergence speed and a large number of iterations. There are few studies on how to improve learning efficiently from the perspective of acquisition in rule-based shallow-trial strategy. In biological world, animals depend on their own empirical knowledge when making path planing. Humanity has transcendental knowledge, which is of great help to peoples navigation. We take the transcendental knowledge of human behavior, and express it acts as shallow-trial rules, then apply the rule-based shallow-trial reinforcement learning(RSRL) to the navigation learning of robot and improve learning efficiently.
Musical Form and its Elucidation in School Textbooks of Music Literature

Familiarization with musical form – a capacious and multiple valued phenomenon – is connected with the initial stage of educating a musician. An important role in this process is carried out by textbooks. An encompassing perception of musical form, the basic types of structures in classical and romantic music and their individual features is taught to a pupil of children’s music schools in music literature classes. In the article certain features of expounding on the subject of “musical form” for schoolchildren are elaborated by the example of four textbooks for the first year of study of this subject (written by Andrei Frolov, Maria Shornikova, Yanina Ostrovskaya & Liudmila Frolova, Zoya Osovitskaya & Anna Kazarinova). The content of the corresponding sections is variable. The list of the spanned examples is more compact in the book by Osovitskaya and Kazarinova (it is defined by the resources of Tchaikovsky’s “Children’s Album”). The subject is unfolded to the fullest extent in the textbooks of Ostrovskaya, Frolova and Shornikova: here almost all the classical-romantic forms are demonstrated, as are some of the baroque forms (the fugue and the suite). In their descriptions of the musical constructions, the authors maintain different perspectives. Osovitskaya and Kazarinova are concentrated on an integral analysis of the “Children’s Album” and its constituent pieces; at the same time Frolov combines the theoretical and practical approaches in comprehension of form, giving recommendations for the compositions. Shornikova makes systematical use of interdisciplinary analogies; Ostrovskaya and Frolova give intense attention to the structural particularities of each of the examined constructions. The correlation of the principles of study of musical forms present in school textbooks allows us to choose the most optimal of them. The article comes up with the conclusion that the use of the descriptive manner upon the first discussion of form is insufficient, since in this case the connection between the content and the constructive sides of the musical structures is not accentuated. The inaccuracies allowed by the authors in their characterizations of a number of forms testify of the necessity of reviewing such types of tutorial editions. Keywords: study of musical form, textbooks of musical literature for children’s music schools for the first year of study, Yanina Ostrovskaya, Liudmila Frolova, Zoya Osovitskaya, Anna Kazarinova, Andrei Frolov, Maria Shornikova.
Dynamic Content Monitoring and Exploration using Vector Spaces

This doctoral research project investigates using Quantum Theory (QT) to represent language, especially in some dynamic scenarios, e.g. when dealing with dynamic corpora or interactive tasks. The author plans to propose a quantum state driven framework for language problems and generalize it in a high-dimensional tensor space. Dynamics will be modeled by the formalism thereof of quantum evolution governing the update of quantum states. The author argues that this proposal will pave the way towards a new paradigm which may provide some novel insights about how to represent the language and its evolution in dynamic scenarios.
Grenade-Cauchy operator integrated artificial bee colony optimisation for QoS-based reliable web service composition

Majority of the dynamic web service composition techniques in the literature addresses the problem of web service composition through the perspectives of quality of service (QoS) or transactional characteristics. Grenade with Cauchy operator integrated artificial bee colony optimisation (GCO-ABC) algorithm is proposed as an attempt of developing a dynamic service composition involved computation methodology that depends on the integration of transactional and QoS-based properties of web services. GCO-ABC algorithm is applied on the work flow sequence of web service composition developed as a constrained directed acyclic graph for determining the near optimal solution with efficacy and it is also predominant in comparison to the traditional ant colony optimisation algorithm (ACOM) and its variant improved ant colony optimisation algorithm (IACOM). The determined results investigated through empirical and simulation means infer that the proposed scheme is not only efficient but also capable of approximating the searching solutions into a much more optimal candidate solution.
A note on tools and techniques for end-to-end QoS monitoring in Internet of Things

Internet of things (IoT) technology has become the focus of many researchers, and quality of service (QoS) is considered one of the most important challenges for IoT technology. Additionally, the expectations of end users in the IoT environment are of great importance, which means that quality of experience (QoE) evaluations are significant. Therefore, this paper proposed a scheme to guarantee QoS in IoT environments. For this scheme, the most efficient QoS methodology was selected based on the data and network types in the IoT environment. The proposed QoS scheme classified the data transmitted through IoT systems into two main statuses. In the first status, called “individual”, the data were exchanged through one type of large-scale network at a time. In the second status, “overlapped”, the data passed through an area that comprised a mixture of different networks. The proposed scheme handled the QoS issue for both statuses. A QoE scheme evaluating the IoT data using different layers was also proposed. The proposed QoS and QoE schemes were then combined to create a more generalized QoE/QoS-oriented scheme, which was used to adapt the QoS scheme to achieve the highest efficiency. The performance of the QoE/QoS-oriented scheme was measured in a simulation environment that was constructed using an NS-3 package. First, the performance of the proposed QoS scheme was measured by two groups of metrics. The first group was general and comprised throughput, delay, and energy consumption. The second group was particular to the proposed QoS scheme and comprised transformation between individual and overlapped statuses, usage percentages for each QoS model, and the degree of complexity of the overlapped areas. The first group of metrics showed that the proposed QoE/QoS scheme had a higher efficiency than that of the previous individual QoS models. The second group of metrics showed that the features of the proposed QoS scheme worked efficiently. Finally, delay, energy consumption, throughput, and jitter were improved after the QoS methodologies were adapted using the proposed QoE scheme.
Effectiveness Analysis of Entrepreneurship Model of Development Qualities of Future Managers

The article describes the psychological characteristics of the development of professionally significant qualities of future managers of organizations. The results of the formative experiment were presented and the components of the professionally significant qualities of future managers were identified that are most sensitive to the effects during the acquisition of professional competence and becoming a professional manager. The development of professionally significant qualities in the process of the formative program was based on the passing by participants of an experimental study of special trainings involving the development of the components of professionally significant qualities of future managers. Conducted three modules of training sessions contributed to the gaining a new communicative experience by the students in the context of future professional activities, which gave them the opportunity to develop skills for effective professional interaction and improve their perception of themselves as the future manager.
Average maps model of super fuzzy cognitive to analyze middle class family problem

In this manuscript we use the new fuzzy model called ASFCM, to study the problems of middle class family. Here we deal with families on a particular group, here we take all the families according to their income. For the group of expert opinions associated with the analysis of family problem happen to vary widely as they are all from different categories. These expert’s opinions varies according to their income. So this new technique, which we have introduced, is found to be a relevant tool in the analysis of the problem under investigation.This manuscript has 3 parts. Section one is introduction of the new notion of Average Super Fuzzy Cognitive Maps (ASFCMs). Section two deals the application of the new technique to the family problems. The third section gives the conclusions. The ankle-brachial index (ABI) is defined as the ratio of the Systolic Blood Pressure (SBP) measured at the ankle to the SBP measured at the brachial artery. Studies show that ABI can also indicate atherosclerosis at various vascular sites. Therefore it can be used as a prognostic marker tool for cardiovascular events and functional impairments, even in the absence of symptoms of peripheral artery diseases (PAD). The standard threshold value of ABI value of 0.9 appears to be lower in patients with complications. A pilot study has been conducted on 77 subjects. Results show that ABI measurement can be used as a screening tool for PAD but requires further larger study for its consolidation.