Reviewerly/exHarmony huggingface dataset:
Generating Structured Database Queries Using Deeply-Bidirectional Natural Language Encodings

In the era of Information and Technology, databases have emerged as an irreplaceable solution to store world's data and effectively use it. They make interaction with data more efficient but on the other hand, it requires the user to understand a query language to access the data. A system that could effectively translate simple Natural Language to database queries would solve the problem of the steep learning curve required to learn database interface query language. The accepted paradigm to solve the problem is to model it as a sequence-to-sequence problem that can in essence translate Natural Language into database queries. Existing state-of-the-art techniques uses bidirectional LSTMs to solve this problem. We propose a deeply bidirectional model that uses parallelized transformer encoders to encode, which can impart bidirectionality to the model which aids in efficient learning. Our proposed model gives a logical form accuracy of 52.2% and an execution accuracy of 67.9%.
Assess the applicability of Agile frameworks in an engineering solutions development project previously managed by traditional methods.

The purpose of this thesis is to identify the main project management problems faced by an engineering solutions development department of a large group. From these problems, we have identified needs that are not being met by traditional project management methods. We therefore asked ourselves the question of the applicability of agile methods in this context. After the implementation and a feedback on the difficulties encountered, we finished the thesis on recommendations open to any company willing to embark on the agile transformation process.
Compressed Sensing Demystified

As mentioned previously, contemporary digital display devices and image processing software imply by default that sampling over regular square sampling lattices is used for image sampling.
Didactic features of the organization of computer means of teaching students of mathematical specialties

The article is devoted to the description of didactic approaches that allow to integrate the theory and practice of teaching students of mathematical specialties by updating informative intra- and interdisciplinary connections of mathematical disciplines and informatics. Methods for implementing cognitive visualization taking into account the specifics of mathematics and computer science are given. The interpretation of interdisciplinary connections (as a category of teaching didactics) and visual modeling in relation to teaching mathematics are also clarified. The article describes a variant of the organization of content in the computer means of teaching (CMT) students of the classical university in mathematical analysis. The content of this course in one or another volume is a mandatory component of mathematical training in universities, it is consistently associated with the content of the course of school mathematics and is widely used in applied problems. On the basis of the analysis of semantics and logic of construction of formulations of those properties which are repeated in relation to various mathematical objects, the variant of content didactic clustering at which such concepts as “convergence”, “uniform convergence”, “differentiability”, etc., act as patterns in the organization of the maintenance of computer means of training is presented.
Multilevel Thresholding of Brain Tumor MRI Images: Patch-Levy Bees Algorithm versus Harmony Search Algorithm

Image segmentation of brain magnetic resonance imaging (MRI) plays a crucial role among radiologists in terms of diagnosing brain disease. Parts of the brain such as white matter, gray matter and cerebrospinal fluids (CFS), have to be clearly determined by the radiologist during the process of brain abnormalities detection. Manual segmentation is grueling and may be prone to error, which can in turn affect the result of the diagnosis. Nature inspired metaheuristic algorithms such as Harmony Search (HS), which was successfully applied in multilevel thresholding for brain tumor segmentation instead of the Patch-Levy Bees algorithm (PLBA). Even though the PLBA is one powerful multilevel thresholding, it has not been applied to brain tumor segmentation. This paper focuses on a comparative study of the PLBA and HS for brain tumor segmentation. The test dataset consisting of nine images was collected from the Tuanku Muhriz UKM Hospital (HCTM). As for the result, it shows that the PLBA has significantly outperformed HS. The performance of both algorithms is evaluated in terms of solution quality and stability.
Research on Case Preprocessing Based on Bert -CNN-LSTM Model

In this paper, we apply the deep learning algorithm to preprocess the criminal case information. By extracting the characteristics of the brief case field, the missing content of other required field is plugged through model training. The experimental results show that the precision rate of CNN-LSTM model is 3% higher than that of LSTM-CNN model in text classification. After the Bert model is integrated, the precision rate, recall rate, and F value are all improved by 10%. To the best of our knowledge, this is the first time to use Bert model in preprocessing criminal case information.
Beware brand concerns presented by variations of domain names

Domain names are alphanumeric character strings that substitute for the numerical addresses, or IP addresses, actually used by internet host computers to locate one another and provide requested information to end users. Like real property, every domain name is unique, and thus their scarcity means their brand function is important. Colleges and universities have an advantage in that the top‐level domain‐name extension . edu is widely recognized as signifying an involvement with higher education (although to be sure, owning a domain name in the . edu extension doesn't indicate accreditation).
Metaheuristics for solving mathematical programming problems

