Miracle-dz/UniFAR-FTUs huggingface dataset:
ARCHAEOLOGICAL ARTIFACTS AS EXPRESSIVE DESIRE OF HINDU-BUDDHA RELIGIONS IN JAVA IN 8th– 15th CENTURIES

This study discusses the Hindu-Buddha religions in the ancient Javanese society which developed in 8—15 th Century AD when the centers of the kingdoms in the central part of Java. The case discussed in this paper is concerned with their ritual and ceremony tools used by the worshipped of Hindu-Buddha religions, especially in the regards with the statues of Hindu-Buddha gods, which are still used up to the present time. The statues of Hindu-Buddha gods are actually the realization of wishes to fulfill their worshipper hopes. This study in line with the opinion of Melford E.Spiro (1977), an expert on religion studies, who states that religion tools and rituals can be considered as expressive desires of the religion worshipper. The statues of Gods, temple structure, and reliefs function ot only as decorative matters, but also as expressive desire of silpins (religious artisants) and the community who performs the rituals in regard with their belief. It can be said that these silpin in the ancient Javanese society were doing religious ceremonies and their dedication to their Gods while they were constructing to the statues, reliefs, and temple. It is then these silpins are expressing (1) their dedication to the God by designing certain statues or narrative reliefs, and (2) personal and community expresses in creating religiously aesthetic artifacts.
A Bayesian approach to multivariate and multilevel modelling with non-random missingness for hierarchical clinical proteomics data

High throughput mass-spectrometry-based proteomics data from clinical studies brings challenges to statistical analysis. The challenges originate from the hierarchical levels of protein abundance data and interactions between clinical study design and experimental design. The non-random missingness of the measurements from a vast amount of information also adds complexity in data analysis. We propose multivariate multilevel models to analyse protein abundances and to handle abundance-dependent missingness within a Bayesian framework. The proposed model enables the variance decomposition at different levels of the data hierarchy and provides shrinkage of protein-level estimates for a group of proteins. A logistic missingness and censored model with informative prior is used to handle incomplete data. Hamiltonian MC/No-U-Turn Sampling and Gibb MCMC algorithms are created to derive the posterior distribution of study parameters; Hamiltonian MC is demonstrated to gain more efficiency for these high-dimensional correlated data. Improvements of the proposed missing data model is compared to the univariate mixed effect model and the multivariate-multilevel model using complete data in a simulated study and a clinical proteomics study. The proposed model framework can be used in other types of data with similar structure and Non Random Missingness mechanism (MNAR).
Adaptive Packet Filtering Techniques for Linux Firewall

Packet filtering techniques play an important role in many of network devices such as firewalls, IPSec Gateways. Firewall plays an important role in safeguarding any system from any external attacks to the system. It can be used to safeguard hosts as well as networks. This research focuses on studying the performance impact and the sensitivity of the Linux firewall (IP tables) also improve by using this research. And these are improving to become fast. A firewall designed in Linux, the user can edit the source code and change it depending on the security requirements for the LAN. At any time one can configure the firewall to encrypt, to decrypt, accept, deny, or proxy all packets that are being sent between any two systems depending on the rules. On the basis of this, the user can be blocked or given access to a network using a good tree algorithm. There are two approaches for the filtering, first by using the early rejection of unwanted flows without impacting other flows significantly. Second, we present a new packet filtering optimization technique that uses adaptive statistical search trees to utilize important traffic characteristics and minimize the average packet matching time. The proposed techniques timely adapt to changes in the traffic conditions by performing simple calculations for optimizing the search data structure. The proposed techniques can significantly minimize the packet filtering time with reasonable memory space requirements.
Modern Standard Arabic in the Minds of Diglossic Speakers of Arabic

This paper reinvestigates the cognitive relevance of Arabic diglossia in spoken word recognition through replicating Ibrahim & Aharon-Peretz’s study (2005) on a more typical diglossic situation of Arabic. The present study targets native speakers of Jordanian colloquial Arabic rather than Arabic-Hebrew bilinguals of Israel. A priming lexicaldecision task was designed and conducted on a group of 40 literate native speakers of Jordanian Colloquial Arabic. The experiment compared participants’ reaction times to Jordanian colloquial Arabic (JCA) words and Modern Standard Arabic (MSA) words when primed by semantically related and unrelated words from the same and the other variety of Arabic. Results revealed a processing advantage for JCA words relative to MSA words. The priming effects were larger when the related primes were presented in JCA relative to the priming effects of the MSA primes. The research findings support the proposal that MSA is an L2 for diaglossic speakers of Arabic (Ibrahim & Aharon-Peretz, 2005). The findings reject the proposal that MSA is an exceptional L2 for Arabic-Hebrew bilingual of Israel, a thing that cannot be generalized to the rest of the Arab-speaking world (Boudelaa & Marslen-Wilson, 2013).
Analysis of multipath channel fading techniques in wireless communication systems

