A Novel Sentence Completion System for Punjabi using Deep Neural Networks

Sentence completion systems are actively studied by many researchers which ultimately results in the reduction of cognitive effort and enhancement in user-experience. The review of the literature reveals that most of the work in the said area is in English and limited effort spent on other languages, especially vernacular languages. This work aims to develop state-of-the-art sentence completion system for the Punjabi language, which is the 10th most spoken language in the world. The presented work is an outcome of the results of the experimentation on various neural network language model combinations. A new Sentence Search Algorithm (SSA) and patching system are developed to search, complete and rank the completed sub-string and give a syntactically rich sentence(s). The quantitative and qualitative evaluation metrics were utilized to evaluate the system. The results are quite promising, and the best performing model is capable of completing a given sub-string with more acceptability. Best performing model is utilized for developing the user-interface.

Hybrid Photovoltaic/Thermal (PVT) Collector Systems With Different Absorber Configurations For Thermal Management – A Review

Thermal management in hybrid Photovoltaic/Thermal (PVT) collectors is essential to derive electrical and thermal energy from a single system. Effective removal of heat gained by the photovoltaic module during its operation is possible with a proper thermal absorber design. Hence, thermal absorber design has gained prominence, and various design techniques were attempted in the literature to enhance energy delivery among different stakeholders. Most research groups tried to design absorber configurations attached to the PV panel's front or rear side. Absorber design configurations include various channel materials and geometry as well as other physical parameter combinations. The quantitative thermal energy delivery from the system could vary based on the absorber configuration and be useful for different applications. This study reports a detailed review to understand the relation between thermal absorber design configurations and the potential energy recovery from PVT systems. This study helps the designers identify channel designs, materials, and adequate working fluids for enhanced heat transfer to anticipate better thermal management of PVT systems. Challenges and suggestions to develop state of the art thermal absorber designs for relative commercial thermal applications using PVT systems are conveyed.

STRATEGY IN DEVELOPING HUMAN RESOURCE COMPETENCY IN VUCA WORLD ERA (A Case Study in PPSDM Ministry of Home Affairs Makassar Region)

Human Resources (HR) is one of the crucial factors which cannot be separated from an organization. In this era, developing HR is in VUCA World (Volatile, Uncertain, Complex, Ambiguous) is a challenge that an institution must deal with. State Civil Apparatus competency development institute, particularly in the Ministry of Home Affairs, is PPSDM in Makassar Region. The strategy for developing competency in the VUCA world era is a vital task. The method used in this research is literary study, while the research location is in PPSDM of the Ministry of Home Affairs Makassar Region. The present research result is that the correct strategy to develop state civil apparatus competency corresponding to Coronavirus Pandemic is to employ digital service (digitalization) through optimizing institutional and program activities to face the VUCA world. This method was applied to support LMS (Learning Management System) in PPSDM of the Ministry of Home Affairs Makassar Region creatively and innovatively. It is supported by a synergic inter-institutional managerial system and learning organization; subsequently, it holds on training rate indicator concept and learning concepts corresponding to the current circumstances by involving all stakeholders.

Researching Data Sets to Develop State Library Standards

California developed standards for library program factors that provide the conditions for students to meet library standard outcomes. To base those program standards empirically, the researchers analyzed three 2008-9 reputable data sets: California’s school library data set, AASL’s School Libraries Count data set, and a national School Library Journal data set. Standards were clustered into two sections: baseline factors, and statistical standards for resources. Findings revealed that school libraries that met the “baseline” standard were significantly different from those libraries that did not meet those standards. Once the baseline set of factors were determined, descriptive and correlational statistics were applied to the data sets, with the resultant figures based on the average figures supplied by those libraries that met the baseline factors.

Ti3C2 MXene–polymer nanocomposites and their applications

Favorable interactions between polymer chains and Ti3C2 MXene flakes are essential to develop state-of-the-art MXene/polymer nanocomposite devices.