This undergraduate research aims to study metaheuristics for solving mathematical programming problems. In optimization's context, metaheuristics are strategies which use problem specific knowledge to, stochastically use solutions worse than the current in order to avoid local maximum or minimum. The literature about metaheuristics is huge and continues in expansion, mostly by its commercial interest, once most real problems are far too large to be solved by exact algorithms. This project considered a wide variety of metaheuristics and focused on a particular one: The Ant Colony Optmization applied to the Symmetric Travelling Salesman Problem (TSP).
JMentor: An Ontology-Based Framework for Software Understanding and Reuse

Understanding and reusing complex APIs is a difficult and time consuming process, especially in legacy code and open-source software libraries and frameworks. While some primary API features are documented properly, most others lack enough documentation and design knowledge that can help developers find, understand, and reuse the needed software components and other library features. As such, the source-code itself is often the only reliable means for programmers to rely on when performing their reuse practices. In order to leverage program understanding and software reuse, this paper describes an ontology-based system named JMentor that we have developed for this purpose. Firstly, JMentor is capable of recovering the lost design decisions by reverse engineering design patterns. Secondly, JMentor provides a mechanism for locating and retrieving reusable software components. Thirdly, JMentor provides an approach for automatically recommending source-code snippets that show an example of how the user can properly reuse the retrieved components. JMentor mechanisms are based on ontology and semantic reasoning techniques. Its evaluation case studies show evidence that such techniques can improve software understanding and reuse practices.
Official Development Assistance and Poverty Alleviation in Nigeria: An Error Correction Model Approach

This study is examined the relationship between official development assistance and poverty alleviation in Nigeria which majority of studies in the past have failed to explore.Consequently, the study utilized an error correction model to address its objective.The major findings in this study are as follows.There is a significant negative relationship between official development assistance and household consumption per capita in Nigeria.This implies that official development assistance has no capacity to alleviate the current worrisome level of poverty in this country.However, FDI contributes to poverty alleviation in Nigeria though not significant.Furthermore, 11% of the error caused by shock was corrected annually in the model.The study therefore makes these recommendations for the policy makers; whenever alleviation of poverty is the target of the policy makers in the country, the Nigerian government should be committed to the provision of conducive investment environment that can facilitate further inflows of FDI from the developed countries, especially G 7 and G 13 countries.Also, the policy makers in Nigeria should not compromise in tailoring official development assistance towards projects and programs that have trickle down effects on the masses in Nigeria.
CCA-Secure and Revocable Certificateless Encryption with Ciphertext Evolution

Certificateless cryptosystems have attracted great interests in cryptographic research since its invention. Because compared with traditional public key cryptosystems or identity-based cryptosystems, they could not only simplify the certificate management, but also alleviate the key escrow problem. In certificateless cryptosystems, user revocation is a challenging issue. To address this issue, one popular method is to update the key via public channels. However, most of the existing schemes in this approach are impractical because of the following two shortcomings. Firstly, the user needs to maintain a list of decryption keys, but the size of the list will keep increasing. Secondly, the revoked user can still recover the plaintexts of the encrypted data prior to revocation, and this is a particular threat in some applications. To solve these problems, this paper presents revocable certificateless encryption with ciphertext evolution. We give a generic construction and then describe how it can be initialized concretely. In our proposed scheme, the user only needs to keep one decryption key, and once a user is revoked, it can no longer decrypt any ciphertext in the server. Moreover, the IND-CCA security model is defined against three types of attacks. And our schemes are formally proved to satisfy these security requirements.
Intelligent Traffic Routing Based on Real-time Congestion Analysis

The problem of traffic congestion has led to several issues like an increase in carbon dioxide emission including the inability to route emergency vehicles on a priority. Hence we aim to find an optimized approach, allocating resources based on the traffic condition at that particular instant. This could be realized by analysing the traffic data relayed by device nodes present all over the city in a real-time environment. The node is a cloud-linked camera-integrated MPU equipped with GSM communication. The captured video frames are processed which is then analysed collectively to suggest the most appropriate route to the vehicles.
Text Processing Procedures for Analysing a Corpus with Medieval Marian Miracle Tales in Old Swedish

Text Processing Procedures for Analysing a Corpus with Medieval Marian Miracle Tales in Old Swedish
A Novel Integrated Strict Verification of Smart Contracts on Blockchain

Blockchain is an evolving technology which helps in keeping records and process transactions in decentralized manner. Blockchain is considered as safest medium because of its decentralized nature and many protocols, algorithms which it follows to make sure that transaction are immutable. Blockchain concept basically uses BZT theorem, this is considered as one of secured algorithm to predict secure results. however formal verification approach for the smart contract is still the best way to perform verification. In our paper, we have depicted various algorithm according to which we can verify the smart contract in best possible way.
Integral cryptanalysis, AES, symmetric key cryptology