Multipath fading occurs in any environment where there is multipath propagation and there is some movement of elements within the radio communications system. This may include the radio transmitter or receiver position, or in the elements that give rise to the reflections. The multipath fading can often be relatively deep, i.e. the signals fade completely away, whereas at other times the fading may not cause the signal to fall below a useable strength. Multipath fading may also cause distortion to the radio signal. As the various paths that can be taken by the signals vary in length, the signal transmitted at a particular instance will arrive at the receiver over a spread of times. This can cause problems with phase distortion and inter symbol interference when data transmissions are made. As a result, it may be necessary to incorporate features within the radio communications system that enables the effects of these problems to be minimized. This paper analyses the effects of various types of multipath fading in wireless transmission system.Multipath fading occurs in any environment where there is multipath propagation and there is some movement of elements within the radio communications system. This may include the radio transmitter or receiver position, or in the elements that give rise to the reflections. The multipath fading can often be relatively deep, i.e. the signals fade completely away, whereas at other times the fading may not cause the signal to fall below a useable strength. Multipath fading may also cause distortion to the radio signal. As the various paths that can be taken by the signals vary in length, the signal transmitted at a particular instance will arrive at the receiver over a spread of times. This can cause problems with phase distortion and inter symbol interference when data transmissions are made. As a result, it may be necessary to incorporate features within the radio communications system that enables the effects of these problems to be minimized. This paper analyses the effects of various types of multipath f.
A hybrid MacCormack-type scheme for computational aeroacoustics

A new hybrid MacCormack-type scheme is presented, using a modified Low Dissipation and Dispersion Runge-Kutta time marching scheme. This new hybrid scheme has two stages in every step which use biased differencing stencils of the standard MacCormack-type scheme and for the remaining stages using the central differencing stencils. The resulting scheme has the inherent artificial dissipation of a MacCormack-type scheme while retaining the relative ease of boundary condition specification of a two-stage MacCormack scheme.
The impact of reviews on the internet on the financial results of a hotel company

Artykul teoretycznie analizuje wplyw opinii hotelu w Internecie na wyniki finansowe firmy hotelarskiej. Artykul zawiera przegląd literatury koncentrującej sie na biznesie hotelowym i koncepcji zarządzania reputacją, ktore wplywają na decyzje podejmowane przez gości. Przedstawiono dotychczasowe wyniki badan akademickich w tej dziedzinie, ze szczegolnym uwzglednieniem wplywu opinii w Internecie na rezerwacje uslug hotelowych, a tym samym przychody finansowe hoteli. Celem artykulu jest przegląd i podsumowanie dotychczasowych badan, poniewaz obecnie akademickie pole eksploracji w tej dziedzinie jest w wiekszości nieznane w literaturze polskiej. Wnioski z tego artykulu wskazują, iz opinie online mają ogolnie pozytywny wplyw na decyzje konsumentow dotyczące zakupu uslug hotelowych. Wskazac takze mozna korelacje miedzy rekomendacjami internetowymi konsumentow a wynikami finansowymi hoteli.
Improvement of Email And Twitter Classification Accuracy Based On Preprocessing Bayes Naive Classifier Optimization In Integrated Digital Assistant

This research focuses on improving the accuracy of email and twitter classification. Spelling mistakes and lack of matches with bag of word causes the low accuracy in classifying. This research used naive Bayes as a text classification algorithms. Text is divided into three categories: personal, work and family. To achieve maximum likelikehood value for the category, a better preprocessing techniques is needed. It is necessary for the process to normalize the preprocessing and search for words that correspond to classes in the bag of word. So that the text can be classified by category or has a higher precision accuracy.
Selective Green Device Discovery for Device-to-Device Communication

The D2D communication is expected to improve devices’ energy-efficiency, which has become a major requirement of the future wireless network. Before the D2D communication can be performed, the device discovery between devices must be done. The previous works usually only assumed one mode of device discovery, i.e. either use network-assisted (with network supervision) or independent (without network supervision) device. Therefore, we propose a selective device discovery for device-to-device (D2D) communication that can utilize both device discovery modes and maintain devices’ energy-efficiency. Different from previous works, our proposed method selects the best device discovery mode to get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy expectation. Our experiment result indicates that the proposed method provides lowest energy consumption per new accepted device while compared with schemes with full network-assisted and independent device discovery in low numbers of new device arrival (for the number of new devices arrival = 1 ~ 3).
Extended TvX: A New Method Feature Based Semantic Similarity for Multiple Ontology

