Reviewerly/exHarmony huggingface dataset:
Evaluation of Entrepreneurial Support Projects by Using IFS Type-2 Fuzzy Sets

Entrepreneurial activities are essential for increasing a nation’s wealth. Successful innovations initiated by the entrepreneurial ventures/startups may improve life quality, create new business areas and decrease the unemployment rate. Therefore, many countries provide various supports including financial support to entrepreneurial companies or start-ups. The selection of the companies that are going to be supported is a laborious process that includes uncertainty and imprecision. Not only the tangible factors such as technical capacity but also the soft factors such as the leadership skills of the management team should be considered in this process. Experience, funding methods of the business, business networking, business plans, and marketing strategies are the factors that can be considered for the evaluation of entrepreneurial projects. For the funding type, the external and personal investment can be regarded as while under the business plan: utilizing business networking, utilizing family for advice, utilizing friends for advice, and utilizing the internet as a source of information can be considered. In this study, IFS Type-2 fuzzy sets are utilized for the evaluation of entrepreneurial support.
Accelerate proposal generation in R-CNN methods for fast pedestrian extraction

Purpose The purpose of this study is to develop a novel region-based convolutional neural networks (R-CNN) approach that is more efficient while at least as accurate as existing R-CNN methods. In this way, the proposed method, namely R 2 -CNN, provides a more powerful tool for pedestrian extraction for person re-identification, which involve a huge number of images and pedestrian needs to be extracted efficiently to meet the real-time requirement. Design/methodology/approach The proposed R 2 -CNN is tested on two types of data sets. The first one the USC Pedestrian Detection data set, which consists of three sub-sets USC-A, UCS-B and USC-C, with respect to their characteristics. This data set is used to test the performance of R 2 -CNN in the pedestrian extraction task. The speed and performance of the investigated algorithms were collected. The second data set is the PASCAL VOC 2007 data set, which is a common benchmark data set for object detection. This data set was used to analyze characteristics of R 2 -CNN in the case of general object detection task. Findings This study proposes a novel R-CNN method that is both more efficient and more accurate than existing methods. The method, when used as an object detector, would facilitate the data preprocessing stage of person re-identification. Originality/value The study proposes a novel approach for object detection, which shows advantages in both efficiency and accuracy for pedestrian detection task. It contributes to both data preprocessing for person re-identification and the research on deep learning.
Adaptive Noise Injection against Side-Channel Attacks on ARM Platform

In recent years, research efforts have been made to develop safe and secure environments for ARM platform.The new ARMv8 architecture brought in security features by design.However, there are still some security problems with ARMv8.For example, on Cortex-A series, there are risks that the system is vulnerable to sidechannel attacks.One major category of side-channel attacks utilizes cache memory to obtain a victim's secret information.In the cache based side-channel attacks, an attacker measures a sequence of cache operations to obtain a victim's memory access information, deriving more sensitive information.The success of such attacks highly depends on accurate information about the victim's cache accesses.In this paper, we describe an innovative approach to defend against side-channel attack on Cortex-A series chips.We also considered the side-channel attacks in the context of using TrustZone protection on ARM.Our adaptive noise injection can significantly reduce the bandwidth of side-channel while maintaining an affordable system overhead.The proposed defense mechanisms can be used on ARM Cortex-A architecture.Our experimental evaluation and theoretical analysis show the effectiveness and efficiency of our proposed defense.
Dispersed Cyber-Physical Coordination and Path Planning Using Unmanned Aerial Vehicle

Dispersed Cyber-Physical Coordination and Path Planning Using Unmanned Aerial Vehicle Alexey Bulgakov, Daher Sayfeddine, Thomas Bock and Sergei Emelianov Pages 730-734 (2019 Proceedings of the 36th ISARC, Banff, Canada, ISBN 978-952-69524-0-6, ISSN 2413-5844) Abstract: In recent years, drones have been used exclusively for military missions, but with the advent of new characteristics in UAV technology, more industries are now moving to add this new element to their practices. Engineers and analysts use UAVs to monitor projects, scan the ground, find out its dimensions and reduce the incidence of costly errors. The Drones improved the world over the next years and its use becomes a general trend in all areas, including industrial. Technology can be said to have a way of breaking down barriers and making impossible. The emergence and spread of a technological event is one of the key features that ensure the continuation of technological progress, and also guarantees us the creation of best products that the future holds. In this paper, we analyze a close coordination between dispersed cyber-physical system parts; aiming to mount pre-casted concrete pergola sections on rooftop of a building. The system consist of a manipulating robotized crane, moving the sections of pergola to the top level and positioning them according to a predefined shape. For better positioning of the sections, the trajectory of the manipulating system, in terms of lifting altitude, and two-dimensional positioning, is coordinated using unmanned aerial vehicle. Keywords: Cyber-physical system; UAV; Robot path planning DOI: https://doi.org/10.22260/ISARC2019/0098 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
Combinational Counters: A Low Overhead Approach to Address DPA Attacks