AES is the mostly used block cipher nowadays.At CRYPTO 2016, Sun et al. proposed the first 5-round distinguisher of the AES [19].However, it is somewhat closely related with the keys and hardly be used to mount a key recovery attack.Later in FSE 2016 [12] and EUROCRYPT 2017 [13], the distinguisher was improved.In this paper, by combining the techniques proposed by Sun et al. at CRYPTO 2016, we find a new 3-round integral distinguisher of AES which is closely related with the round keys.Then, based on the new distinguisher, we develop new techniques and give a new integral cryptanalysis for the round-reduced AES.We believe this may give new insight on the security of the AES.
IMPACT OF SECTORAL ALLOCATION OF BANKS' CREDIT ON ECONOMIC GROWTH IN NIGERIA

Sectoralallocation ofcreditis a vitalfunction ofthe banking sectoras itenhances economic growth and development. However, contributions ofcredits byBanks to various sectors in Nigeria are notsufficient to the growth ofthe Nigerian economy in spite ofthe various reforms and development in the banking sector. Hence, this study examines the impact of sectoral allocation of banks' credit on economic growth in Nigeria. The study uses annual time series data obtained from the Central bank of Nigeria (CBN) statistical bulletins and National Bureau ofStatistics (NBS) annual reports covering the period of thirty years (1986-2015). The data were analysed using Augmented Dickey Fuller (ADF) unit root test, Johansen co-integration test, vector error correction model (VECM) and fully modified Ordinary Least Square (FMOLS) regression. The findings ofthis study reveal that a long-run relationship exists between economic growth and the explanatory variables. The results ofthe regression revealed that credit allocated to productive sector and broad money supply have a significant positive influence on economic growth in Nigeria at 1% level of significance, while credit allocated to general commerce, credit allocated to service sector and credit allocated to other sectors have a negatively significant effect on economic growth in Nigeria at 1% level of significance. Based on these findings, the study concludes that sectoral allocation of banks' credit has a significant impact on economic growth in Nigeria. Therefore, the study recommends that policy makers such as the Central Bank of Nigeria (CBN), the Nigerian Deposit Insurance Corporation (NDIC), Securities and Exchange Commission (SEC), amongst others should fashion out appropriate policies through the establishment of infrastructures that will enhance the bidirectional flow between the banking sectors from where investible funds are sourced, and the priority sectors where goods and services are produced.
Pengaruh Model Cooperative Script Terhadap Hasil Belajar Peserta

The purpose of the research was to find out the pos i tive and significant effects o f the cooperative script model to learning result . T he type of this research was experimental research. The research design used non-equivalent control group design. The students' population of this study was 45 students at the fourth grade . The data collection technique tools used cognitive test . The data analysis technique used t-test pooled varians H ypothesis testing result obtained t count =3.033 > t table = 2.021 (α=0.05), the conclusion of this research showed that there was a positif and significant of the cooperative script model application to student result . Tujuan penelitian adalah mengetahui pengaruh yang positif dan signifikan pada penerapan model cooperative script terhadap hasil belajar. Jenis penelitian ini adalah penelitian eksperimen. Desain penelitian yang digunakan yaitu non-equivalent control group design . Populasi penelitian berjumlah 45 orang peserta didik kelas IV. Teknik pengumpulan data menggunakan tes kognitif. Teknik analisis data menggunakan uji t-test pooled varians . Hasil pengujian hipotesis diperoleh data t hitung =3,033 > t tabel = 2,021 (α=0,05), dapat disimpulkan hasil penelitian menunjukan terdapat pengaruh yang positif dan signifikan pada penerapan model pembelajaran cooperative script terhadap hasil belajar peserta didik. Kata kunci : cooperative script , hasil belajar, model pembelajaran
PROTOTYPING OF CAPRICIOUS D–DRONE

A hybrid of a quad-copter and an all-terrain tank has been called ‘Unmanned  Aerial  and Ground Vehicle’ or UAGV. Their use has increased drastically because they are multifunctional and reliable. It's capable of driving across rough terrain, armed with 4 propellers that allow it to take off once the obstacle becomes too big to drive over. The project would have an impact on carrying out future rescue missions and would provide visual and audio aid to the people in distress. This paper tries to give cost effective measures to improve upon some features  of ‘drones’ used in the military, construction sitemonitoring.
Analysis of Deep Metric Learning Approaches