Semantic similarity between the terms is the main phase in information retrieval and information integration, which requires semantic content matching. Semantic similarity function is important in psychology, artificial intelligence and cognitive science. The problem of integrating various sources is the matching between ontological concepts. In this paper, we proposed to develop this method by analyzing the semantic similarity between the modeled taxonomical knowledge and features in different ontology. This paper contains a review on semantic similarity and multiple ontology that focuses on the feature-based approach. Besides that, we proposed a method, namely a semantic similarity that overcomes the limitation of different features of terms compared. As a result, we are able to develop a better method that improves the accuracy of the similarity measurement.
Multitier decentralized control scheme using energy storage unit and load management in inverter-based AC microgrids

The use of renewable energies, such as wind and solar, is rising in microgrids. However, because of their intermittent nature, achieving a stable system in spite of the fluctuations of generation and demand is very difficult. Aiming to increase the stability margin of AC islanded microgrids comprising nondeterministic resources, properly share real power (P), and keep the network frequency (f) at nominal value, this study exploits the presence of energy storage units (ESUs) along with a load-shedding scheme. To this end, this study proposes a multitier decentralized control strategy that is based on frequency and includes three control schemes, distributed generation unit (DGU) control, ESU control, and local loads control (LLC). These controllers operate simultaneously. The DGU controller shares the loads among DGUs in accordance with the frequency droop method. On the other hand, the ESU controller controls the production of ESUs and also the LLCs manage the loads and dump-load of the microgrid. This method ensures the proper operation of AC microgrids that comprise intermittent resources under stand-alone conditions and despite numerous events. The time responses of P and f prove the high performance of the method. The simulations are performed and coded in m-file of MATLAB.
Leveraging Internal Resources for Business Sustainability in Independent Quick-Service Restaurants

Leveraging Internal Resources for Business Sustainability in Independent Quick-Service Restaurants by Mario D. Wallace MEd, University of Arkansas at Little Rock, 2015 BA, University of Arkansas at Little Rock, 2013 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration
To Study the Functionality and Performance of Web Services

Nowadays, the ability to smoothly exchange information between internal business units, customers, and partners is essential for success. On the other hand, most administrations service a variety of disparate applications that store and exchange data in different ways and therefore cannot "talk" to one another effectively. Net Application and Access models have evolved as a practical, cost-effective solution for consolidate information distributed between critical applications over the operating system, platform, and language barriers that were previously blocked. This study presents the analytical review of Web services functionality and their performance through latency and throughput.
Effective methods for knowledge transfer to strengthen mental health systems in low- and middle-income countries

Background The Emerald project's focus is on how to strengthen mental health systems in six low- and middle-income countries (LMICs) (Ethiopia, India, Nepal, Nigeria, South Africa and Uganda). This was done by generating evidence and capacity to enhance health system performance in delivering mental healthcare. A common problem in scaling-up interventions and strengthening mental health programmes in LMICs is how to transfer research evidence, such as the data collected in the Emerald project, into practice. Aims To describe how core elements of Emerald were implemented and aligned with the ultimate goal of strengthening mental health systems, as well as their short-term impact on practices, policies and programmes in the six partner countries. Method We focused on the involvement of policy planners, managers, patients and carers. Results Over 5 years of collaboration, the Emerald consortium has provided evidence and tools for the improvement of mental healthcare in the six LMICs involved in the project. We found that the knowledge transfer efforts had an impact on mental health service delivery and policy planning at the sites and countries involved in the project. Conclusions This approach may be valid beyond the mental health context, and may be effective for any initiative that aims at implementing evidence-based health policies for health system strengthening.
SUPPLY CHAIN MANAGEMENT AND THE ACCOMPANYING PROBLEMS IN PRODUCTION ENVIRONMENT: A REVIEW