Differential Power Analysis (DPA) attacks are known as viable and practical techniques to break the security of cryptographic algorithms. In this type of attack, an adversary extracts the encryption key based on the correlation of consumed power of the hardware running encryption algorithms to the processed data. To address DPA attacks in the hardware layer, various techniques have been proposed thus far. However, current techniques generally impose high performance overhead. Especially, the power overhead is a serious issue which may limit the applicability of current techniques in power-constrained applications. In this paper, combinational counters are explored as a way to address the DPA attacks. By randomizing the consumed power in each clock cycle of the circuit operation, these counters can enhance the resistance of the cryptographic cores against DPA attacks with low power overhead as well as zero timing overhead. Experimental results for an AES S-Box module in 45[Formula: see text]nm technology reveal that the proposed technique is capable of achieving higher level of security in comparison to two other approaches while preserving the power and performance overhead at a same or lower level.
Automating Text Simplification Using Pictographs for People with Language Deficits

Automating text simplification is a challenging research area due to the compound structures present in natural languages.Social involvement of people with language deficits can be enhanced by providing them with means to communicate with the outside world, for instance using the internet independently.Using pictographs instead of text is one of such means.This paper presents a system which performs text simplification by translating text into pictographs.The proposed system consists of a set of phases.First, a simple summarization technique is used to decrease the number of sentences before converting them to pictures.Then, text preprocessing is performed including processes such as tokenization and lemmatization.The resulting text goes through a spelling checker followed by a word sense disambiguation algorithm to find words which are most suitable to the context in order to increase the accuracy of the result.Clearly, using WSD improves the results.Furthermore, when support vector machine is used for WSD, the system yields the best results.Finally, the text is translated into a list of images.For testing and evaluation purposes, a test corpus of 37 Basic English sentences has been manually constructed.Experiments are conducted by presenting the list of generated images to ten normal children who are asked to reproduce the input sentences based on the pictographs.The reproduced sentences are evaluated using precision, recall, and F-Score.Results show that the proposed system enhances pictograph understanding and succeeds to convert text to pictograph with precision, recall and F-score of over 90% when SVM is used for word sense disambiguation, also all these techniques are not combined together before which increases the accuracy of the system over all other studies.
Educational services promotion in line with the experiential marketing philosophy

We consider the aspects of experiential marketing development as a marketing philosophy. The direction of experiential marketing was developed in line with experience economy. The concept is based on the thesis that a product or service purchase is accompanied by the impressions formation from the purchase process, and the nature of these impressions determines the consumers’loyalty to the brand of the company that offers goods or services. Experiential marketing develops at the junction of relationship marketing, emotional marketing, event marketing and show marketing. Experiential marketing is designed to make the process of purchasing a product or service more personalized. Experiential marketing began to be applied in areas related to sales of impression (hotel, restaurant business, etc.). The idea of marketing is used in the process of promoting university educational services. We cover the event promotion cases of Derzhavin Tambov State University, the essence of which reflects the ideas of experiential marketing. As a case study, we focus on experience of holding a special event “Night at Tambov State University named after G.R. Derzhavin”, aimed at development of positive impression among the guests. One of the “Night at Tambov State University named after G.R. Derzhavin” tasks was to demonstrate the university capabilities in an informal way, different from traditionally held events.
Capturing AIS Behavior Using xAPI-like Statements

In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the learners interact with the learning resources in a given learning environment following preset steps of learning processes. From this foundation, we make several subsequent arguments. (1) All intelligent digital resources such as intelligent tutoring systems (ITS) need to be well-documented with standardized metadata scheme. We propose a learning science extension of IEEE learning object metadata (LOM). specifically, we need to consider cognitive learning principles that have been used in creating the intelligent digital resources. (2) We need to consider AIS as whole when we record system behavior. Specifically, we need to record all four components delineated above (the learners, the resources, the environments, and the processes). We point to selected learning principles from the literature as examples for implementation of this approach. We concretize this approach using AutoTutor, a conversation-based ITS, serving as a typical intelligent digital resource.
A New Structural Template Design of Control Instruction for Semantic Analysis