Mustard Yield Prediction using State Space Models

Forecasting of agricultural outputs well in advance has always been the focus of numerous researchers due to its direct implications on various areas of the society. This study aims to develop State Space Models (SSMs) with weather as an exogenous input over the commonly used ARIMA and regression analysis for yield prediction for mustard crop in eight districts of Haryana state in India. These models are time-varying parameter models and take into account for changes that are known over time in structure of the framework. SSMs with various kinds of growth trends were tried and model performances were compared using AIC and BIC criteria but the growth trend represented by polynomial splines of order-2 with the weather as an exogenous input was chosen as the most appropriate model for mustard yield prediction in all the eight districts under study. Based on the developed models, post-sample yield predictions for the next three years, i.e. 2016-17 to 2018-19 have been obtained and the deviations from actual values are also calculated which came out to be acceptable in an agricultural setup.

Comparative Study of Various Convolutional Neural Networks on Cifar-10

Image recognition plays a foundational role in the field of computer vision and there has been extensive research to develop state-of-the-art techniques especially using Convolutional Neural Network (CNN). This paper aims to study some CNNs, heavily inspired by highly popular state-of-the-art CNNs, designed from scratch specifically for the Cifar-10 dataset and present a fair comparison between them.

Multilingual Legal Information Retrieval System for Mapping Recitals and Normative Provisions

This paper presents a multilingual legal information retrieval system for mapping recitals to articles in European Union (EU) directives and normative provisions in national legislation. Such a system could be useful for purposive interpretation of norms. A previous work on mapping recitals and normative provisions was limited to EU legislation in English and only one lexical text similarity technique. In this paper, we develop state-of-the-art text similarity models to investigate the interplay between directive recitals, directive (sub-)articles and provisions of national implementing measures (NIMs) on a multilingual corpus (from Ireland, Italy and Luxembourg). Our results indicate that directive recitals do not have a direct influence on NIM provisions, but they sometimes contain additional information that is not present in the transposed directive sub-article, and can therefore facilitate purposive interpretation.

FORECASTING MIGRATION FLOWS USING PREDICTIVE ANALYTICS

The present article considers the need to predict migration flows using Predictive Analytics. The Russian Federation is a center of migration activity. The modern world is changing rapidly. An effective migration policy requires effective monitoring of migration flows, assessing the current situation in our and other countries and forecasting migration processes. There are information systems in Russia that contain a wide range of information about foreign citizens and stateless persons that provide the requested information about specific foreign citizens, including grouping it on various grounds. However, it is not possible to analyze and predict it automatically using thousands of parameters. Special attention in Russia is paid to digitalization. Using information technologies (artificial intelligence, machine learning and big data analysis) to forecast migration flows in conditions of variability of future events will allow to take into account a number of events and most accurately predict the quantitative and so-called "qualitative" structure of arrivals. The received information will help to develop state policy and to take appropriate measures in the field of migration regulation. The authors come to the conclusion that it is necessary to amend existing legal acts in order to implement information technologies of Predictive Analytics into the practice of migration authorities.

Concerning Foreign Migrants’ Integration in Russian Empire

The article deals with the possibility to use historical experience of pre-revolutionary Russia to develop state policy in the migration sphere. During centuries of multinational and multicultural society formation a vast and unique integration experience was acquired. It promoted unity and integrity of the country, its development and geo-political interests. In general policy of Russian empire demonstrated consistency in resolving problems of home and foreign migration, clear understanding of goals aimed at ensuring country’s interests. The effective state system gave an opportunity to help migrants, to control their stay, to regulate migration flows, to provide differentiated approach to various categories of foreigners and internally displaced persons. Today’s migration policy in Russia is more complicated as we have an ineffective system of social and cultural adaptation and integration of foreign migrants, which requires serious optimization and building the centralized infrastructure. The objective and critical interpretation of home experience of the past carried out by the author could enrich academic support of migration policy at the current stage and create the efficient system of migrants’ inclusion in the host society.