This article aims to demonstrate the value of deep metric learning considering recent studies. Most existing studies are inspired by Siamese and Triplet networks that build a high-level representation of samples in separable linear space. The success and main idea of these networks is the ability to capture the similarity relationship between samples in the dataset. There are mainly three components: sampling method, loss function, and neural network architecture that determine the metric learning model. Improvement of these components is the main challenge for researchers. This article is a review and analysis of deep metric learning components.
Improving collaborative filtering's rating prediction coverage in sparse datasets by exploiting the 'friend of a friend' concept

In collaborative filtering users with highly similar tastes are termed 'near neighbours' and recommendations for a user are based on her 'near neighbours' ratings. However, for a number of users no near neighbours can be found, a problem termed as the 'grey sheep' problem. This problem is more intense in sparse datasets. In this work, we propose an algorithm for alleviating this problem by exploiting the friend of a friend (FOAF) concept. The proposed algorithm, CFfoaf, has been evaluated against eight widely used sparse datasets and under two widely used collaborative filtering correlation metrics, namely the Pearson Correlation Coefficient and the Cosine Similarity and has been proven to be particularly effective.
15 PhD positions in GRAPES

We are pleased to announce 15 open PhD Positions within the new European Network GRAPES: Learning, Processing and Optimising Shapes. GRAPES is a Marie Sk lodowska-Curie Innovative Training Network in the framework of H2020, started on December 1st, 2019, and lasting for 4 years. It includes 11 academic/industrial groups o.ering 15 PhD's, and 6 associated partners; it is coordinated by ATHENA Research &amp; Innovation Center, Greece. GRAPES aims at advancing the state-of-the-art in Mathematics, Computer-Aided Design, and Machine Learning, in order to promote game changing approaches for generating, optimising, and learning 3D shapes, along with a multisectoral training for young researchers, supported by the active participation of SMEs. Recent advances in the above domains have solved numerous tasks concerning multimedia and 2D data. However, automation of 3D geometry processing and analysis lags severely behind, despite their importance in science, technology and everyday life, and some well-understood underlying mathematical principles. Concrete applications include simulation, manufacturing and 3D printing, visualisation and naval design, retrieval and mining, reconstruction and urban planning.
Not yet the default setting - in 2020 open research remains a work in progress.

Responding to Daniel Hook’s post, The Open Tide – How openness in research and communication is becoming the default setting, Daniel Spichtinger argues that there remains much work to be done in order for open research practices to become the “new normal”. Highlighting unresolved issues around learned societies and the globalisation of open research policies, he suggests that rather than floating passively on a rising tide, building a truly open research system will require continued innovation particularly at the level of policy development and implementation.
A Modified Student Teams Achievement Divisions (MSTAD) to Enhance Students’ Vocabulary Achievement

Penelitian ini dilaksanakan untuk mengetahui i) perbedaan signifikan dalam pencapaian kosa kata antara siswa yang diajar dengan teknik STAD dan teknik MSTAD dan ii) untuk menyelidiki persepsi siswa terhadap teknik MSTAD. Penelitian ini menerapkan desain eksperimental sejati. Ada 32 siswa eksperimen dan 30 siswa kontrol sebagai sampel yang dipilih secara acak di SMAN 3 Bandar Lampung. Instrumen yang digunakan adalah tes kosa kata, kuesioner dan wawancara. Hasil penelitian menunjukkan bahwa ada perbedaan yang signifikan secara statistik dalam prestasi kosa kata antara siswa yang diajar dengan teknik STAD dan teknik MSTAD. Ini menunjukkan bahwa teknik pengajaran kosa kata adalah salah satu faktor yang mempengaruhi prestasi kosa kata siswa. Selain itu, penggunaan teknik MSTAD dalam pengajaran kosa kata dianggap lebih efektif untuk meningkatkan prestasi kosa kata siswa. The research was implemented to find out i) the significant difference in vocabulary achievement between students who are taught with the STAD technique and the MSTAD technique and ii) to investigate the students’ perceptions towards MSTAD technique. This study applied the true experimental design. There were 32 experimental students and 30 control students as the sample chosen randomly at SMAN 3 Bandar Lampung. The instruments used were the vocabulary test, questionnaire and interview. The result showed that there was a statistically significant difference in vocabulary achievement between students who were taught with the STAD technique and MSTAD technique. It indicates that the vocabulary teaching technique is one of the factors which affects the students’ vocabulary achievement. Furthermore, the use of MSTAD technique in teaching vocabulary is regarded as being more effective to enhance the students’ vocabulary achievement. Keywords: MSTAD, STAD, vocabulary achievement.