To solve conflicts attributable to controller error, automatic speech recognition (ASR) and natural language processing (NLP) can be used to extract control instruction for first-time understanding, avoiding potential conflict. The semantic understanding of the control instruction is crucial to the final judgment of scene conflict. Therefore, a new structural template is proposed, which is designed according to both the rule of radiotelephony air-ground communication and dependent grammar. In order to understand the verb-argument-relationship, the theory of case grammar is given. This template can better analyze the control instruction in the actual working environment and realize the function of automatic understanding of the control instruction. ASR and NLP will be applied to turn control speech into structured control instruction. Finally, the experimental results show that the template can be used to understand the control instruction automatically.
A Linking Belief is Not Essential for Reasoning

In reasoning, you acquire a new conclusion attitude on the basis of premise attitudes. It is commonly thought that an essential feature of reasoning is that you have a linking belief, which is a belief that the premises imply the conclusion. This chapter shows that a linking belief is not essential for reasoning. A genuinely essential feature of reasoning is that you acquire the conclusion attitude by following a rule. A linking belief may be a necessary feature of theoretical reasoning, because it may be a consequence of having the disposition to follow a rule. But it is not essential for reasoning, which is to say that it does not contribute to making the process reasoning. For other sorts of reasoning including practical reasoning, a linking belief is not even necessary.
Learning Analytics of Playing Space Fortress with Reinforcement Learning

In this paper we analyze the learning process of a neural network-based reinforcement learning algorithm while making comparisons to characteristics of human learning. For the task environment we use the game of Space Fortress which was originally designed to study human instruction strategies in complex skill acquisition. We present our method for mastering Space Fortress with reinforcement learning, identify similarities with the learning curve of humans and evaluate the performance of part-task training which corresponds to earlier findings in humans.
ANALISIS PELAPORAN KEUANGAN PENDIDIKAN ANAK USIA DINI (PAUD) KB ASSA’DAH CIKUPA DENGAN PENDEKATAN PERNYATAAN STANDAR AKUNTANSI KEUANGAN

Financial reporting is all aspects related to the provision and delivery of financial information. Early Childhood Education (PAUD) is a non-profit organization, in which the source of funds comes from the government and the community. In carrying out activities, Early Childhood Education (PAUD) requires an accounting system to produce financial information as a tool to ensure accountability and transparency in the implementation of educational activities, accounting in education aims for accountability, managerial and supervisory. The purpose of this study was to analyze KB Assa’adah Cikupa's PAUD Financial Reporting with the PSAK 45 approach. In this study the data used was qualitative data, while for data sources using secondary data, the analytical method used was descriptive analysis. Based on the results of the study, concluded that the KB Assa’adah Cikupa PAUD Financial Reporting was not in accordance with the applicable regulations, namely the Statement of Financial Accounting Standards (PSAK) 45
Greater Aceh, Indonesia Enters Climate Change: Climate on Extreme ENSO 2015-2016

The objective of the study is to analyse the rainfall variability and temperature over Greater Aceh and its correlation to ENSO event. Long-term rainfall observation data spanning from 1982-2018 was retrieved from meteorological station of Blang Bintang, Greater Aceh. The Pearson correlation was employed to find the relationship between rainfall and El Nino and Southern Oscillation (ENSO) occurrence. It is shown from frequency analysis that rainfall decreased in the 90s. After the tsunami as climate change become unequivocal the rainfall trend increase as a result of land use change and much worst as severe ENSO 2015 arrived over the region which statistically significant was found between those two corresponding events. During El Nino, rainfall is less while La Nina more rainfall than normal drop over the region. To cope with climate change issues where ENSO is very likely to occur in future time, an appropriate mitigation is required to conduct for instance: managing forest resources and land use by reducing deforestation and land conversion, the control of fossil fuel burning, and the most important thing is to establish a renewable energy as an effort to implement sustainable green energy in the future as well as climate risk reduction.
Fusion of Hand-crafted and Deep Features for Empathy Prediction

We propose an approach to the OMG-Empathy Challenge for predicting self-annotated, continuous values of valence within the range [-1,1]. We propose the fusion of hand-crafted and deep features, extracted from both actor and listener data, to predict these valence levels. The handcrafted features include image level fusion, facial landmarks, and spectrogram features. Our proposed fusion approach can utilized in multiple parts (i.e. sub-modules), specifically utilized for the generalized track, leading to unique submissions to address the challenge problem. First, both actor and listener images are fused at the image-level. Secondly, facial landmarks from both the actor and listener are fused into one feature vector which is then used to train a random forest for prediction of continuous valence levels. Finally, we use a weighted fusion of the predicted values from both hand-crafted and deep features. We show competitive results on the OMG-Empathy challenge validation set.
PENGOLAHAN DAN ANALISIS DATA KUANTITATIF MENGGUNAKAN APLIKASI SPSS