In production environment, supply chain system is a tool for attaining efficient production performance because it streamlines and optimizes the entire production processes. It appears that research efforts so far only supported arguments for the benefits of supply chain management in production environment without taking into account problems associated with the administration of supply chain system within production setting that constitute impediment to production throughput and make it difficult for manufacturers to satisfy customers’ demands. Consequently, the aim of the review effort is to highlight the importance of supply chain management and identifies the underlying bottleneck problems related to supply chain administration in production setting to guide stakeholders in policy formulation for further production performance. Notable among the problems identified that are attributable to supply chain organization in production environment are, supply disruption, lack of agility to respond to supply and demand fluctuation, inadequate logistics, lack of adaptation to evolving market, inaccuracy of information between the extended enterprises, ineffective integration and coordination of supply chain strategy across the functional units, lack of capacity and resources availability, lack of quality and regulation compliance. Based on the identified problems, we developed a supply chain appraisal tool for pre-qualification and selection of supply chain vendors in production environment.
Effective Task Transfer Through Indirect Encoding

An important goal for machine learning is to transfer knowledge between tasks. For example, learning to play RoboCup Keepaway should contribute to learning the full game of RoboCup soccer. Often approaches to task transfer focus on transforming the original representation to fit the new task. Such representational transformations are necessary because the target task often requires new state information that was not included in the original representation. In RoboCup Keepaway, changing from the 3 vs. 2 variant of the task to 4 vs. 3 adds state information for each of the new players. In contrast, this dissertation explores the idea that transfer is most effective if the representation is designed to be the same even across different tasks. To this end, (1) the bird’s eye view (BEV) representation is introduced, which can represent different tasks on the same two-dimensional map. Because the BEV represents state information associated with positions instead of objects, it can be scaled to more objects without manipulation. In this way, both the 3 vs. 2 and 4 vs. 3 Keepaway tasks can be represented on the same BEV, which is (2) demonstrated in this dissertation. Yet a challenge for such representation is that a raw two-dimensional map is highdimensional and unstructured. This dissertation demonstrates how this problem is addressed naturally by the Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT) approach. HyperNEAT evolves an indirect encoding, which compresses the representation by exploiting its geometry. The dissertation then explores further exploiting the power of such encoding, beginning by (3) enhancing the configuration of the BEV with a focus on
A privacy-preserving decentralized storage with payments based on a blockchain

ly speaking, each transaction in a blockchain is a state transition from some global state to another one. In Bitcoin these state transitions change the balance of the users. In Ethereum the state transitions correspond to computations in the EVM. Additionally to Ethereum, a second proposal to realize smart contracts in a blockchain setting is called Hawk [132]. In Hawk, financial transactions are not stored in clear on the blockchain but instead in an “encrypted” form, informally speaking. To achieve this, the compiler generates smart contracts which require cryptographic primitives such as zero knowledge proofs to interact with them.
Une méthodologie de sémantique de corpus appliquée à des tâches de fouille d’opinion et d’analyse des sentiments : étude sur l’impact de marqueurs dialogiques et dialectiques dans l’expression de la subjectivité

Cet article entend dresser, dans un premier temps, un panorama critique des relations entre TAL et linguistique. Puis, il esquisse une discussion sur l’apport possible d’une sémantique de corpus dans un contexte applicatif en s’appuyant sur plusieurs expériences en fouille de textes subjectifs (analyse de sentiments et fouille d’opinions). Ces expériences se démarquent des approches traditionnelles fondées sur la recherche de marqueurs axiologiques explicites par l’utilisation de critères relevant des représentations des acteurs (composante dialogique) et des structures argumentatives et narratives des textes (composante dialectique). Nous souhaitons de cette façon mettre en lumière le bénéfice d’un dialogue méthodologique entre une théorie (la sémantique textuelle), des méthodes de linguistique de corpus orientées vers l’analyse du sens (la textométrie) et les usages actuels du TAL en termes d’algorithmiques (apprentissage automatique) mais aussi de méthodologie d’évaluation des résultats.
Driver Safety -Iot Based Driver Gaze Tracking & Health Monitoring System

Driver Safety - Fatal Road accidents can be easily avoided by understanding the psychological state of drivers. Majority of road accidents occur during night driving due to drowsiness state of vehicle drivers (Subject). The proposed work monitors Eye Blink Monitoring System (EBM) that alerts the subject during state of drowsiness. This physiological sleep state analysis of subject can be determined by monitoring subject’s eye blink rate using an Open CV Library. A normal eye blink rate has no effect on the output of the system. However, subject is in extreme state of sleep cycle, then it will click picture of subject and send to web application, where administer is monitoring and send the message that will be converted into alarm is initiated to wake the subject. For Health Monitoring of driver we are making wearable device which will give the heart beat and body temperature of subject, so before boarding to vehicle admin should know the status of subject. For the proposed system the authors have used Bluetooth Technology to send sensor data to a Smartphone and also to web application for archiving and analysis. The information available on the web application can be supervised by the subject by using a Mobile application. Real tracking of driver will also track with mobile GPS.