Abstrak. Statistika adalah salah satu cabang dalam Matematika. Statistika merupakan yang mempelajari bagaimana merencanakan, mengumpulkan, menganalisis, menginterpretasi, dan mempresentasikan  data . Statistika adalah yang berkenaan dengan data. Penggunaan istilah  Statistika  berakar dari istilah-istilah dalam bahasa latin modern  statisticum collegium  (dewan negara) dan bahasa Italia  statista  (negarawan atau politikus).  Gottfried Achen-wall  (1749) menggunakan  Statistik  dalam  bahasa Jerman  untuk pertama kalinya sebagai nama bagi kegiatan analisis data kenegaraan, dengan mengartikannya sebagai ilmu tentang negara ( state Statistika banyak diaplikasikan dalam program SPSS ( Statistical Package for the Socialt Sciences ). Pengertian SPSS diciptakan untuk proses mengolah data dalam bidang sosial, dan saat itu SPSS merupakan singkatan dari  Statistical Package for the Social Science . Namun, sekarang fungsi SPSS sudah diperluas untuk melayani berbagai jenis  user  seperti untuk proses produksi pabrik, riset ilmu  science , dan lainnya. SPSS juga biasa digunakan dalam pengolahan data kuantitatif. Kata kunci : Matematika, Statistika, SPSS Abstract. Statistics is one branch of science in Mathematics. Statistics is the study of how to plan, collect, analyze, interpret, and present data. Statistics is the science relating to data. The use of the term Statistic is rooted in terms of the Latin modern statisticum collegium (Italian state council) and Italian statista (statesman or politician). Gottfried Achen-wall (1749) used Statistics in German for the first time as a name for state data analysis activities, meaning state. Statistics are widely applied in the SPSS program (Statistical Package for the Socialt Sciences). The definition of SPSS was created for the process of processing data in the social sciences field, and at that time SPSS was an abbreviation for Statistical Package for the Social Science. However, now the SPSS function has been expanded to serve various types of users such as factory production processes, science research, and others. SPSS is also commonly used in processing quantitative data. Keywords : Mathematics, Statistics, SPSS
Pseudo Credal Networks for Inference With Probability Intervals

Abstract The computation of the inference corresponds to an NP-hard problem even for a single connected credal network. The novel concept of pseudo networks is proposed as an alternative to reduce the computational cost of probabilistic inference in credal networks and overcome the computational cost of existing methods. The method allows identifying the combination of intervals that optimizes the probability values of each state of the queried variable from the credal network. In the case of no evidence, the exact probability bounds of the query variable are calculated. When new evidence is inserted into the network, the outer and inner approximations of the query variable are computed by means of the marginalization of the joint probability distributions of the pseudo networks. The applicability of the proposed methodology is shown by solving numerical case studies.
Generating interpretable reinforcement learning policies using genetic programming

The search for interpretable reinforcement learning policies is of high academic and industrial interest. Especially for industrial systems, domain experts are more likely to deploy autonomously learned controllers if they are understandable and convenient to evaluate. Basic algebraic equations are supposed to meet these requirements, as long as they are restricted to an adequate complexity. In our recent work "Interpretable policies for reinforcement learning by genetic programming" published in Engineering Applications of Artificial Intelligence 76 (2018), we introduced the genetic programming for reinforcement learning (GPRL) approach. GPRL uses model-based batch reinforcement learning and genetic programming and autonomously learns policy equations from preexisting default state-action trajectory samples. Experiments on three reinforcement learning benchmarks demonstrate that GPRL can produce human-interpretable policies of high control performance.
An Ontological Approach to Meaning Making through PATH and Gestalt Foregrounding in Climax

Climax is a compound rhetorical figure, consisting of the trope, Crementum, and the scheme, Gradatio (itself a series of Anadiploses), a combination that results in compelling semiotic effects. The component figures impact the conveyed meaning independently and collectively, which we chart by way of the PATH image schema and the Gestalt Figure-Ground relation. These layers of meaning function in a similar fashion to the dual figure visual phenomenon examined by Koffka and Rubin. Key elements of our project include knowledge representation of Climax and component figures, a suite of ontologies that map the cognitive features supporting these complex structures and a base model of surface entities augmented with the related cognitive functions. Our ontologies are developed in the Web Ontology Language (OWL), validated for consistency and published online.
Azure Kubernetes Service

Previous chapters discussed the benefits and various challenges of microservices applications. By now, it’s quite clear that orchestrators are the backbone of the microservices ecosystem. We also discussed Azure Service Fabric and the various options to deploy microservices applications. Azure Kubernetes Service (AKS) is a vast subject; however, we will cover the fundamental details required to deploy microservices applications. There are practical scenarios along with hands-on code to give you a fair idea of how easy it is to adopt AKS.